honest truth about dishonesty 
by dan appropriately




Dedication
To my teachers, collaborators, and students,
for making research fun and exciting.
And to all the participants who took part in our
experiments over the years—you are the engine of this
research, and I am deeply grateful for all your help.
Contents
Title Page
Dedication
Introduction
Why Is Dishonesty So Interesting?
From Enron to our own misbehaviors … A fascination
with cheating … Becker’s parking problem and the birth of
rational crime … Elderly volunteers and petty thieves … Why
behavioral economics and dishonesty?
Chapter 1
Testing the Simple Model of Rational Crime (SMORC)
Get rich cheating … Tempting people to cheat, the
measure of dishonesty … What we know versus what we
think we know about dishonesty … Cheating when we can’t
get caught … Market vendors, cab drivers, and cheating the
blind … Fishing and tall tales … Striking a balance between
truth and cheating.
Chapter 2
Fun with the Fudge Factor
Why some things are easier to steal than others … How
companies pave the way for dishonesty … Token dishonesty
… How pledges, commandments, honor codes, and paying
with cash can support honesty … But lock your doors just the
same … And a bit about religion, the IRS, and insurance
companies.
Chapter 2B
Golf
Man versus himself … A four-inch lie … Whether ’tis nobler
in the mind to take the mulligan … Schrödinger’s scorecard.
Chapter 3
Blinded by Our Own Motivations
Craze lines, tattoos, and how conflicts of interest distort our
perception … How favors affect our choices … Why full
disclosure and other policies aren’t fully effective …
Imagining less conflicted compensation … Disclosure and
regulation are the answers—or not.
Chapter 4
Why We Blow It When We’re Tired
Why we don’t binge in the morning … Willpower: another
limited resource … Judgment on an empty stomach … How
flexing our cognitive and moral muscles can make us more
dishonest … Self-depletion and a rational theory of
temptation.
Chapter 5
Why Wearing Fakes Makes Us Cheat More
The secret language of shoes … From ermine to Armani and
the importance of signaling … Do knockoffs knock down our
standards of honesty? … Can gateway fibs lead to monster
lies? … When “what the hell” wreaks havoc … There’s no
such thing as one little white lie Halting the downward spiral.
Chapter 6
Cheating Ourselves
Claws and peacock tails … When answer keys tell us what we
already knew … Overly optimistic IQ scores … The Center
for Advanced Hindsight … Being Kubrick … War heroes and
sports heroes who let us down … Helping ourselves to a
better self-image.
Chapter 7
Creativity and Dishonesty: We Are All Storytellers
The tales we tell ourselves and how we create stories we can
believe … Why creative people are better liars … Redrawing
the lines until we see what we want … When irritation spurs
us onward … How thinking creatively can get us into trouble.
Chapter 8
Cheating as an Infection: How We Catch the Dishonesty
Germ
Catching the cheating bug … One bad apple really does spoil
the barrel (unless that apple goes to the University of
Pittsburgh) … How ambiguous rules + group dynamics =
cultures of cheating … A possible road to ethical health.
Chapter 9
Collaborative Cheating: Why Two Heads Aren’t Necessarily
Better than One
Lessons from an ambiguous boss … All eyes are on you:
observation and cheating … Working together to cheat more?
… Or keeping one another in line … Cheating charitably …
Building trust and taking liberties … Playing well with others.
Chapter 10
A Semioptimistic Ending: People Don’t Cheat Enough!
Cheer up! Why we should not be too depressed by this book
… True crime … Cultural differences in dishonesty …
Politicians or bankers, who cheats more? … How can we
improve our moral health?
Nondepleting Condition
Depleting Condition
List of Collaborators
Bibliography and Additional Readings
Searchable Terms
Thanks
About the Author
Notes
Other Books by Dan Ariely
Copyright
About the Publisher
INTRODUCTION
Why Is Dishonesty So Interesting?
There’s one way to find out if a man is honest—ask him.
If he says “yes,” he is a crook.
—GROUCHO MARX
My interest in cheating was first ignited in 2002, just a few months after the
collapse of Enron. I was spending the week at some technology-related
conference, and one night over drinks I got to meet John Perry Barlow. I knew
John as the erstwhile lyricist for the Grateful Dead, but during our chat I
discovered that he had also been working as a consultant for a few companies—
including Enron.
In case you weren’t paying attention in 2001, the basic story of the fall of the
Wall Street darling went something like this: Through a series of creative
accounting tricks—helped along by the blind eye of consultants, rating agencies,
the company’s board, and the now-defunct accounting firm Arthur Andersen,
Enron rose to great financial heights only to come crashing down when its
actions could no longer be concealed. Stockholders lost their investments,
retirement plans evaporated, thousands of employees lost their jobs, and the
company went bankrupt.
While I was talking to John, I was especially interested in his description of
his own wishful blindness. Even though he consulted for Enron while the
company was rapidly spinning out of control, he said he hadn’t seen anything
sinister going on. In fact, he had fully bought into the worldview that Enron was
an innovative leader of the new economy right up until the moment the story was
all over the headlines. Even more surprising, he also told me that once the
information was out, he could not believe that he failed to see the signs all along.
That gave me pause. Before talking to John, I assumed that the Enron disaster
had basically been caused by its three sinister C-level architects (Jeffrey Skilling,
Kenneth Lay, and Andrew Fastow), who together had planned and executed a
large-scale accounting scheme. But here I was sitting with this guy, whom I
liked and admired, who had his own story of involvement with Enron, which
was one of wishful blindness—not one of deliberate dishonesty.
It was, of course, possible that John and everyone else involved with Enron
were deeply corrupt, but I began to think that there may have been a different
type of dishonesty at work—one that relates more to wishful blindness and is
practiced by people like John, you, and me. I started wondering if the problem of
dishonesty goes deeper than just a few bad apples and if this kind of wishful
blindness takes place in other companies as well.
*
I also wondered whether my
friends and I would have behaved similarly if we had been the ones consulting
for Enron.
I became fascinated by the subject of cheating and dishonesty. Where does it
come from? What is the human capacity for both honesty and dishonesty? And,
perhaps most important, is dishonesty largely restricted to a few bad apples, or is
it a more widespread problem? I realized that the answer to this last question
might dramatically change how we should try to deal with dishonesty: that is, if
only a few bad apples are responsible for most of the cheating in the world, we
might easily be able to remedy the problem. Human resources departments could
screen for cheaters during the hiring process or they could streamline the
procedure for getting rid of people who prove to be dishonest over time. But if
the problem is not confined to a few outliers, that would mean that anyone could
behave dishonestly at work and at home—you and I included. And if we all have
the potential to be somewhat criminal, it is crucially important that we first
understand how dishonesty operates and then figure out ways to contain and
control this aspect of our nature.
WHAT DO WE know about the causes of dishonesty? In rational economics, the
prevailing notion of cheating comes from the University of Chicago economist
Gary Becker, a Nobel laureate who suggested that people commit crimes based
on a rational analysis of each situation. As Tim Harford describes in his book
The Logic of Life,
*
the birth of this theory was quite mundane. One day, Becker
was running late for a meeting and, thanks to a scarcity of legal parking, decided
to park illegally and risk a ticket. Becker contemplated his own thought process
in this situation and noted that his decision had been entirely a matter of
weighing the conceivable cost—being caught, fined, and possibly towed—
against the benefit of getting to the meeting in time. He also noted that in
weighing the costs versus the benefits, there was no place for consideration of
right or wrong; it was simply about the comparison of possible positive and
negative outcomes.
And thus the Simple Model of Rational Crime (SMORC) was born.
According to this model, we all think and behave pretty much as Becker did.
Like your average mugger, we all seek our own advantage as we make our way
through the world. Whether we do this by robbing banks or writing books is
inconsequential to our rational calculations of costs and benefits. According to
Becker’s logic, if we’re short on cash and happen to drive by a convenience
store, we quickly estimate how much money is in the register, consider the
likelihood that we might get caught, and imagine what punishment might be in
store for us if we are caught (obviously deducting possible time off for good
behavior). On the basis of this cost-benefit calculation, we then decide whether it
is worth it to rob the place or not. The essence of Becker’s theory is that
decisions about honesty, like most other decisions, are based on a cost-benefit
analysis.
The SMORC is a very straightforward model of dishonesty, but the question
is whether it accurately describes people’s behavior in the real world. If it does,
society has two clear means for dealing with dishonesty. The first is to increase
the probability of being caught (through hiring more police officers and
installing more surveillance cameras, for example). The second is to increase the
magnitude of punishment for people who get caught (for example, by imposing
steeper prison sentences and fines). This, my friends, is the SMORC, with its
clear implications for law enforcement, punishment, and dishonesty in general.
But what if the SMORC’s rather simple view of dishonesty is inaccurate or
incomplete? If that is the case, the standard approaches for overcoming
dishonesty are going to be inefficient and insufficient. If the SMORC is an
imperfect model of the causes of dishonesty, then we need to first figure out
what forces really cause people to cheat and then apply this improved
understanding to curb dishonesty. That’s exactly what this book is about.
*
Life in SMORCworld
Before we examine the forces that influence our honesty and dishonesty, let’s
consider a quick thought experiment. What would our lives be like if we all
strictly adhered to the SMORC and considered only the costs and benefits of our
actions?
If we lived in a purely SMORC-based world, we would run a cost-benefit
analysis on all of our decisions and do what seems to be the most rational thing.
We wouldn’t make decisions based on emotions or trust, so we would most
likely lock our wallets in a drawer when we stepped out of our office for a
minute. We would keep our cash under the mattress or lock it away in a hidden
safe. We would be unwilling to ask our neighbors to bring in our mail while
we’re on vacation, fearing that they would steal our belongings. We would
watch our coworkers like hawks. There would be no value in shaking hands as a
form of agreement; legal contracts would be necessary for any transaction,
which would also mean that we would likely spend a substantial part of our time
in legal battles and litigation. We might decide not to have kids because when
they grew up, they, too, would try to steal everything we have, and living in our
homes would give them plenty of opportunities to do so.
Sure, it is easy to see that people are not saints. We are far from perfect. But
if you agree that SMORCworld is not a correct picture of how we think and
behave, nor an accurate description of our daily lives, this thought experiment
suggests that we don’t cheat and steal as much as we would if we were perfectly
rational and acted only in our own self-interest.
Calling All Art Enthusiasts
In April 2011, Ira Glass’s show, This American Life,
1
featured a story about Dan
Weiss, a young college student who worked at the John F. Kennedy Center for
the Performing Arts in Washington, D.C. His job was to stock inventory for the
center’s gift shops, where a sales force of three hundred well-intentioned
volunteers—mostly retirees who loved theater and music—sold the merchandise
to visitors.
The gift shops were run like lemonade stands. There were no cash registers,
just cash boxes into which the volunteers deposited cash and from which they
made change. The gift shops did a roaring business, selling more than $400,000
worth of merchandise a year. But they had one big problem: of that amount,
about $150,000 disappeared each year.
When Dan was promoted to manager, he took on the task of catching the
thief. He began to suspect another young employee whose job it was to take the
cash to the bank. He contacted the U.S. National Park Service’s detective
agency, and a detective helped him set up a sting operation. One February night,
they set the trap. Dan put marked bills into the cash-box and left. Then he and
the detective hid in the nearby bushes, waiting for the suspect. When the
suspected staff member eventually left for the night, they pounced on him and
found some marked bills in his pocket. Case closed, right?
Not so, as it turned out. The young employee stole only $60 that night, and
even after he was fired, money and merchandise still went missing. Dan’s next
step was to set up an inventory system with price lists and sales records. He told
the retirees to write down what was sold and what they received, and—you
guessed it—the thievery stopped. The problem was not a single thief but the
multitude of elderly, well-meaning, art-loving volunteers who would help
themselves to the goods and loose cash lying around.
The moral of this story is anything but uplifting. As Dan put it, “We are
going to take things from each other if we have a chance … many people need
controls around them for them to do the right thing.”
THE PRIMARY PURPOSE of this book is to examine the rational cost-benefit forces
that are presumed to drive dishonest behavior but (as you will see) often do not,
and the irrational forces that we think don’t matter but often do. To wit, when a
large amount of money goes missing, we usually think it’s the work of one
coldhearted criminal. But as we saw in the art lovers’ story, cheating is not
necessarily due to one guy doing a cost-benefit analysis and stealing a lot of
money. Instead, it is more often an outcome of many people who quietly justify
taking a little bit of cash or a little bit of merchandise over and over. In what
follows we will explore the forces that spur us to cheat, and we’ll take a closer
look at what keeps us honest. We will discuss what makes dishonesty rear its
ugly head and how we cheat for our own benefit while maintaining a positive
view of ourselves—a facet of our behavior that enables much of our dishonesty.
Once we explore the basic tendencies that underlie dishonesty, we will turn
to some experiments that will help us discover the psychological and
environmental forces that increase and decrease honesty in our daily lives,
including conflicts of interest, counterfeits, pledges, creativity, and simply being
tired. We’ll explore the social aspects of dishonesty too, including how others
influence our understanding of what’s right and wrong, and our capacity for
cheating when others can benefit from our dishonesty. Ultimately, we will
attempt to understand how dishonesty works, how it depends on the structure of
our daily environment, and under what conditions we are likely to be more and
less dishonest.
In addition to exploring the forces that shape dishonesty, one of the main
practical benefits of the behavioral economics approach is that it shows us the
internal and environmental influences on our behavior. Once we more clearly
understand the forces that really drive us, we discover that we are not helpless in
the face of our human follies (dishonesty included), that we can restructure our
environment, and that by doing so we can achieve better behaviors and
outcomes.
It’s my hope that the research I describe in the following chapters will help
us understand what causes our own dishonest behavior and point to some
interesting ways to curb and limit it.
And now for the journey …
CHAPTER 1
Testing the Simple Model of Rational Crime (SMORC)
Let me come right out and say it. They cheat. You cheat. And yes, I also cheat
from time to time.
As a college professor, I try to mix things up a bit in order to keep my
students interested in the material. To this end, I occasionally invite interesting
guest speakers to class, which is also a nice way to reduce the time I spend on
preparation. Basically, it’s a win-win-win situation for the guest speaker, the
class, and, of course, me.
For one of these “get out of teaching free” lectures, I invited a special guest
to my behavioral economics class. This clever, well-established man has a fine
pedigree: before becoming a legendary business consultant to prominent banks
and CEOs, he had earned his juris doctor and, before that, a bachelor’s at
Princeton. “Over the past few years,” I told the class, “our distinguished guest
has been helping business elites achieve their dreams!”
With that introduction, the guest took the stage. He was forthright from the
get-go. “Today I am going to help you reach your dreams. Your dreams of
MONEY!” he shouted with a thumping, Zumba-trainer voice. “Do you guys
want to make some MONEY?”
Everyone nodded and laughed, appreciating his enthusiastic, non-buttoneddown approach.
“Is anybody here rich?” he asked. “I know I am, but you college students
aren’t. No, you are all poor. But that’s going to change through the power of
CHEATING! Let’s do it!”
He then recited the names of some infamous cheaters, from Genghis Khan
through the present, including a dozen CEOs, Alex Rodriguez, Bernie Madoff,
Martha Stewart, and more. “You all want to be like them,” he exhorted. “You
want to have power and money! And all that can be yours through cheating. Pay
attention, and I will give you the secret!”
With that inspiring introduction, it was now time for a group exercise. He
asked the students to close their eyes and take three deep, cleansing breaths.
“Imagine you have cheated and gotten your first ten million dollars,” he said.
“What will you do with this money? You! In the turquoise shirt!”
“A house,” said the student bashfully.
“A HOUSE? We rich people call that a MANSION. You?” he said, pointing
to another student.
“A vacation.”
“To the private island you own? Perfect! When you make the kind of money
that great cheaters make, it changes your life. Is anyone here a foodie?”
A few students raised their hands.
“What about a meal made personally by Jacques Pépin? A wine tasting at
Châteauneuf-du-Pape? When you make enough money, you can live large
forever. Just ask Donald Trump! Look, we all know that for ten million dollars
you would drive over your boyfriend or girlfriend. I am here to tell you that it is
okay and to release the handbrake for you!”
By that time most of the students were starting to realize that they were not
dealing with a serious role model. But having spent the last ten minutes sharing
dreams about all the exciting things they would do with their first $10 million,
they were torn between the desire to be rich and the recognition that cheating is
morally wrong.
“I can sense your hesitation,” the lecturer said. “You must not let your
emotions dictate your actions. You must confront your fears through a costbenefit analysis. What are the pros of getting rich by cheating?” he asked.
“You get rich!” the students responded.
“That’s right. And what are the cons?”
“You get caught!”
“Ah,” said the lecturer, “There is a CHANCE you will get caught. BUT—
here is the secret! Getting caught cheating is not the same as getting punished for
cheating. Look at Bernie Ebbers, the ex-CEO of WorldCom. His lawyer
whipped out the ‘Aw, shucks’ defense, saying that Ebbers simply did not know
what was going on. Or Jeff Skilling, former CEO of Enron, who famously wrote
an e-mail saying, ‘Shred the documents, they’re onto us.’ Skilling later testified
that he was just being ‘sarcastic’! Now, if these defenses don’t work, you can
always skip town to a country with no extradition laws!”
Slowly but surely, my guest lecturer—who in real life is a stand-up
comedian named Jeff Kreisler and the author of a satirical book called Get Rich
Cheating—was making a hard case for approaching financial decisions on a
purely cost-benefit basis and paying no attention to moral considerations.
Listening to Jeff’s lecture, the students realized that from a perfectly rational
perspective, he was absolutely right. But at the same time they could not help but
feel disturbed and repulsed by his endorsement of cheating as the best path to
success.
At the end of the class, I asked the students to think about the extent to
which their own behavior fit with the SMORC. “How many opportunities to
cheat without getting caught do you have in a regular day?” I asked them. “How
many of these opportunities do you take? How much more cheating would we
see around us if everyone took Jeff’s cost-benefit approach?”
Setting Up the Testing Stage
Both Becker’s and Jeff’s approach to dishonesty are comprised of three basic
elements: (1) the benefit that one stands to gain from the crime; (2) the
probability of getting caught; and (3) the expected punishment if one is caught.
By comparing the first component (the gain) with the last two components (the
costs), the rational human being can determine whether committing a particular
crime is worth it or not.
Now, it could be that the SMORC is an accurate description of the way
people make decisions about honesty and cheating, but the uneasiness
experienced by my students (and myself) with the implications of the SMORC
suggests that it’s worth digging a bit further to figure out what is really going on.
(The next few pages will describe in some detail the way we will measure
cheating throughout this book, so please pay attention.)
My colleagues Nina Mazar (a professor at the University of Toronto) and On
Amir (a professor at the University of California at San Diego) and I decided to
take a closer look at how people cheat. We posted announcements all over the
MIT campus (where I was a professor at the time), offering students a chance to
earn up to $10 for about ten minutes of their time.
* At the appointed time,
participants entered a room where they sat in chairs with small desks attached
(the typical exam-style setup). Next, each participant received a sheet of paper
containing a series of twenty different matrices (structured like the example you
see on the next page) and were told that their task was to find in each of these
matrices two numbers that added up to 10 (we call this the matrix task, and we
will refer to it throughout much of this book). We also told them that they had
five minutes to solve as many of the twenty matrices as possible and that they
would get paid 50 cents per correct answer (an amount that varied depending on
the experiment). Once the experimenter said, “Begin!” the participants turned
the page over and started solving these simple math problems as quickly as they
could.
On the next page is a sample of what the sheet of paper looked like, with one
matrix enlarged. How quickly can you find the pair of numbers that adds up to
10?
This was how the experiment started for all the participants, but what
happened at the end of the five minutes was different depending on the particular
condition.
Imagine that you are in the control condition and you are hurrying to solve
as many of the twenty matrices as possible. After a minute passes, you’ve solved
one. Two more minutes pass, and you’re up to three. Then time is up, and you
have four completed matrices. You’ve earned $2. You walk up to the
experimenter’s desk and hand her your solutions. After checking your answers,
the experimenter smiles approvingly. “Four solved,” she says and then counts
out your earnings. “That’s it,” she says, and you’re on your way. (The scores in
this control condition gave us the actual level of performance on this task.)
Now imagine you are in another setup, called the shredder condition, in
which you have the opportunity to cheat. This condition is similar to the control
condition, except that after the five minutes are up the experimenter tells you,
“Now that you’ve finished, count the number of correct answers, put your
worksheet through the shredder at the back of the room, and then come to the
front of the room and tell me how many matrices you solved correctly.” If you
were in this condition you would dutifully count your answers, shred your
worksheet, report your performance, get paid, and be on your way.
If you were a participant in the shredder condition, what would you do?
Would you cheat? And if so, by how much?
With the results for both of these conditions, we could compare the
performance in the control condition, in which cheating was impossible, to the
reported performance in the shredder condition, in which cheating was possible.
If the scores were the same, we would conclude that no cheating had occurred.
But if we saw that, statistically speaking, people performed “better” in the
shredder condition, then we could conclude that our participants overreported
their performance (cheated) when they had the opportunity to shred the
evidence. And the degree of this group’s cheating would be the difference in the
number of matrices they claimed to have solved correctly above and beyond the
number of matrices participants actually solved correctly in the control
condition.
Perhaps somewhat unsurprisingly, we found that given the opportunity,
many people did fudge their score. In the control condition, participants solved
on average four out of the twenty matrices. Participants in the shredder condition
claimed to have solved an average of six—two more than in the control
condition. And this overall increase did not result from a few individuals who
claimed to solve a lot more matrices, but from lots of people who cheated by just
a little bit.
More Money, More Cheating?
With this basic quantification of dishonesty under our belts, Nina, On, and I
were ready to investigate what forces motivate people to cheat more and less.
The SMORC tells us that people should cheat more when they stand a chance of
getting more money without being caught or punished. That sounds both simple
and intuitively appealing, so we decided to test it next. We set up another version
of the matrix experiment, only this time we varied the amount of money the
participants would get for solving each matrix correctly. Some participants were
promised 25 cents per question; others were promised 50 cents, $1, $2, or $5. At
the highest level, we promised some participants a whopping $10 for each
correct answer. What do you think happened? Did the amount of cheating
increase with the amount of money offered?
Before I divulge the answer, I want to tell you about a related experiment.
This time, rather than taking the matrix test themselves, we asked another group
of participants to guess how many answers those in the shredder condition would
claim to solve correctly at each level of payment. Their predictions were that the
claims of correctly solved matrices would increase as the amount of money went
up. Essentially, their intuitive theory was the same as the premise of the
SMORC. But they were wrong. It turned out that when we looked at the
magnitude of cheating, our participants added two questions to their scores on
average, regardless of the amount of money they could make per question. In
fact, the amount of cheating was slightly lower when we promised our
participants the highest amount of $10 for each correct answer.
Why wouldn’t the level of cheating increase with the amount of money
offered? Why was cheating slightly lower at the highest level of payment? This
insensitivity to the amount of reward suggests that dishonesty is most likely not
an outcome of a cost-benefit analysis. If it were, the increase in the benefit (the
amount of money offered) would lead to more cheating. And why was the level
of cheating lowest when the payment was greatest? I suspect that when the
amount of money that the participants could make per question was $10, it was
harder for them to cheat and still feel good about their own sense of integrity (we
will come back to this later). At $10 per matrix, we’re not talking about cheating
on the level of, say, taking a pencil from the office. It’s more akin to taking
several boxes of pens, a stapler, and a ream of printer paper, which is much more
difficult to ignore or rationalize.
To Catch a Thief
Our next experiment looked at what might happen if participants felt that there
was a higher probability of getting caught cheating. Basically, we inserted the
mental equivalent of a partially operating security camera into the experiment.
We asked one group of participants to shred one half of their worksheet—
which meant that if they were dishonest, we might find some evidence of it. We
asked a second group to shred the whole work sheet, meaning that they could get
off scot-free. Finally, we asked a third group to shred the whole worksheet, leave
the testing room, and pay themselves from a sizable bowl of money filled with
more than $100 in small bills and coins. In this self-paying condition,
participants could not only cheat and get away with it, but they could also help
themselves to a lot of extra cash.
Again, we asked a different group to predict how many questions, on
average, participants would claim to solve correctly in each condition. Once
again, they predicted that the human tendency for dishonesty would follow the
SMORC and that participants would claim to solve more matrices as the
probability of getting caught decreased.
What did we find? Once again, lots of people cheated, but just by a bit, and
the level of cheating was the same across all three conditions (shredding half,
shredding all, shredding all and self-paying).
NOW, YOU MIGHT wonder if the participants in our experiments really believed
that in our experimental setting, they could cheat and not get caught. To make it
clear that this was indeed the case, Racheli Barkan (a professor at Ben-Gurion
University of the Negev), Eynav Maharabani (a master’s candidate working with
Racheli), and I carried out another study where either Eynav or a different
research assistant, Tali, proctored the experiment. Eynav and Tali were similar in
many ways—but Eynav is noticeably blind, which meant that it was easier to
cheat when she was in charge. When it was time to pay themselves from the pile
of money that was placed on the table in front of the experimenter, participants
could grab as much of the cash as they wanted and Eynav would not be able to
see them do so.
So did they cheat Eynav to a greater degree? They still took a bit more
money than they deserved, but they cheated just as much when Tali supervised
the experiments as they did when Eynav was in charge.
These results suggest that the probability of getting caught doesn’t have a
substantial influence on the amount of cheating. Of course, I am not arguing that
people are entirely uninfluenced by the likelihood of being caught—after all, no
one is going to steal a car when a policeman is standing nearby—but the results
show that getting caught does not have as great an influence as we tend to
expect, and it certainly did not play a role in our experiments.
YOU MIGHT BE wondering whether the participants in our experiments were using
the following logic: “If I cheat by only a few questions, no one will suspect me.
But if I cheat by more than a small amount, it may raise suspicion and someone
might question me about it.”
We tested this idea in our next experiment. This time, we told half of the
participants that the average student in this experiment solves about four
matrices (which was true). We told the other half that the average student solves
about eight matrices. Why did we do this? Because if the level of cheating is
based on the desire to avoid standing out, then our participants would cheat in
both conditions by a few matrices beyond what they believed was the average
performance (meaning that they would claim to solve around six matrices when
they thought the average was four and about ten matrices when they thought the
average was eight).
So how did our participants behave when they expected others to solve more
matrices? They were not influenced even to a small degree by this knowledge.
They cheated by about two extra answers (they solved four and reported that
they had solved six) regardless of whether they thought that others solved on
average four or eight matrices.
This result suggests that cheating is not driven by concerns about standing
out. Rather, it shows that our sense of our own morality is connected to the
amount of cheating we feel comfortable with. Essentially, we cheat up to the
level that allows us to retain our self-image as reasonably honest individuals.
Into the Wild
Armed with this initial evidence against the SMORC, Racheli and I decided to
get out of the lab and venture into a more natural setting. We wanted to examine
common situations that one might encounter on any given day. And we wanted
to test “real people” and not just students (though I have discovered that students
don’t like to be told that they are not real people). Another component missing
from our experimental paradigm up to that point was the opportunity for people
to behave in positive and benevolent ways. In our lab experiments, the best our
participants could do was not cheat. But in many real-life situations, people can
exhibit behaviors that are not only neutral but are also charitable and generous.
With this added nuance in mind, we looked for situations that would let us test
both the negative and the positive sides of human nature.
IMAGINE A LARGE farmer’s market spanning the length of a street. The market is
located in the heart of Be’er Sheva, a town in southern Israel. It’s a hot day, and
hundreds of merchants have set out their wares in front of the stores that line
both sides of the street. You can smell fresh herbs and sour pickles, freshly
baked bread and ripe strawberries, and your eyes wander over plates of olives
and cheese. The sound of merchants shouting praises of their goods surrounds
you: “Rak ha yom!” (only today), “Matok!” (sweet), “Bezol!” (cheap).
Eynav and Tali entered the market and headed in different directions, Eynav
using a white cane to navigate the market. Each of them approached a few
vegetable vendors and asked each of the sellers to pick out two kilos (about 4.5
pounds) of tomatoes for them while they went on another errand. Once they
made their request, they left for about ten minutes, returned to pick up their
tomatoes, paid, and left. From there they took the tomatoes to another vendor at
the far end of the market who had agreed to judge the quality of the tomatoes
from each seller. By comparing the quality of the tomatoes that were sold to
Eynav and to Tali, we could figure out who got better produce and who got
worse.
Did Eynav get a raw deal? Keep in mind that from a purely rational
perspective, it would have made sense for the seller to choose his worst-looking
tomatoes for her. After all, she could not possibly benefit from their aesthetic
quality. A traditional economist from, say, the University of Chicago might even
argue that in an effort to maximize the social welfare of everyone involved (the
seller, Eynav, and the other consumers), the seller should have sold her the
worst-looking tomatoes, keeping the pretty ones for people who could also enjoy
that aspect of the tomatoes. As it turned out, the visual quality of the tomatoes
chosen for Eynav was not worse and, in fact, was superior to those chosen for
Tali. The sellers went out of their way, and at some cost to their business, to
choose higher-quality produce for a blind customer.
WITH THOSE OPTIMISTIC results, we next turned to another profession that is
often regarded with great suspicion: cab drivers. In the taxi world, there is a
popular stunt called “long hauling,” which is the official term for taking
passengers who don’t know their way around to their destination via a lengthy
detour, sometimes adding substantially to the fare. For example, a study of cab
drivers in Las Vegas found that some cabbies drive from McCarran International
Airport to the Strip by going through a tunnel to Interstate 215, which can mount
to a fare of $92 for what should be a two-mile journey.
1
Given the reputation that cabbies have, one has to wonder whether they
cheat in general and whether they would be more likely to cheat those who
cannot detect their cheating. In our next experiment we asked Eynav and Tali to
take a cab back and forth between the train station and Ben-Gurion University of
the Negev twenty times. The way the cabs on this particular route work is as
follows: if you have the driver activate the meter, the fare is around 25 NIS
(about $7). However, there is a customary flat rate of 20 NIS (about $5.50) if the
meter is not activated. In our setup, both Eynav and Tali always asked to have
the meter activated. Sometimes drivers would tell the “amateur” passengers that
it would be cheaper not to activate the meter; regardless, both of them always
insisted on having the meter activated. At the end of the ride, Eynav and Tali
asked the cab driver how much they owed them, paid, left the cab, and waited a
few minutes before taking another cab back to the place they had just left.
Looking at the charges, we found that Eynav paid less than Tali, despite the
fact that they both insisted on paying by the meter. How could this be? One
possibility was that the drivers had taken Eynav on the shortest and cheapest
route and had taken Tali for a longer ride. If that were the case, it would mean
that the drivers had not cheated Eynav but that they had cheated Tali to some
degree. But Eynav had a different account of the results. “I heard the cab drivers
activate the meter when I asked them to,” she told us, “but later, before we
reached our final destination, I heard many of them turn the meter off so that the
fare would come out close to twenty NIS.” “That certainly never happened to
me,” Tali said. “They never turned off the meter, and I always ended up paying
around twenty-five NIS.”
There are two important aspects to these results. First, it’s clear that the cab
drivers did not perform a cost-benefit analysis in order to optimize their
earnings. If they had, they would have cheated Eynav more by telling her that
the meter reading was higher than it really was or by driving her around the city
for a bit. Second, the cab drivers did better than simply not cheat; they took
Eynav’s interest into account and sacrificed some of their own income for her
benefit.
Making Fudge
Clearly there’s a lot more going on here than Becker and standard economics
would have us believe. For starters, the finding that the level of dishonesty is not
influenced to a large degree (to any degree in our experiments) by the amount of
money we stand to gain from being dishonest suggests that dishonesty is not an
outcome of simply considering the costs and benefits of dishonesty. Moreover,
the results showing that the level of dishonesty is unaltered by changes in the
probability of being caught makes it even less likely that dishonesty is rooted in
a cost-benefit analysis. Finally, the fact that many people cheat just a little when
given the opportunity to do so suggests that the forces that govern dishonesty are
much more complex (and more interesting) than predicted by the SMORC.
What is going on here? I’d like to propose a theory that we will spend much
of this book examining. In a nutshell, the central thesis is that our behavior is
driven by two opposing motivations. On one hand, we want to view ourselves as
honest, honorable people. We want to be able to look at ourselves in the mirror
and feel good about ourselves (psychologists call this ego motivation). On the
other hand, we want to benefit from cheating and get as much money as possible
(this is the standard financial motivation). Clearly these two motivations are in
conflict. How can we secure the benefits of cheating and at the same time still
view ourselves as honest, wonderful people?
This is where our amazing cognitive flexibility comes into play. Thanks to
this human skill, as long as we cheat by only a little bit, we can benefit from
cheating and still view ourselves as marvelous human beings. This balancing act
is the process of rationalization, and it is the basis of what we’ll call the “fudge
factor theory.”
To give you a better understanding of the fudge factor theory, think of the
last time you calculated your tax return. How did you make peace with the
ambiguous and unclear decisions you had to make? Would it be legitimate to
write off a portion of your car repair as a business expense? If so, what amount
would you feel comfortable with? And what if you had a second car? I’m not
talking about justifying our decisions to the Internal Revenue Service (IRS); I’m
talking about the way we are able to justify our exaggerated level of tax
deductions to ourselves.
Or let’s say you go out to a restaurant with friends and they ask you to
explain a work project you’ve been spending a lot of time on lately. Having done
that, is the dinner now an acceptable business expense? Probably not. But what
if the meal occurred during a business trip or if you were hoping that one of your
dinner companions would become a client in the near future? If you have ever
made allowances of this sort, you too have been playing with the flexible
boundaries of your ethics. In short, I believe that all of us continuously try to
identify the line where we can benefit from dishonesty without damaging our
own self-image. As Oscar Wilde once wrote, “Morality, like art, means drawing
a line somewhere.” The question is: where is the line?
I THINK JEROME K. JEROME got it right in his 1889 novel, Three Men in a Boat (to
Say Nothing of the Dog), in which he tells a story about one of the most
famously lied-about topics on earth: fishing. Here’s what he wrote:
I knew a young man once, he was a most conscientious fellow and, when he
took to fly-fishing, he determined never to exaggerate his hauls by more
than twenty-five per cent.
“When I have caught forty fish,” said he, “then I will tell people that I
have caught fifty, and so on. But I will not lie any more than that, because it
is sinful to lie.”
Although most people haven’t consciously figured out (much less
announced) their acceptable rate of lying like this young man, this overall
approach seems to be quite accurate; each of us has a limit to how much we can
cheat before it becomes absolutely “sinful.”
Trying to figure out the inner workings of the fudge factor—the delicate
balance between the contradictory desires to maintain a positive self-image and
to benefit from cheating—is what we are going to turn our attention to next.
CHAPTER 2
Fun with the Fudge Factor
Here’s a little joke for you:
Eight-year-old Jimmy comes home from school with a note from his teacher
that says, “Jimmy stole a pencil from the student sitting next to him.” Jimmy’s
father is furious. He goes to great lengths to lecture Jimmy and let him know
how upset and disappointed he is, and he grounds the boy for two weeks. “And
just wait until your mother comes home!” he tells the boy ominously. Finally he
concludes, “Anyway, Jimmy, if you needed a pencil, why didn’t you just say
something? Why didn’t you simply ask? You know very well that I can bring
you dozens of pencils from work.”
If we smirk at this joke, it’s because we recognize the complexity of human
dishonesty that is inherent to all of us. We realize that a boy stealing a pencil
from a classmate is definitely grounds for punishment, but we are willing to take
many pencils from work without a second thought.
To Nina, On, and me, this little joke suggested the possibility that certain
types of activities can more easily loosen our moral standards. Perhaps, we
thought, if we increased the psychological distance between a dishonest act and
its consequences, the fudge factor would increase and our participants would
cheat more. Of course, encouraging people to cheat more is not something we
want to promote in general. But for the purpose of studying and understanding
cheating, we wanted to see what kinds of situations and interventions might
further loosen people’s moral standards.
To test this idea, we first tried a university version of the pencil joke: One
day, I sneaked into an MIT dorm and seeded many communal refrigerators with
one of two tempting baits. In half of the refrigerators, I placed six-packs of
Coca-Cola; in the others, I slipped in a paper plate with six $1 bills on it. I went
back from time to time to visit the refrigerators and see how my Cokes and
money were doing—measuring what, in scientific terms, we call the half-life of
Coke and money.
As anyone who has been to a dorm can probably guess, within seventy-two
hours all the Cokes were gone, but what was particularly interesting was that no
one touched the bills. Now, the students could have taken a dollar bill, walked
over to the nearby vending machine and gotten a Coke and change, but no one
did.
I must admit that this is not a great scientific experiment, since students
often see cans of Coke in their fridge, whereas discovering a plate with a few
dollar bills on it is rather unusual. But this little experiment suggests that we
human beings are ready and willing to steal something that does not explicitly
reference monetary value—that is, something that lacks the face of a dead
president. However, we shy away from directly stealing money to an extent that
would make even the most pious Sunday school teacher proud. Similarly, we
might take some paper from work to use in our home printer, but it would be
highly unlikely that we would ever take $3.50 from the petty-cash box, even if
we turned right around and used the money to buy paper for our home printer.
To look at the distance between money and its influence on dishonesty in a
more controlled way, we set up another version of the matrix experiment, this
time including a condition where cheating was one step removed from money.
As in our previous experiments, participants in the shredder condition had the
opportunity to cheat by shredding their worksheets and lying about the number
of matrices they’d solved correctly. When the participants finished the task, they
shredded their worksheet, approached the experimenter, and said, “I solved X
*
matrices, please give me X dollars.”
The innovation in this experiment was the “token” condition. The token
condition was similar to the shredder condition, except that the participants were
paid in plastic chips instead of dollars. In the token condition, once participants
finished shredding their worksheets, they approached the experimenter and said,
“I solved X matrices, please give me X tokens.” Once they received their chips,
they walked twelve feet to a nearby table, where they handed in their tokens and
received cold, hard cash.
As it turned out, those who lied for tokens that a few seconds later became
money cheated by about twice as much as those who were lying directly for
money. I have to confess that, although I had suspected that participants in the
token condition would cheat more, I was surprised by the increase in cheating
that came with being one small step removed from money. As it turns out,
people are more apt to be dishonest in the presence of nonmonetary objects—
such as pencils and tokens—than actual money.
From all the research I have done over the years, the idea that worries me the
most is that the more cashless our society becomes, the more our moral compass
slips. If being just one step removed from money can increase cheating to such a
degree, just imagine what can happen as we become an increasingly cashless
society. Could it be that stealing a credit card number is much less difficult from
a moral perspective than stealing cash from someone’s wallet? Of course, digital
money (such as a debit or credit card) has many advantages, but it might also
separate us from the reality of our actions to some degree. If being one step
removed from money liberates people from their moral shackles, what will
happen as more and more banking is done online? What will happen to our
personal and social morality as financial products become more obscure and less
recognizably related to money (think, for example, about stock options,
derivatives, and credit default swaps)?
Some Companies Already Know This!
As scientists, we took great care to carefully document, measure, and examine
the influence of being one step removed from money. But I suspect that some
companies intuitively understand this principle and use it to their advantage.
Consider, for example, this letter that I received from a young consultant:
Dear Dr. Ariely,
I graduated a few years ago with a BA degree in Economics from a
prestigious college and have been working at an economic consulting firm,
which provides services to law firms.
The reason I decided to contact you is that I have been observing and
participating in a very well documented phenomenon of overstating billable
hours by economic consultants. To avoid sugar coating it, let’s call it
cheating. From the most senior people all the way to the lowest analyst, the
incentive structure for consultants encourages cheating: no one checks to
see how much we bill for a given task; there are no clear guidelines as to
what is acceptable; and if we have the lowest billability among fellow
analysts, we are the most likely to get axed. These factors create the perfect
environment for rampant cheating.
The lawyers themselves get a hefty cut of every hour we bill, so they
don’t mind if we take longer to finish a project. While lawyers do have
some incentive to keep costs down to avoid enraging clients, many of the
analyses we perform are very difficult to evaluate. Lawyers know this and
seem to use it to their advantage. In effect, we are cheating on their behalf;
we get to keep our jobs and they get to keep an additional profit.
Here are some specific examples of how cheating is carried out in my
company:
• A deadline was fast approaching and we were working extremely long
hours. Budget didn’t seem to be an issue and when I asked how much of my
day I should bill, my boss (a midlevel project manager) told me to take the
total amount of time I was in the office and subtract two hours, one for
lunch and one for dinner. I said that I had taken a number of other breaks
while the server was running my programs and she said I could count that
as a mental health break that would promote higher productivity later.
• A good friend of mine in the office adamantly refused to overbill and
consequently had an overall billing rate that was about 20 percent lower
than the average. I admire his honesty, but when it was time to lay people
off, he was the first to go. What kind of message does that send to the rest of
us?
• One person bills every hour he is monitoring his email for a project,
whether or not he receives any work to do. He is “on-call,” he says.
• Another guy often works from home and seems to bill a lot, but when he is
in the office he never seems to have any work to do.
These kinds of examples go on and on. There is no doubt that I am
complicit in this behavior, but seeing it more clearly makes me want to fix
the problems. Do you have any advice? What would you do in my situation?
Sincerely yours,
Jonah
Unfortunately, the problems Jonah noted are commonplace, and they are a
direct outcome of the way we think about our own morality. Here is another way
to think about this issue: One morning I discovered that someone had broken the
window of my car and stolen my portable GPS system. Certainly, I was very
annoyed, but in terms of its economic impact on my financial future, this crime
had a very small effect. On the other hand, think about how much my lawyers,
stockbrokers, mutual fund managers, insurance agents, and others probably take
from me (and all of us) over the years by slightly overcharging, adding hidden
fees, and so on. Each of these actions by itself is probably not very financially
significant, but together they add up to much more than a few navigation
devices. At the same time, I suspect that unlike the person who took my GPS,
those white-collar transgressors think of themselves as highly moral people
because their actions are relatively small and, most important, several steps
removed from my pocket.
The good news is that once we understand how our dishonesty increases
when we are one or more steps removed from money, we can try to clarify and
emphasize the links between our actions and the people they can affect. At the
same time, we can try to shorten the distance between our actions and the money
in question. By taking such steps, we can become more cognizant of the
consequences of our actions and, with that awareness, increase our honesty.
LESSONS FROM LOCKSMITHS
Not too long ago, one of my students named Peter told me a story that
captures our misguided efforts to decrease dishonesty rather nicely.
One day, Peter locked himself out of his house, so he called around
to find a locksmith. It took him a while to find one who was certified by
the city to unlock doors. The locksmith finally pulled up in his truck
and picked the lock in about a minute.
“I was amazed at how quickly and easily this guy was able to open
the door,” Peter told me. Then he passed on a little lesson in morality
he learned from the locksmith that day.
In response to Peter’s amazement, the locksmith told Peter that
locks are on doors only to keep honest people honest. “One percent of
people will always be honest and never steal,” the locksmith said.
“Another one percent will always be dishonest and always try to pick
your lock and steal your television. And the rest will be honest as long
as the conditions are right—but if they are tempted enough, they’ll be
dishonest too. Locks won’t protect you from the thieves, who can get in
your house if they really want to. They will only protect you from the
mostly honest people who might be tempted to try your door if it had
no lock.”
After reflecting on these observations, I came away thinking that
the locksmith was probably right. It’s not that 98 percent of people are
immoral or will cheat anytime the opportunity arises; it’s more likely
that most of us need little reminders to keep ourselves on the right
path.
How to Get People to Cheat Less
Now that we had figured out how the fudge factor works and how to expand it,
as our next step we wanted to figure out whether we could decrease the fudge
factor and get people to cheat less. This idea, too, was spawned by a little joke:
A visibly upset man goes to see his rabbi one day and says, “Rabbi, you
won’t believe what happened to me! Last week, someone stole my bicycle from
synagogue!”
The rabbi is deeply upset by this, but after thinking for a moment, he offers a
solution: “Next week come to services, sit in the front row, and when we recite
the Ten Commandments, turn around and look at the people behind you. And
when we get to ‘Thou shalt not steal,’ see who can’t look you in the eyes and
that’s your guy.” The rabbi is very pleased with his suggestion, and so is the
man.
At the next service, the rabbi is very curious to learn whether his advice
panned out. He waits for the man by the doors of the synagogue, and asks him,
“So, did it work?”
“Like a charm,” the man answers. “The moment we got to ‘Thou shalt not
commit adultery,’ I remembered where I left my bike.”
What this little joke suggests is that our memory and awareness of moral
codes (such as the Ten Commandments) might have an effect on how we view
our own behavior.
Inspired by the lesson behind this joke, Nina, On, and I ran an experiment at
the University of California, Los Angeles (UCLA). We took a group of 450
participants and split them into two groups. We asked half of them to try to
recall the Ten Commandments and then tempted them to cheat on our matrix
task. We asked the other half to try to recall ten books they had read in high
school before setting them loose on the matrices and the opportunity to cheat.
Among the group who recalled the ten books, we saw the typical widespread but
moderate cheating. On the other hand, in the group that was asked to recall the
Ten Commandments, we observed no cheating whatsoever. And that was despite
the fact that no one in the group was able to recall all ten.
This result was very intriguing. It seemed that merely trying to recall moral
standards was enough to improve moral behavior. In another attempt to test this
effect, we asked a group of self-declared atheists to swear on a Bible and then
gave them the opportunity to claim extra earnings on the matrix task. What did
the atheists do? They did not stray from the straight-and-narrow path.
These experiments with moral reminders suggest that our willingness and
tendency to cheat could be diminished if we are given reminders of ethical
standards. But although using the Ten Commandments and the Bible as honestybuilding mechanisms might be helpful, introducing religious tenets into society
on a broader basis as a means to reduce cheating is not very practical (not to
mention the fact that doing so would violate the separation of church and state).
So we began to think of more general, practical, and secular ways to shrink the
fudge factor, which led us to test the honor codes that many universities already
use.
To discover whether honor codes work, we asked a group of MIT and Yale
students to sign such a code just before giving half of them a chance to cheat on
the matrix tasks. The statement read, “I understand that this experiment falls
under the guidelines of the MIT/Yale honor code.” The students who were not
asked to sign cheated a little bit, but the MIT and Yale students who signed this
statement did not cheat at all. And that was despite the fact that neither
university has an honor code (somewhat like the effect that swearing on the
Bible had on the self-declared atheists).
STEALING PAPER
A few years ago I received a letter from a woman named Rhonda who
attended the University of California at Berkeley. She told me about a
problem she’d had in her house and how a little ethical reminder
helped her solve it.
She was living near campus with several other people—none of
whom knew one another. When the cleaning people came each
weekend, they left several rolls of toilet paper in each of the two
bathrooms. However, by Monday all the toilet paper would be gone. It
was a classic tragedy-of-the-commons situation: because some people
hoarded the toilet paper and took more than their fair share, the public
resource was destroyed for everyone else.
After reading about the Ten Commandments experiment on my
blog, Rhonda put a note in one of the bathrooms asking people not to
remove toilet paper, as it was a shared commodity. To her great
satisfaction, one roll reappeared in a few hours, and another the next
day. In the other note-free bathroom, however, there was no toilet
paper until the following weekend, when the cleaning people returned.
This little experiment demonstrates how effective small reminders
can be in helping us maintain our ethical standards and, in this case, a
fully stocked bathroom.
We found that an honor code worked in universities that don’t have an honor
code, but what about universities that have a strong honor code? Would their
students cheat less all the time? Or would they cheat less only when they signed
the honor code? Luckily, at the time I was spending some time at the Institute for
Advanced Study at Princeton University, which was a great petri dish in which
to test this idea.
Princeton University has a rigorous honor system that’s been around since
1893. Incoming freshmen receive a copy of the Honor Code Constitution and a
letter from the Honor Committee about the honor system, which they must sign
before they can matriculate. They also attend mandatory talks about the
importance of the Honor Code during their first week of school. Following the
lectures, the incoming Princetonians further discuss the system with their dorm
advising group. As if that weren’t enough, one of the campus music groups, the
Triangle Club, performs its “Honor Code Song” for the incoming class.
For the rest of their time at Princeton, students are repeatedly reminded of
the honor code: they sign an honor code at the end of every paper they submit
(“This paper represents my own work in accordance with University
regulations”). They sign another pledge for every exam, test, or quiz (“I pledge
my honor that I have not violated the honor code during this examination”), and
they receive biannual reminder e-mails from the Honor Committee.
To see if Princeton’s crash course on morality has a long-term effect, I
waited two weeks after the freshmen finished their ethics training before
tempting them to cheat—giving them the same opportunities as the students at
MIT and Yale (which have neither an honor code nor a weeklong course on
academic honesty). Were the Princeton students, still relatively fresh from their
immersion in the honor code, more honest when they completed the matrix task?
Sadly, they were not. When the Princeton students were asked to sign the
honor code, they did not cheat at all (but neither did the MIT or Yale students).
However, when they were not asked to sign the honor code, they cheated just as
much as their counterparts at MIT and Yale. It seems that the crash course, the
propaganda on morality, and the existence of an honor code did not have a
lasting influence on the moral fiber of the Princetonians.
These results are both depressing and promising. On the depressing side, it
seems that it is very difficult to alter our behavior so that we become more
ethical and that a crash course on morality will not suffice. (I suspect that this
ineffectiveness also applies to much of the ethics training that takes place in
businesses, universities, and business schools.) More generally, the results
suggest that it’s quite a challenge to create a long-term cultural change when it
comes to ethics.
On the positive side, it seems that when we are simply reminded of ethical
standards, we behave more honorably. Even better, we discovered that the “sign
here” honor code method works both when there is a clear and substantial cost
for dishonesty (which, in the case of Princeton, can entail expulsion) and when
there is no specific cost (as at MIT and Yale). The good news is that people
seem to want to be honest, which suggests that it might be wise to incorporate
moral reminders into situations that tempt us to be dishonest.
*
ONE PROFESSOR AT Middle Tennessee State University got so fed up with the
cheating among his MBA students that he decided to employ a more drastic
honor code. Inspired by our Ten Commandments experiment and its effect on
honesty, Thomas Tang asked his students to sign an honor code stating that they
would not cheat on an exam. The pledge also stated that they “would be sorry for
the rest of their lives and go to Hell” if they cheated.
The students, who did not necessarily believe in Hell or agree that they were
going there, were outraged. The pledge became very controversial, and, perhaps
unsurprisingly, Tang caught a lot of heat for his effort (he eventually had to
revert to the old, Hell-free pledge).
Still, I imagine that in its short existence, this extreme version of the honor
code had quite an effect on the students. I also think the students’ outrage
indicates how effective this type of pledge can be. The future businessmen and
women must have felt that the stakes were very high, or they would not have
cared so much. Imagine yourself confronted by such a pledge. How comfortable
would you feel signing it? Would signing it influence your behavior? What if
you had to sign it just before filling out your expense reports?
RELIGIOUS REMINDERS
The possibility of using religious symbols as a way to increase honesty
has not escaped religious scholars. There is a story in the Talmud about
a religious man who becomes desperate for sex and goes to a prostitute.
His religion wouldn’t condone this, of course, but at the time he feels
that he has more pressing needs. Once alone with the prostitute, he
begins to undress. As he takes off his shirt, he sees his tzitzit, an
undergarment with four pieces of knotted fringe. Seeing the tzitzit
reminds him of the mitzvoth (religious obligations), and he quickly
turns around and leaves the room without violating his religious
standards.
Adventures with the IRS
Using honor codes to curb cheating at a university is one thing, but would moral
reminders of this type also work for other types of cheating and in nonacademic
environments? Could they help prevent cheating on, say, tax-reporting and
insurance claims? That is what Lisa Shu (a PhD student at Harvard University),
Nina Mazar, Francesca Gino (a professor at Harvard University), Max Bazerman
(a professor at Harvard University), and I set out to test.
We started by restructuring our standard matrix experiment to look a bit like
tax reporting. After they finished solving and shredding the matrix task, we
asked participants to write down the number of questions that they had solved
correctly on a form we modeled after the basic IRS 1040EZ tax form. To make it
feel even more as if they were working with a real tax form, it was stated clearly
on the form that their income would be taxed at a rate of 20 percent. In the first
section of the form, the participants were asked to report their “income” (the
number of matrices they had solved correctly). Next, the form included a section
for travel expenses, where participants could be reimbursed at a rate of 10 cents
per minute of travel time (up to two hours, or $12) and for the direct cost of their
transportation (up to another $12). This part of the payment was tax exempt (like
a business expense). The participants were then asked to add up all the numbers
and come up with their final net payment.
There were two conditions in this experiment: Some of the participants filled
out the entire form and then signed it at the bottom, as is typically done with
official forms. In this condition, the signature acted as verification of the
information on the form. In the second condition, participants signed the form
first and only then filled it out. That was our “moral reminder” condition.
What did we find? The participants in the sign-at-the-end condition cheated
by adding about four extra matrices to their score. And what about those who
signed at the top? When the signature acted as a moral reminder, participants
claimed only one extra matrix. I am not sure how you feel about “only” one
added matrix—after all, it is still cheating—but given that the one difference
between these two conditions was the location of the signature line, I see this
outcome as a promising way to reduce dishonesty.
Our version of the tax form also allowed us to look at the requests for travel
reimbursements. Now, we did not know how much time the participants really
spent traveling, but if we assumed that due to randomization, the average amount
of travel time was basically the same in both conditions, we could see in which
condition participants claimed higher travel expenses. What we saw was that the
amount of requests for travel reimbursement followed the same pattern: Those in
the signature-at-the-bottom condition claimed travel expenses averaging $9.62,
while those in the moral reminder (signature-at-the-top) condition claimed that
they had travel expenses averaging $5.27.
ARMED WITH OUR evidence that when people sign their names to some kind of
pledge, it puts them into a more honest disposition (at least temporarily), we
approached the IRS, thinking that Uncle Sam would be glad to hear of ways to
boost tax revenues. The interaction with the IRS went something like this:
ME: By the time taxpayers finish entering all the data onto the form, it is too
late. The cheating is done and over with, and no one will say, “Oh, I
need to sign this thing, let me go back and give honest answers.” You
see? If people sign before they enter any data onto the form, they cheat
less. What you need is a signature at the top of the form, and this will
remind everyone that they are supposed to be telling the truth.
IRS: Yes, that’s interesting. But it would be illegal to ask people to sign at
the top of the form. The signature needs to verify the accuracy of the
information provided.
ME: How about asking people to sign twice? Once at the top and once at the
bottom? That way, the top signature will act as a pledge—reminding
people of their patriotism, moral fiber, mother, the flag, homemade
apple pie—and the signature at the bottom would be for verification.
IRS: Well, that would be confusing.
ME: Have you looked at the tax code or the tax forms recently?
IRS: [No reaction.]
ME: How about this? What if the first item on the tax form asked if the
taxpayer would like to donate twenty-five dollars to a task force to fight
corruption? Regardless of the particular answer, the question will force
people to contemplate their standing on honesty and its importance for
society! And if the taxpayer donates money to this task force, they not
only state an opinion, but they also put some money behind their
decision, and now they might be even more likely to follow their own
example.
IRS: [Stony silence.]
ME: This approach may have another interesting benefit: You could flag the
taxpayers who decide not to donate to the task force and audit them!
IRS: Do you really want to talk about audits?
*
Despite the reaction from the IRS, we were not entirely discouraged, and
continued to look for other opportunities to test our “sign first” idea. We were
finally (moderately) successful when we approached a large insurance company.
The company confirmed our already substantiated theory that most people cheat,
but only by a little bit. They told us that they suspect that very few people cheat
flagrantly (committing arson, faking a robbery, and so on) but that many people
who undergo a loss of property seem comfortable exaggerating their loss by 10
to 15 percent. A 32-inch television becomes 40 inches, an 18k necklace becomes
22k, and so on.
I went to their headquarters and got to spend the day with the top folks at
this company, trying to come up with ways to decrease dishonest reporting on
insurance claims. We came up with lots of ideas. For instance, what if people
had to declare their losses in highly concrete terms and provide more specific
details (where and when they bought the items) in order to allow less moral
flexibility? Or if a couple lost their house in a flood, what if they had to agree on
what was lost (although as we will see in chapter 8, “Cheating as an Infection,”
and chapter 9, “Collaborative Cheating,” this particular idea might backfire).
What if we played religious music when people were on hold? And of course,
what if people had to sign at the top of the claim form or even next to each
reported item?
As is the way with such large companies, the people I met with took the
ideas to their lawyers. We waited six months and then finally heard from the
lawyers—who said that they were not willing to let us try any of these
approaches.
A few days later, my contact person at the insurance company called me and
apologized for not being able to try any of our ideas. He also told me that there
was one relatively unimportant automobile insurance form that we could use for
an experiment. The form asked people to record their current odometer reading
so that the insurance company could calculate how many miles they had driven
the previous year. Naturally, people who want their premium to be lower (I can
think of many) might be tempted to lie and underreport the actual number of
miles they drove.
The insurance company gave us twenty thousand forms, and we used them
to test our sign-at-the-top versus the sign-at-the-bottom idea. We kept half of the
forms with the “I promise that the information I am providing is true” statement
and signature line on the bottom of the page. For the other half, we moved the
statement and signature line to the top. In all other respects, the two forms were
identical. We mailed the forms to twenty thousand customers and waited a
while, and when we got the forms back we were ready to compare the amount of
driving reported on the two types of forms. What did we find?
When we estimated the amount of driving that took place over the last year,
those who signed the form first appeared to have driven on average 26,100
miles, while those who signed at the end of the form appeared to have driven on
average 23,700 miles—a difference of about 2,400 miles. Now, we don’t know
how much those who signed at the top really drove, so we don’t know if they
were perfectly honest—but we do know that they cheated to a much lesser
degree. It is also interesting to note that this magnitude of decreased cheating
(which was about 15 percent of the total amount of driving reported) was similar
to the percentage of dishonesty we found in our lab experiments.
TOGETHER, THESE EXPERIMENTAL results suggest that although we commonly
think about signatures as ways to verify information (and of course signatures
can be very useful in fulfilling this purpose), signatures at the top of forms could
also act as a moral prophylactic.
COMPANIES ARE ALWAYS RATIONAL!
Many people believe that although individuals might behave
irrationally from time to time, large commercial companies that are
run by professionals with boards of directors and investors will always
operate rationally. I never bought into this sentiment, and the more I
interact with companies, the more I find that they are actually far less
rational than individuals (and the more I am convinced that anyone
who thinks that companies are rational has never attended a corporate
board meeting).
What do you think happened after we demonstrated to the
insurance company that we could improve honesty in mileage
reporting using their forms? Do you think the company was eager to
emend their regular practices? They were not! Or do you think anyone
asked (maybe begged) us to experiment
Some Lessons
When I ask people how we might reduce crime in society, they usually suggest
putting more police on the streets and applying harsher punishments for
offenders. When I ask CEOs of companies what they would do to solve the
problem of internal theft, fraud, overclaiming on expense reports, and sabotage
(when employees do things to hurt their employer with no concrete benefit to
themselves), they usually suggest stricter oversight and tough no-tolerance
policies. And when governments try to decrease corruption or create regulations
for more honest behavior, they often push for transparency (also known as
“sunshine policies”) as a cure for society’s ills. Of course, there is little evidence
that any of these solutions work.
By contrast, the experiments described here show that doing something as
simple as recalling moral standards at the time of temptation can work wonders
to decrease dishonest behavior and potentially prevent it altogether. This
approach works even if those specific moral codes aren’t a part of our personal
belief system. In fact, it’s clear that moral reminders make it relatively easy to
get people to be more honest—at least for a short while. If your accountant were
to ask you to sign an honor code a moment before filing your taxes or if your
insurance agent made you swear that you were telling the whole truth about that
water-damaged furniture, chances are that tax evasion and insurance fraud would
be less common.
*
What are we to make of all this? First, we need to recognize that dishonesty
is largely driven by a person’s fudge factor and not by the SMORC. The fudge
factor suggests that if we want to take a bite out of crime, we need to find a way
to change the way in which we are able to rationalize our actions. When our
ability to rationalize our selfish desires increases, so does our fudge factor,
making us more comfortable with our own misbehavior and cheating. The other
side is true as well; when our ability to rationalize our actions is reduced, our
fudge factor shrinks, making us less comfortable with misbehaving and cheating.
When you consider the range of undesirable behaviors in the world from this
stand-point—from banking practices to backdating stock options, from
defaulting on loans and mortgages to cheating on taxes—there’s a lot more to
honesty and dishonesty than rational calculations.
Of course, this means that understanding the mechanisms involved in
dishonesty is more complex and that deterring dishonesty is not an easy task—
but it also means that uncovering the intricate relationship between honesty and
dishonesty will be a more exciting adventure.
CHAPTER 2B
Golf
The income tax has made more liars out of the American people than golf
has.
—WILL ROGERS
There’s a scene in the movie The Legend of Bagger Vance where Matt Damon’s
character, Rannulph Junuh, is attempting to get his golf game back, but he makes
a critical error and his ball ends up in the woods. After making it back onto the
green, he moves a twig that is just adjacent to the ball in order to create a clear
path for his shot. As he moves the twig the ball rolls a tiny bit to the side.
According to the rules, he has to count it as a stroke. At that point in the match,
Junuh had gained enough of a lead that if he ignored the rule, he could win,
making a comeback and restoring his former glory. His youthful assistant
tearfully begs Junuh to ignore the movement of the ball. “It was an accident,” the
assistant says, “and it’s a stupid rule anyway. Plus, no one would ever know.”
Junuh turns to him and says stoically, “I will. And so will you.”
Even Junuh’s opponents suggest that most likely the ball just wobbled and
returned to its former position or that the light tricked Junuh into thinking that
the ball moved. But Junuh insists that the ball rolled away. The result is an
honorably tied game.
That scene was inspired by a real event that occurred during the 1925 U.S.
Open. The golfer, Bobby Jones, noticed that his ball moved ever so slightly as he
prepared for his shot in the rough. No one saw, no one would ever have known,
but he called the stroke on himself and went on to lose the match. When people
discovered what he’d done and reporters began to flock to him, Jones famously
asked them not to write about the event, saying “You might as well praise me for
not robbing banks.” This legendary moment of noble honesty is still referred to
by those who love the game, and for good reason.
I think this scene—both cinematic and historic—captures the romantic ideal
of golf. It’s a demonstration of man versus himself, showing both his skill and
nobility. Perhaps these characteristics of self-reliance, self-monitoring, and high
moral standards are why golf is often used as a metaphor for business ethics (not
to mention the fact that so many businesspeople spend so much time on golf
courses). Unlike other sports, golf has no referee, umpire, or panel of judges to
make sure rules are followed or to make calls in questionable situations. The
golfer, much like the businessperson, has to decide for him- or herself what is
and is not acceptable. Golfers and businesspeople must choose for themselves
what they are willing and not willing to do, since most of the time there is no one
else to supervise or check their work. In fact, golf’s three underlying rules are,
Play the ball as it lies, play the course as you find it, and if you cannot do either,
do what is fair. But “fair” is a notoriously difficult thing to determine. After all, a
lot of people might judge not counting an accidental and inconsequential change
in the ball’s location after a movement of a twig as “fair.” In fact, it might seem
pretty unfair to be penalized for an incidental movement of the ball.
DESPITE THE NOBLE heritage that golfers claim for their sport, it seems that many
people view the game in the same way Will Rogers did: as one that will make a
cheater out of anyone. That is not terribly surprising when you stop to think
about it. In golf, players hit a tiny ball across a great distance, replete with
obstacles, into a very small hole. In other words, it’s extremely frustrating and
difficult, and when we’re the ones judging our own performance, it seems that
there would be many times where we might be a little extra lenient when it
comes to applying the rules to our own score.
So in our quest to learn more about dishonesty, we turned to our nation’s
many golfers. In 2009, Scott McKenzie (a Duke undergraduate student at the
time) and I carried out a study in which we asked thousands of golfers a series of
questions about how they play the game and, most importantly, how they cheat.
We asked them to imagine situations in which nobody could observe them (as is
often the case in golf) and they could decide to follow the rules (or not) without
any negative consequences. With the help of a company that manages golf
courses, we e-mailed golfers around the United States, asking them to participate
in a survey on golf in return for a chance to win all kinds of high-end golf
equipment. About twelve thousand golfers answered our call, and here is what
we learned.
Moving the Ball
“Imagine,” we asked the participants, “that as the average golfer approaches
their ball they realize that it would be highly advantageous if the ball would lie 4
inches away from where it is currently. How likely do you think the average
golfer would be to move the ball by these 4 inches?”
This question appeared in three different versions, each describing a
different approach for improving the unfortunate location of the ball (it is a
curious coincidence, by the way, that in golf lingo the location of the ball is
called a “lie”). How comfortable do you think the average golfer would be about
moving the ball 4 inches (1) with his club; (2) with his shoe; and (3) by picking
the ball up and placing it 4 inches away?
The “moving the ball” questions were designed to see whether in golf, as in
our previous experiments, the distance from the dishonest action would change
the tendency to behave immorally. If distance worked in the same way as the
token experiment we discussed earlier (see chapter 2, “Fun with the Fudge
Factor”), we would expect to have the lowest level of cheating when the
movement was carried out explicitly with one’s hand; we would see higher
levels of cheating when the movement was accomplished with a shoe; and we
would see the highest level of dishonesty when the distance was greatest and the
movement was achieved via an instrument (a golf club) that removed the player
from direct contact with the ball.
What our results showed is that dishonesty in golf, much as in our other
experiments, is indeed directly influenced by the psychological distance from the
action. Cheating becomes much simpler when there are more steps between us
and the dishonest act. Our respondents felt that moving the ball with a club was
the easiest, and they stated that the average golfer would do it 23 percent of the
time. Next was kicking the ball (14 percent of the time), and finally, picking up
and moving the ball was the most morally difficult way to improve the ball’s
position (10 percent of the time).
These results suggest that if we pick up the ball and reposition it, there is no
way we can ignore the purposefulness and intentionality of the act, and
accordingly we cannot help but feel that we have done something unethical.
When we kick the ball with our shoe, there is a little bit of distance from the act,
but we are still the ones doing the kicking. But when the club is doing the
tapping (and especially if we move the ball in a slightly haphazard and imprecise
way) we can justify what we have done relatively easily. “After all,” we might
say to ourselves, “perhaps there was some element of luck in exactly how the
ball ended up being positioned.” In that case, we can almost fully forgive
ourselves.
Taking Mulligans
Legend has it that in the 1920s, a Canadian golfer named David Mulligan was
golfing at a country club in Montreal. One day, he teed off and wasn’t happy
with his shot, so he reteed and tried again. According to the story, he called it a
“correction shot,” but his partners thought “mulligan” was a better name, and it
stuck as the official term for a “do-over” in golf.
These days, if a shot is egregiously bad, a golfer might write it off as a
“mulligan,” place the ball back at its original starting point, and score himself as
if the shot never happened (one of my friends refers to her husband’s ex-wife as
a “mulligan”). Strictly speaking, mulligans are never allowed, but in friendly
games, players sometimes agree in advance that mulligans are permitted. Of
course, even when mulligans are not legal nor agreed upon, golfers still take
them from time to time, and those illegal mulligans were the focus of our next
set of questions.
We asked our participants how likely other golfers are to take illegal
mulligans when they could do it without being noticed by the other players. In
one version of this question, we asked them about the likelihood of someone
taking an illegal mulligan on the first hole. In the second version of the question
we asked them about the likelihood of taking an illegal mulligan on the ninth
hole.
To be clear, the rules don’t differentiate between these two acts: they are
equally prohibited. At the same time, it seems that it is easier to rationalize a doover on the first hole than on the ninth hole. If you’re on the first hole and you
start over, you can pretend that “now I am really starting the game, and from
now on every shot will count.” But if you are on the ninth hole, there is no way
for you to pretend that the game has not yet started. This means that if you take a
mulligan you have to admit to yourself that you are simply not counting a shot.
As we would expect based on what we already knew about self-justification
from our other experiments, we found a vast difference in the willingness to take
mulligans. Our golfers predicted that 40 percent of golfers would take a mulligan
on the first hole while (only?) 15 percent of golfers would take a mulligan on the
ninth hole.
Fuzzy Reality
In a third set of questions, we asked the golfers to imagine that they shot 6
strokes on a par–5 hole (a hole that good players can complete in 5 strokes). In
one version of this question we asked whether the average golfer would write
down “5” instead of “6” on his scorecard. In the second version of this question,
we asked how likely the average golfer would be to record his score accurately
but then, when it comes to adding the scores up, count the 6 as a 5 and thus get
the same discount on the score but doing so by adding incorrectly.
We wanted to see whether it would be more easily justifiable to write down
the score wrongly to start with, because once the score is written, it is hard to
justify adding incorrectly (akin to repositioning a ball by hand). After all, adding
incorrectly is an explicit and deliberate act of cheating that cannot be as easily
rationalized. That was indeed what we found. Our golfers predicted that in such
cases, 15 percent of golfers would write down an improved score, while many
fewer (5 percent) would add their score inaccurately.
The great golfer Arnold Palmer once said, “I have a tip that can take five
strokes off anyone’s golf game. It’s called an eraser.” It appears, however, that
the vast majority of golfers are unwilling to go this route, or at least that they
would have an easier time cheating if they did not write the score correctly from
the get-go. So here’s the timeless “if-a-tree-falls-in-the-forest”-type question: if a
golfer shoots a 6 on a par–5 hole, the score is not recorded, and there is no one
there to see it—is his score a 6 or a 5?
LYING ABOUT A score in this way has a lot in common with a classic thought
experiment called “Schrödinger’s cat.” Erwin Schrödinger was an Austrian
physicist who, in 1935, described the following scenario: A cat is sealed in a
steel box with a radioactive isotope that may or may not decay. If it does decay,
it will set off a chain of events that will result in the cat’s death. If not, the cat
will continue living. In Schrödinger’s story, as long as the box remains sealed,
the cat is suspended between life and death; it cannot be described as either alive
or dead. Schrödinger’s scenario was intended to critique an interpretation of
physics that held that quantum mechanics did not describe objective reality—
rather, it dealt only in probability. Leaving the philosophical aspects of physics
aside for now, Schrödinger’s cat story might serve us well here when thinking
about golf scores. A golf score might be a lot like Schrödinger’s alive-and-dead
cat: until it is written down, it does not really exist in either form. Only when it’s
written down does it obtain the status of “objective reality.”
YOU MAY BE wondering why we asked participants about “the average golfer”
rather than about their own behavior on the course. The reason for this was that
we expected that, like most people, our golfers would lie if they were asked
directly about their own tendency to behave in unethical ways. By asking them
about the behavior of others, we expected that they would feel free to tell the
truth without feeling that they are admitting to any bad behavior themselves.
*
Still, we also wanted to examine what unethical behaviors golfers would be
willing to admit to about their own behavior. What we found was that although
many “other golfers” cheat, the particular participants in our study were relative
angels: when asked about their own behavior, they admitted to moving the ball
with their club in order to improve their lie just 8 percent of the time. Kicking
the ball with their shoe was even more rare (just 4 percent of the time), and
picking up the ball and moving it occurred only 2.5 percent of the time. Now, 8
percent, 4 percent, and 2.5 percent might still look like big numbers (particularly
given the fact that a golf course has 18 holes and many different ways to be
dishonest), but they pale in comparison to what “other golfers” do.
We found similar differences in golfers’ responses regarding mulligans and
scorekeeping. Our participants reported that they would take a mulligan on the
first hole only 18 percent of the time and on the ninth hole just 4 percent of the
time. They also said that they would write in the wrong score only 4 percent of
the time, and barely 1 percent copped to something as egregious as mistallying
their scores.
So here’s a summary of our results:
I am not sure how you want to interpret these differences, but it looks to me
as though golfers not only cheat a lot in golf, they also lie about lying.
WHAT HAVE WE learned from this fairway adventure? It seems that cheating in
golf captures many of the nuances we discovered about cheating in our
laboratory experiments. When our actions are more distant from the execution of
the dishonest act, when they are suspended, and when we can more easily
rationalize them, golfers—like every other human on the planet—find it easier to
be dishonest. It also seems that golfers, like everyone else, have the ability to be
dishonest but at the same time think of themselves as honest. And what have we
learned about the cheating of businesspeople? Well. When the rules are
somewhat open to interpretation, when there are gray areas, and when people are
left to score their own performance—even honorable games such as golf can be
traps for dishonesty.
CHAPTER 3
Blinded by Our Own Motivations
Picture your next dental appointment. You walk in, exchange pleasantries with
the receptionist, and begin leafing through some old magazines while waiting for
your name to be called.
Now let’s imagine that since your last visit, your dentist went out and bought
an innovative and expensive piece of dental equipment. It’s a dental CAD/CAM
(short for computer-aided design/computer-aided manufacturing) machine, a
cutting-edge device used to customize tooth restorations such as crowns and
bridges. The device works in two steps. First it displays a 3D replica of the
patient’s teeth and gums on a computer screen, allowing the dentist to trace the
exact shape of the crown—or whatever the restoration—against the screen’s
image. This is the CAD part. Then comes the CAM part; this device molds
ceramic material into a crown according to the dentist’s blueprint. Altogether,
this fancy machine comes with a hefty price tag.
But let’s get back to you. Just as you finish skimming an article about some
politician’s marital troubles and are about to start a story about the next it-girl,
the receptionist calls your name. “Second room to the left,” she says.
You situate yourself in the dentist’s chair and engage in a bit of small talk
with the hygienist, who pokes around your mouth for a while and follows up
with a cleaning. Before long, your dentist walks in.
The dentist repeats the same general poking procedure, and as he checks
your teeth he tells the hygienist to mark teeth 3 and 4 for further observation and
to mark tooth 7 as having craze lines.
“Huh? Caze wha?” you gurgle, with your mouth open wide and the suction
tube pulling on the right side of your mouth.
The dentist stops, pulls the instruments out, carefully places them on the tray
next to him, and sits back in his chair. He then starts explaining your situation:
“Craze lines are what we call certain small cracks in the tooth enamel. But no
problem, we have a great solution for this. We’ll just use the CAD/CAM to fit
you with a crown, problem solved. How about it?” he asks.
You waver a little, but after you get his assurance that it won’t hurt one bit,
you agree. After all, you have been seeing this dentist for a long time, and
although some of his treatments over the years were rather unpleasant, you feel
that he has generally treated you well.
Now, I should point out—because your dentist might not—that craze lines
are basically very, very small cracks in the enamel of your teeth, and what’s
more, they’re almost always completely asymptomatic; many people have them
and aren’t bothered by them in the least. So, in effect, it’s usually unnecessary to
target craze lines with any kind of treatment.
LET ME GIVE you one real-life story from my friend Jim, the former vice
president of a large dental company. Over the years, Jim has encountered his fair
share of oddball dental cases, but one CAD/CAM story he told me was
particularly horrible.
A few years after the CAD/CAM equipment came onto the market, one
particular dentist in Missouri invested in the equipment, and from that point on
he seemed to start looking at craze lines differently. “He wanted to crown
everything,” Jim told me. “He was excited and enthusiastic to use his brand-new
gadget, so he recommended that many of his patients improve their smiles,
using, of course, his state-of-the-art CAD/CAM equipment.”
One of his patients was a young law student with asymptomatic craze lines;
still, he recommended that she get a crown. The young woman complied,
because she was used to listening to her dentist’s advice, but guess what?
Because of the crown, her tooth became symptomatic and then died, forcing her
to go in for a root canal. But wait, it gets worse. The root canal failed and had to
be redone, and that second root canal failed as well. As a result, the woman had
no choice but to undergo more complex and painful surgery. So what began as a
treatment for harmless craze lines ultimately resulted in a lot of pain and
financial cost for this young woman.
After the woman graduated from law school, she did her homework and
realized that (surprise!) she’d never needed that crown in the first place. As you
can imagine, she wasn’t thrilled by this, so she went after the dentist with a
vengeance, took him to court, and won.
NOW, WHAT CAN we make of this tale? As we’ve already learned, people don’t
need to be corrupt in order to act in problematic and sometimes damaging ways.
Perfectly well-meaning people can get tripped up by the quirks of the human
mind, make egregious mistakes, and still consider themselves to be good and
moral. It’s safe to say that most dentists are competent, caring individuals who
approach their work with the best of intentions. Yet, as it turns out, biased
incentives can—and do—lead even the most upstanding professionals astray.
Think about it. When a dentist decides to purchase a new device, he no
doubt believes it will help him better serve his patients. But it can also be an
expensive venture. He wants to use it to improve patient care, but he also wants
to recover his investment by charging his patients for using this wonderful new
technology. So, consciously or not, he looks for ways to do so, and voilà! The
patient ends up with a crown—sometimes necessary, other times not.
To be clear, I don’t think dentists (or the vast majority of people, for that
matter) carry out an explicit calculation of costs and benefits by weighing
patients’ well-being against their own pockets and then deliberately choose their
own self-interest over their patients’ best interest. Instead, I suspect that some
dentists who purchase the CAD/CAM equipment are reacting to the fact that
they have invested a great deal of money in the device and want to make the
most of it. This information then colors the dentists’ professional judgment,
leading them to make recommendations and decisions that are in their own selfinterest rather than doing what is best for the patient.
You might think that instances like this, when a service provider is pulled in
two directions (generally referred to as a conflict of interest), are rare. But the
reality is that conflicts of interest influence our behavior in all kinds of places
and, quite frequently, both professionally and personally.
Can I Tattoo Your Face?
Some time ago I ran smack into a rather strange conflict of interest. In this case I
was the patient. As a young man in my midtwenties—about six or seven years
after I was originally injured
*—I went back to the hospital for a routine checkup.
On that particular visit, I met with a few physicians, and they reviewed my case.
Later, I met the head of the burn department, who seemed especially happy to
see me.
“Dan, I have a fantastic new treatment for you!” he exclaimed. “You see,
because you have thick, dark hair, when you shave, no matter how closely you
try to shave, there will always be little black dots where your hair grows. But
since the right side of your face is scarred, you don’t have any facial hair or
small black dots on that side, making your face look asymmetrical.”
At that point, he launched into a short lecture on the importance of symmetry
for aesthetic and social reasons. I knew how important symmetry was to him,
because I was given a similar minilecture a few years earlier, when he convinced
me to undergo a complex and lengthy operation in which he would take part of
my scalp together with its blood supply and re-create the right half of my right
eyebrow. (I’d undergone that complex twelve-hour operation and liked the
results.)
Then came his proposal: “We have started tattooing little dots resembling
stubble onto scarred faces much like yours, and our patients have been
incredibly happy with the results.”
“That sounds interesting,” I said. “Can I talk to one of the patients that had
this procedure?”
“Unfortunately you can’t—that would violate medical confidentiality,” he
said. Instead, he showed me pictures of the patients—not of their whole faces,
just the parts that were tattooed. And sure enough, it did look as though the
scarred faces were covered with black stubblelike specks.
But then I thought of something. “What happens when I grow old and my
hair turns gray?” I asked.
“Oh, that’s no problem,” he replied. “When that happens, we’ll just lighten
up the tattoo with a laser.” Satisfied, he got up, adding “Come back tomorrow at
nine. Just shave the left side of your face as you usually do, with the same
closeness of shave that you like to keep, and I’ll tattoo the right side of your face
to look the same. I guarantee that by noon, you’ll be happier and more
attractive.”
I mulled over the possible treatment on my drive home and for the rest of the
day. I also realized that in order to get the full benefit from this treatment, I
would have to shave in exactly the same way for the rest of my life. I walked
into the department head’s office the next morning and told him that I was not
interested in the procedure.
I did not expect what came next. “What is wrong with you?” he growled.
“Do you like looking unattractive? Do you derive some kind of strange pleasure
from looking asymmetrical? Do women feel sorry for you and give you
sympathy sex? I’m offering you a chance to fix yourself in a very simple and
elegant way. Why not just take it and be grateful?”
“I don’t know,” I said. “I’m just uncomfortable with the idea. Let me think
about it some more.”
You may find it hard to believe that the department head could be so
aggressive and harsh, but I assure you this is exactly what he told me. At the
same time, it was not his usual manner with me, so I was puzzled by his
unrelenting approach. In fact, he was a fantastic, dedicated doctor who treated
me well and worked very hard to make me better. It was also not the first time I
refused a treatment. Over many years of interacting with medical professionals, I
had decided to have some treatments and not others. But none of my doctors,
including the head of the burn department, had ever tried to guilt me into having
a treatment.
In an attempt to solve this mystery, I went to his deputy, a younger doctor
with whom I had a friendly rapport. I asked him to explain why the department
head had put me under such pressure.
“Ah, yes, yes,” the deputy said. “He’s already performed this procedure on
two patients, and he needs just one more in order to publish a scientific paper in
one of the leading medical journals.”
This additional information certainly helped me better understand the
conflict of interest I was up against. Here was a really good physician, someone I
had known for many years and who had consistently treated me with compassion
and great care. Yet, despite the fact that he cared a great deal about me in
general, in this instance he was unable to see past his conflict of interest. It goes
to show just how hard it is to overcome conflicts of interests once they
fundamentally color our view of the world.
After years of experience publishing in academic journals myself, I now
have a greater understanding of this physician’s conflict of interest (more about
this later). Of course, I’ve never tried to coerce anyone into tattooing his face—
but there’s still time for that.
The Hidden Cost of Favors
One other common cause of conflicts of interest is our inherent inclination to
return favors. We humans are deeply social creatures, so when someone lends us
a hand in some way or presents us with a gift, we tend to feel indebted. That
feeling can in turn color our view, making us more inclined to try to help that
person in the future.
One of the most interesting studies on the impact of favors was carried out
by Ann Harvey, Ulrich Kirk, George Denfield, and Read Montague (at the time
all were at the Baylor College of Medicine). In this study, Ann and her
colleagues looked into whether a favor could influence aesthetic preferences.
When participants arrived at the neuroscience lab at Baylor, they were told
that they would be evaluating art from two galleries, one called “Third Moon”
and another called “Lone Wolfe.” The participants were informed that the
galleries had generously provided their payment for participating in this
experiment. Some were told that their individual payment was sponsored by
Third Moon, while the others were told that their individual payment was
sponsored by Lone Wolfe.
Armed with this information, the participants moved to the main part of the
experiment. One by one, they were asked to remain as motionless as possible in
a functional magnetic resonance imagining (fMRI) scanner, a large machine
with a cylinder-shaped hole in the middle. Once they were situated inside the
massive magnet, they viewed a series of sixty paintings, one at a time. All the
paintings were by Western artists dating from the thirteenth through the
twentieth century and ranged from representational to abstract art. But the sixty
paintings were not all that they saw. Near the top-left corner of each painting
was the handsome logo of the gallery where that particular picture could be
purchased—which meant that some pictures were presented as if they came from
the gallery that sponsored the participant, and some pictures were presented as if
they came from the non-sponsoring gallery.
Once the scanning portion of the experiment was over, each participant was
asked to take another look at each of the painting-logo combinations, but this
time they were asked to rate each of the pictures on a scale that ranged from
“dislike” to “like.”
With the rating information in hand, Ann and her colleagues could compare
which paintings the participants liked more, the ones from Third Moon or the
ones from Lone Wolfe. As you might suspect, when the researchers examined
the ratings they found that participants gave more favorable ratings to the
paintings that came from their sponsoring gallery.
You might think that this preference for the sponsoring gallery was due to a
kind of politeness—or maybe just lip service, the way we compliment friends
who invite us for dinner even when the food is mediocre. This is where the fMRI
part of the study came in handy. Suggesting that the effects of reciprocity run
deep, the brain scans showed the same effect; the presence of the sponsor’s logo
increased the activity in the parts of the participants’ brains that are related to
pleasure (particularly the ventromedial prefrontal cortex, a part of the brain that
is responsible for higher-order thinking, including associations and meaning).
This suggested that the favor from the sponsoring gallery had a deep effect on
how people responded to the art. And get this: when participants were asked if
they thought that the sponsor’s logo had any effect on their art preferences, the
universal answer was “No way, absolutely not.”
What’s more, different participants were given varying amounts of money
for their time in the experiments. Some received $30 from their sponsoring
gallery, others received $100. At the highest level, participants were paid $300.
It turned out that the favoritism toward the sponsoring gallery increased as the
amount of earnings grew. The magnitude of brain activation in the pleasure
centers of the brain was lowest when the payment was $30, higher when the
payment was $100, and highest when the payment was $300.
These results suggest that once someone (or some organization) does us a
favor, we become partial to anything related to the giving party—and that the
magnitude of this bias increases as the magnitude of the initial favor (in this case
the amount of payment) increases. It’s particularly interesting that financial
favors could have an influence on one’s preferences for art, especially
considering that the favor (paying for their participation in the study) had
nothing at all to do with the art, which had been created independently of the
galleries. It is also interesting to note that participants knew the gallery would
pay their compensation regardless of their ratings of the paintings and yet the
payment (and its magnitude) established a sense of reciprocity that guided their
preferences.
Fun with Pharma
Some people and companies understand this human propensity for reciprocity
very well and consequently spend a lot of time and money trying to engender a
feeling of obligation in others. To my mind, the profession that most embodies
this type of operation, that is, the one that depends most on creating conflicts of
interests, is—of course—that of governmental lobbyists, who spend a small
fraction of their time informing politicians about facts as reported by their
employers and the rest of their time trying to implant a feeling of obligation and
reciprocity in politicians who they hope will repay them by voting with their
interest in mind.
But lobbyists are not alone in their relentless pursuit of conflicts of interest,
and some other professions could arguably give them a run for their wellapportioned money. For example, let’s consider the way representatives for drug
companies (pharma reps) run their business. A pharma rep’s job is to visit
doctors and convince them to purchase medical equipment and drugs to treat
everything from A(sthma) to Z(ollinger-Ellison syndrome). First they may give a
doctor a free pen with their logo, or perhaps a notepad, a mug, or maybe some
free drug samples. Those small gifts can subtly influence physicians to prescribe
a drug more often—all because they feel the need to give back.
1
But small gifts and free drug samples are just a few of the many
psychological tricks that pharma reps use as they set out to woo physicians.
“They think of everything,” my friend and colleague (let’s call him MD) told
me. He went on to explain that drug companies, especially smaller ones, train
their reps to treat doctors as if they were gods. And they seem to have a
disproportionately large reserve of attractive reps. The whole effort is
coordinated with military precision. Every self-respecting rep has access to a
database that tells them exactly what each doctor has prescribed over the last
quarter (both that company’s drugs as well as their competitors’). The reps also
make it their business to know what kind of food each doctor and their office
staff likes, what time of day they are most likely to see reps, and also which type
of rep gets the most face time with the doctors. If the doctor is noted to spend
more time with a certain female rep, they may adjust that rep’s rotation so that
she can spend more time in that office. If the doctor is a fan of the military,
they’ll send him a veteran. The reps also make it a point to be agreeable with the
doctor’s outer circles, so when the rep arrives they start by handing out candy
and other small gifts to the nurses and the front desk, securing themselves in
everyone’s good graces from the get-go.
One particularly interesting practice is the “dine-and-dash,” where, in the
name of education, doctors can simply pull up at prespecified take-out
restaurants and pick up whatever they want. Even medical students and trainees
are pulled into some schemes. One particularly creative example of this strategy
was the famous black mug. A black mug with the company’s logo was handed
out to doctors and residents, and the company arranged it such that a doctor
could take this mug to any location of a local coffee chain (which shall go
unnamed) and get as much espresso or cappuccino as he or she wanted. The
clamor for this mug was so great that it became a status symbol among students
and trainees. As these practices became more extravagant, there was also more
regulation from hospitals and the American Medical Association, limiting the
use of these aggressive marketing tactics. Of course, as the regulations become
more stringent, pharma reps continue to search for new and innovative
approaches to influence physicians. And the arms race continues …*
A FEW YEARS AGO, my colleague Janet Schwartz (a professor at Tulane
University) and I invited some pharmaceutical reps to dinner. We basically tried
the pharma reps at their own game; we took them to a nice restaurant and kept
the wine flowing. Once we had them feeling happily lubricated, they were ready
to tell us the tricks of their trade. And what we learned was fairly shocking.
Picture one of those pharma reps, an attractive, charming man in his early
twenties. Not the kind of guy who would have any trouble finding a date. He
told us how he had once persuaded a reluctant female physician to attend an
informational seminar about a medication he was promoting—by agreeing to
escort her to a ballroom dancing class. It was an unstated quid pro quo: the rep
did a personal favor for the doctor, and the doctor took his free drug samples and
promoted the product to her patients.
Another common practice, the reps told us, was to take fancy meals to the
entire doctor’s office (one of the perks of being a nurse or receptionist, I
suppose). One doctor’s office even required alternating days of steak and lobster
for lunch if the reps wanted access to the doctors. Even more shocking, we found
out that physicians sometimes called the reps into the examination room (as an
“expert”) to directly inform patients about the way certain drugs work.
Hearing stories from the reps who sold medical devices was even more
disturbing. We learned that it’s common practice for device reps to peddle their
medical devices in the operating room in real time and while a surgery is under
way.
Janet and I were surprised at how well the pharmaceutical reps understood
classic psychological persuasion strategies and how they employed them in a
sophisticated and intuitive manner. Another clever tactic that they told us about
involved hiring physicians to give a brief lecture to other doctors about a drug
they were trying to promote. Now, the pharma reps really didn’t care about what
the audience took from the lecture—what they were actually interested in was
the effect that giving the lecture had on the speaker. They found that after giving
a short lecture about the benefits of a certain drug, the speaker would begin to
believe his own words and soon prescribe accordingly. Psychological studies
show that we quickly and easily start believing whatever comes out of our own
mouths, even when the original reason for expressing the opinion is no longer
relevant (in the doctors’ case, that they were paid to say it). This is cognitive
dissonance at play; doctors reason that if they are telling others about a drug, it
must be good—and so their own beliefs change to correspond to their speech,
and they start prescribing accordingly.
The reps told us that they employed other tricks too, turning into chameleons
—switching various accents, personalities, and political affiliations on and off.
They prided themselves on their ability to put doctors at ease. Sometimes a
collegial relationship expanded into the territory of social friendship—some reps
would go deep-sea fishing or play basketball with the doctors as friends. Such
shared experiences allowed the physicians to more happily write prescriptions
that benefited their “buddies.” The physicians, of course, did not see that they
were compromising their values when they were out fishing or shooting hoops
with the drug reps; they were just taking a well-deserved break with a friend
with whom they just happened to do business. Of course, in many cases the
doctors probably didn’t realize that they were being manipulated—but there is
no doubt that they were.
DISGUISED FAVORS ARE one thing, but there are many cases when conflicts of
interest are more easily recognizable. Sometimes a drug maker pays a doctor
thousands of dollars in consulting fees. Sometimes the company donates a
building or gives an endowment to a medical researcher’s department in the
hope of influencing his views. This type of action creates immense conflicts of
interest—especially at medical schools, where pharmaceutical bias can be passed
from the medical professor to medical students and along to patients.
Duff Wilson, a reporter for The New York Times, described one example of
this type of behavior. A few years ago, a Harvard Medical School student
noticed that his pharmacology professor was promoting the benefits of
cholesterol drugs and downplaying their side effects. When the student did some
googling, he discovered that the professor was on the payroll of ten drug
companies, five of which made cholesterol drugs. And the professor wasn’t
alone. As Wilson put it, “Under the school’s disclosure rules, about 1,600 of
8,900 professors and lecturers at Harvard Medical School have reported to the
dean that they or a family member had a financial interest in a business related to
their teaching, research, or clinical care.”
2 When professors publicly pass drug
recommendations off as academic knowledge, we have a serious problem.
Fudging the Numbers
If you think that the world of medicine is rife with conflicts of interest, let’s
consider another profession in which these conflicts may be even more
widespread. Yes, I’m talking about the wonderland of financial services.
Say it’s 2007, and you’ve just accepted a fantastic banking job on Wall
Street. Your bonus could be in the neighborhood of $5 million a year, but only if
you view mortgage-backed securities (or some other new financial instrument)
in a positive light. You’re being paid a lot of money to maintain a distorted view
of reality, but you don’t notice the tricks that your big bonus plays on your
perception of reality. Instead, you are quickly convinced that mortgage-backed
securities are every bit as solid as you want to believe they are.
Once you’ve accepted that mortgage-backed securities are the wave of the
future, you’re at least partially blind to their risks. On top of that, it’s notoriously
hard to evaluate how much securities are really worth. As you sit there with your
large and complex Excel spreadsheet full of parameters and equations, you try to
figure out the real value of the securities. You change one of the discount
parameters from 0.934 to 0.936, and right off the bat you see how the value of
the securities jumps up. You continue to play around with the numbers,
searching for parameters that provide the best representation of “reality,” but
with one eye you also see the consequences of your parameter choices for your
personal financial future. You continue to play with the numbers for a while
longer, until you are convinced that the numbers truly represent the ideal way to
evaluate mortgage-backed securities. You don’t feel bad because you are certain
that you have done your best to represent the values of the securities as
objectively as possible.
Moreover, you aren’t dealing with real cash; you are only playing with
numbers that are many steps removed from cash. Their abstractness allows you
to view your actions more as a game, and not as something that actually affects
people’s homes, livelihoods, and retirement accounts. You are also not alone.
You realize that the smart financial engineers in the offices next to yours are
behaving more or less the same way as you and when you compare your
evaluations to theirs, you realize that a few of your coworkers have chosen even
more extreme values than yours. Believing that you are a rational creature, and
believing that the market is always correct, you are even more inclined to accept
what you’re doing—and what everyone else is doing (we’ll learn more about this
in chapter 8)—as the right way to go. Right?
Of course, none of this is actually okay (remember the financial crisis of
2008?), but given the amount of money involved, it feels natural to fudge things
a bit. And it’s perfectly human to behave this way. Your actions are highly
problematic, but you don’t see them as such. After all, your conflicts of interest
are supported by the facts that you’re not dealing with real money; that the
financial instruments are mind-bogglingly complex; and that every one of your
colleagues is doing the same thing.
The riveting (and awfully distressing) Academy Award–winning
documentary Inside Job shows in detail how the financial services industry
corrupted the U.S. government, leading to a lack of oversight on Wall Street and
to the financial meltdown of 2008. The film also describes how the financial
services industry paid leading academics (deans, heads of departments,
university professors) to write expert reports in the service of the financial
industry and Wall Street. If you watch the film, you will most likely feel puzzled
by the ease with which academic experts seemed to sell out, and think that you
would never do the same.
But before you put a guarantee on your own standards of morality, imagine
that I (or you) were paid a great deal to be on Giantbank’s audit committee. With
a large part of my income depending on Giantbank’s success, I would probably
not be as critical as I am currently about the bank’s actions. With a hefty enough
incentive I might not, for example, repeatedly say that investments must be
transparent and clear and that companies need to work hard to try to overcome
their conflicts of interests. Of course, I’ve yet to be on such a committee, so for
now it’s easy for me to think that many of the actions of the banks have been
reprehensible.
Academics Are Conflicted Too
When I reflect on the ubiquity of conflicts of interest and how impossible they
are to recognize in our own lives, I have to acknowledge that I’m susceptible to
them as well.
We academics are sometimes called upon to use our knowledge as
consultants and expert witnesses. Shortly after I got my first academic job, I was
invited by a large law firm to be an expert witness. I knew that some of my more
established colleagues provided expert testimonials as a regular side job for
which they were paid handsomely (though they all insisted that they didn’t do it
for the money). Out of curiosity, I asked to see the transcripts of some of their
old cases, and when they showed me a few I was surprised to discover how onesided their use of the research findings was. I was also somewhat shocked to see
how derogatory they were in their reports about the opinions and qualifications
of the expert witnesses representing the other side—who in most cases were also
respectable academics.
Even so, I decided to try it out (not for the money, of course), and I was paid
quite a bit to give my expert opinion.
* Very early in the case I realized that the
lawyers I was working with were trying to plant ideas in my mind that would
buttress their case. They did not do it forcefully or by saying that certain things
would be good for their clients. Instead, they asked me to describe all the
research that was relevant to the case. They suggested that some of the less
favorable findings for their position might have some methodological flaws and
that the research supporting their view was very important and well done. They
also paid me warm compliments each time that I interpreted research in a way
that was useful to them. After a few weeks, I discovered that I rather quickly
adopted the viewpoint of those who were paying me. The whole experience
made me doubt whether it’s at all possible to be objective when one is paid for
his or her opinion. (And now that I am writing about my lack of objectivity, I am
sure that no one will ever ask me to be an expert witness again—and maybe
that’s a good thing.)
The Drunk Man and the Data Point
I had one other experience that made me realize the dangers of conflicts of
interest; this time it was in my own research. At the time, my friends at Harvard
were kind enough to let me use their behavioral lab to conduct experiments. I
was particularly interested in using their facility because they recruited residents
from the surrounding area rather than relying only on students.
One particular week, I was testing an experiment on decision making, and,
as is usually the case, I predicted that the performance level in one of the
conditions would be much higher than the performance level in the other
condition. That was basically what the results showed—aside from one person.
This person was in the condition I expected to perform best, but his performance
was much worse than everyone else’s. It was very annoying. As I examined his
data more closely, I discovered that he was about twenty years older than
everyone else in the study. I also remembered that there was one older fellow
who was incredibly drunk when he came to the lab.
The moment I discovered that the offending participant was drunk, I realized
that I should have excluded his data in the first place, given that his decisionmaking ability was clearly compromised. So I threw out his data, and instantly
the results looked beautiful—showing exactly what I expected them to show.
But, a few days later I began thinking about the process by which I decided to
eliminate the drunk guy. I asked myself: what would have happened if this
fellow had been in the other condition—the one I expected to do worse? If that
had been the case, I probably would not have noticed his individual responses to
start with. And if I had, I probably would not have even considered excluding his
data.
In the aftermath of the experiment, I could easily have told myself a story
that would excuse me from using the drunk guy’s data. But what if he hadn’t
been drunk? What if he had some other kind of impairment that had nothing to
do with drinking? Would I have invented another excuse or logical argument to
justify excluding his data? As we will see in chapter 7, “Creativity and
Dishonesty,” creativity can help us justify following our selfish motives while
still thinking of ourselves as honest people.
I decided to do two things. First, I reran the experiment to double-check the
results, which worked out beautifully. Then I decided it was okay to create
standards for excluding participants from an experiment (that is, we wouldn’t
test drunks or people who couldn’t understand the instructions). But the rules for
exclusion have to be made up front, before the experiment takes place, and
definitely not after looking at the data.
What did I learn? When I was deciding to exclude the drunk man’s data, I
honestly believed I was doing so in the name of science—as if I were heroically
fighting to clear the data so that the truth could emerge. It didn’t occur to me that
I might be doing it for my own self-interest, but I clearly had another motivation:
to find the results I was expecting. More generally, I learned—again—about the
importance of establishing rules that can safeguard ourselves from ourselves.
Disclosure: A Panacea?
So what is the best way to deal with conflicts of interest? For most people, “full
disclosure” springs to mind. Following the same logic as “sunshine policies,” the
basic assumption underlying disclosure is that as long as people publicly declare
exactly what they are doing, all will be well. If professionals were to simply
make their incentives clear and known to their clients, so the thinking goes, the
clients can then decide for themselves how much to rely on their (biased) advice
and then make more informed decisions.
If full disclosure were the rule of the land, doctors would inform their
patients when they own the equipment required for the treatments they
recommend. Or when they are paid to consult for the manufacturer of the drugs
that they are about to prescribe. Financial advisers would inform their clients
about all the different fees, payments, and commissions they get from various
vendors and investment houses. With that information in hand, consumers
should be able to appropriately discount the opinions of those professionals and
make better decisions. In theory, disclosure seems to be a fantastic solution; it
both exonerates the professionals who are acknowledging their conflicts of
interest and it provides their clients with a better sense of where their
information is coming from.
HOWEVER, IT TURNS out that disclosure is not always an effective cure for
conflicts of interest. In fact, disclosure can sometimes make things worse. To
explain how, allow me to run you through a study conducted by Daylian Cain (a
professor at Yale University), George Loewenstein (a professor at Carnegie
Mellon University), and Don Moore (a professor at the University of California,
Berkeley). In this experiment, participants played a game in one of two roles.
(By the way, what researchers call a “game” is not what any reasonable kid
would consider a game.) Some of the participants played the role of estimators:
their task was to guess the total amount of money in a large jar full of loose
change as accurately as possible. These players were paid according to how
close their guess was to the real value of the money in the jar. The closer their
estimates were, the more money they received, and it didn’t matter if they
missed by overestimating or underestimating the true value.
The other participants played the role of advisers, and their task was to
advise the estimators on their guesses. (Think of someone akin to your stock
adviser, but with a much simpler task.) There were two interesting differences
between the estimators and the advisers. The first was that whereas the
estimators were shown the jar from a distance for a few seconds, the advisers
had more time to examine it, and they were also told that the amount of money
in the jar was between $10 and $30. That gave the advisers an informational
edge. It made them relative experts in the field of estimating the jar’s value, and
it gave the estimators a very good reason to rely on their advisers’ reports when
formulating their guesses (comparable to the way we rely on experts in many
areas of life).
The second difference concerned the rule for paying the advisers. In the
control condition, the advisers were paid according to the accuracy of the
estimators’ guesses, so no conflicts of interest were involved. In the conflict-ofinterest condition, the advisers were paid more as the estimators overguessed the
value of the coins in the jar to a larger degree. So if the estimators overguessed
by $1, it was good for the advisers—but it was even better if they overguessed
by $3 or $4. The higher the overestimation, the less the estimator made but the
more the adviser pocketed.
So what happened in the control condition and in the conflict-of-interest
condition? You guessed it: in the control condition, advisers suggested an
average value of $16.50, while in the conflict-of-interest condition, the advisers
suggested an estimate that was over $20. They basically goosed the estimated
value by almost $4. Now, you can look at the positive side of this result and tell
yourself, “Well, at least the advice was not $36 or some other very high
number.” But if that is what went through your mind, you should consider two
things: first, that the adviser could not give clearly exaggerated advice because,
after all, the estimator did see the jar. If the value had been dramatically too
high, the estimator would have dismissed the suggestion altogether. Second,
remember that most people cheat just enough to still feel good about themselves.
In that sense, the fudge factor was an extra $4 (or about 25 percent of the
amount).
The importance of this experiment, however, showed up in the third
condition—the conflict-of-interest-plus-disclosure condition. Here the payment
for the adviser was the same as it was in the conflict-of-interest condition. But
this time the adviser had to tell the estimator that he or she (the adviser) would
receive more money when the estimator overguessed. The sunshine policy in
action! That way, the estimator could presumably take the adviser’s biased
incentives into account and discount the advice of the adviser appropriately.
Such a discount of the advice would certainly help the estimator, but what about
the effect of the disclosure on the advisers? Would the need to disclose eliminate
their biased advice? Would disclosing their bias stretch the fudge factor? Would
they now feel more comfortable exaggerating their advice to an even greater
degree? And the billion-dollar question is this: which of these two effects would
prove to be larger? Would the discount that the estimator applied to the adviser’s
advice be smaller or larger than the extra exaggeration of the adviser?
The results? In the conflict-of-interest-plus-disclosure condition, the advisers
increased their estimates by another $4 (from $20.16 to $24.16). And what did
the estimators do? As you can probably guess, they did discount the estimates,
but only by $2. In other words, although the estimators did take the advisers’
disclosure into consideration when formulating their estimates, they didn’t
subtract nearly enough. Like the rest of us, the estimators didn’t sufficiently
recognize the extent and power of their advisers’ conflicts of interest.
The main takeaway is this: disclosure created even greater bias in advice.
With disclosure the estimators made less money and the advisers made more.
Now, I am not sure that disclosure will always make things worse for clients, but
it is clear that disclosure and sunshine policies will not always make things
better.
So What Should We Do?
Now that we understand conflicts of interest a bit better, it should be clear what
serious problems they cause. Not only are they ubiquitous, but we don’t seem to
fully appreciate their degree of influence on ourselves and on others. So where
do we go from here?
One straightforward recommendation is to try to eradicate conflicts of
interest altogether, which of course is easier said than done. In the medical
domain, that would mean, for example, that we would not allow doctors to treat
or test their own patients using equipment that they own. Instead, we’d have to
require that an independent entity, with no ties to the doctors or equipment
companies, conduct the treatments and tests. We would also prohibit doctors
from consulting for drug companies or investing in pharmaceutical stocks. After
all, if we don’t want doctors to have conflicts of interest, we need to make sure
that their income doesn’t depend on the number and types of procedures or
prescriptions they recommend. Similarly, if we want to eliminate conflicts of
interest for financial advisers, we should not allow them to have incentives that
are not aligned with their clients’ best interests—no fees for services, no
kickbacks, and no differential pay for success and failure.
Though it is clearly important to try to reduce conflicts of interest, it is not
easy to do so. Take contractors, lawyers, and car mechanics, for example. The
way these professionals are paid puts them into terrible conflicts of interest
because they both make the recommendation and benefit from the service, while
the client has no expertise or leverage. But stop for a few minutes and try to
think about a compensation model that would not involve any conflicts of
interest. If you are taking the time to try to come up with such an approach, you
most likely agree that it is very hard—if not impossible—to pull off. It is also
important to realize that although conflicts of interest cause problems, they
sometimes happen for good reason. Take the case of physicians (and dentists)
ordering treatments that use equipment they own. Although this is a potentially
dangerous practice from the perspective of conflicts of interest, it also has some
built-in advantages: professionals are more likely to purchase equipment that
they believe in; they are likely to become experts in using it; it can be much
more convenient for the patient; and the doctors might even conduct some
research that could help improve the equipment or the ways in which it is used.
The bottom line is that it is no easy task to come up with compensation
systems that don’t inherently involve—and sometimes rely on—conflicts of
interest. Even if we could eliminate all conflicts of interest, the cost of doing so
in terms of decreased flexibility and increased bureaucracy and oversight might
not be worth it—which is why we should not overzealously advocate draconian
rules and restrictions (say, that physicians can never talk to pharma reps or own
medical equipment). At the same time, I do think it’s important for us to realize
the extent to which we can all be blinded by our financial motivations. We need
to acknowledge that situations involving conflicts of interest have substantial
disadvantages and attempt to thoughtfully reduce them when their costs are
likely to outweigh their benefits.
As you might expect, there are many straightforward instances where
conflicts of interest should simply be eliminated. For example, the conflicts for
financial advisers who receive side payments, auditors who serve as consultants
to the same firms, financial professionals who are paid handsome bonuses when
their clients make money but lose nothing when their clients lose their shirts,
rating agencies that are paid by the companies they rate, and politicians who
accept money and favors from corporations and lobbyists in exchange for their
votes; in all of these cases it seems to me that we must do our best to eradicate as
many conflicts of interest as possible—most likely by regulation.
You’re probably skeptical that regulation of this sort could ever happen.
When regulation by the government or by professional organizations does not
materialize, we as consumers should recognize the danger that conflicts of
interest bring with them and do our best to seek service providers who have
fewer conflicts of interest (or, if possible, none). Through the power of our
wallets we can push service providers to meet a demand for reduced conflicts of
interest.
Finally, when we face serious decisions in which we realize that the person
giving us advice may be biased—such as when a physician offers to tattoo our
faces—we should spend just a little extra time and energy to seek a second
opinion from a party that has no financial stake in the decision at hand.
CHAPTER 4
Why We Blow It When We’re Tired
Imagine yourself at the end of a really long, hard day. Let’s say it’s the most
exhausting of days: moving day. You’re completely exhausted. Even your hair
feels tired. Cooking is certainly out of the question. You don’t even have the
energy to locate a pan, plate, and fork, much less put them to use. Clearly it’s
going to be a take-out night.
Within a block of your new place are three restaurants. One is a little bistro
with fresh salads and paninis. Another is a Chinese place; the greasy, salty
smells emanating from within make the back of your mouth tingle. There’s also
a cute mom-and-pop pizzeria where the locals enjoy cheesy slices twice the size
of their faces. To which restaurant do you drag your tired, aching body? Which
kind of cuisine would you prefer to enjoy on your new floor? By contrast,
consider what your choice might be if the meal were after an afternoon spent
relaxing in the backyard with a good book.
In case you haven’t noticed, on stressful days many of us give in to
temptation and choose one of the less healthy alternatives. Chinese takeout and
pizza are practically synonymous with moving day, conjuring up an image of a
young, attractive, tired, but happy couple surrounded by cardboard boxes and
eating chow mein out of the box with chopsticks. And we all remember the
times college friends offered us pizza and beer in exchange for helping them
move.
This mysterious connection between exhaustion and the consumption of
junk food is not just a figment of your imagination. And it is the reason why so
many diets die on the chopping block of stress and why people start smoking
again after a crisis.
Let Us Eat Cake
The key to this mystery has to do with the struggle between the impulsive (or
emotional) and the rational (or deliberative) parts of ourselves. This is not a new
idea; many seminal books (and academic papers) throughout history have had
something to say about the conflicts between desire and reason. We have Adam
and Eve, tempted by the prospect of forbidden knowledge and that succulent
fruit. There was Odysseus, who knew he’d be lured by the Sirens’ song and
cleverly ordered his crew to tie him to the mast and fill their ears with wax to
muffle the tantalizing call (that way, Odysseus could have it both ways—he
could hear the song without worrying that the men would wreck the ship). And
in one of the most tragic struggles between emotion and reason, Shakespeare’s
Romeo and Juliet fell hard for each other, despite Friar Laurence’s warning that
untamed passion only brings disaster.
In a fascinating demonstration of the tension between reason and desire,
Baba Shiv (a professor at Stanford University) and Sasha Fedorikhin (a
professor at Indiana University) examined the idea that people fall into
temptation more frequently when the part of their brain that is in charge of
deliberative thinking is otherwise occupied. To reduce participants’ ability to
think effectively, Baba and Sasha did not remove parts of their brains (as animal
researchers sometimes do), nor did they use magnetic pulses to disrupt thinking
(though there are machines that can do that). Instead, they decided to tax their
participants’ ability to think by piling on what psychologists call cognitive load.
Simply put, they wanted to find out whether having a lot on one’s mind would
leave less cognitive room for resisting temptation and make people more likely
to succumb to it.
Baba and Sasha’s experiment went like this: they divided participants into
two groups and asked members of one group to remember a two-digit number
(something like, say, 35) and they asked members of the other group to
remember a seven-digit number (say, 7581280). The participants were told that
in order to get their payment for the experiment, they would have to repeat the
number to another experimenter who was waiting for them in a second room at
the other end of the corridor. And if they didn’t remember the number? No
reward.
The participants lined up to take part in the experiment and were briefly
shown either the two-digit number or the seven-digit number. With their
numbers in mind, they each walked down the hall to the second room where they
would be asked to recall the number. But on the way, they unexpectedly passed
by a cart displaying pieces of rich, dark chocolate cake and bowls of colorful,
healthy-looking fruit. As participants passed the cart, another experimenter told
them that once they got to the second room and recited their number they could
have one of the two snacks—but they had to make their decision right then, at
the cart. The participants made their choice, received a slip of paper indicating
their chosen snack, and off they went to the second room.
What decisions did participants make while laboring under more and less
cognitive strain? Did the “Yum, cake!” impulse win the day, or did they select
the healthy fruit salad (the well-reasoned choice)? As Baba and Sasha suspected,
the answer depended in part on whether the participants were thinking about an
easy-to-remember number or a hard one. Those breezing down the hall with a
mere “35” on their minds chose the fruit much more frequently than those
struggling with “7581280.” With their higher-level faculties preoccupied, the
seven-digit group was less able to overturn their instinctive desires, and many of
them ended up succumbing to the instantly gratifying chocolate cake.
The Tired Brain
Baba and Sasha’s experiment showed that when our deliberative reasoning
ability is occupied, the impulsive system gains more control over our behavior.
But the interplay between our ability to reason and our desires gets even more
complicated when we think about what Roy Baumeister (a professor at Florida
State University) coined “ego depletion.”
To understand ego depletion, imagine that you’re trying to lose a few extra
pounds. One day at work, you are eyeing a cheese danish at the morning
meeting, but you’re trying to be good, so you work very hard to resist the
temptation and just sip your coffee instead. Later that day, you are craving
fettuccine alfredo for lunch but you force yourself to order a garden salad with
grilled chicken. An hour later, you want to knock off a little early since your
boss is out, but you stop yourself and say, “No, I must finish this project.” In
each of these instances your hedonic instincts prompt you toward pleasurable
types of gratification, while your laudable self-control (or willpower) applies
opposing force in an attempt to counteract these urges.
The basic idea behind ego depletion is that resisting temptation takes
considerable effort and energy. Think of your willpower as a muscle. When we
see fried chicken or a chocolate milkshake, our first reaction is an instinctive
“Yum, want!” Then, as we try to overcome the desire, we expend a bit of
energy. Each of the decisions we make to avoid temptation takes some degree of
effort (like lifting a weight once), and we exhaust our willpower by using it over
and over (like lifting a weight over and over). This means that after a long day of
saying “no” to various and sundry temptations, our capacity for resisting them
diminishes—until at some point we surrender and end up with a belly full of
cheese danish, Oreos, french fries, or whatever it is that makes us salivate. This,
of course, is a worrisome thought. After all, our days are increasingly full of
decisions, along with a never-ending barrage of temptations. If our repeated
attempts to control ourselves deplete our ability to do so, is it any wonder that
we so often fail? Ego depletion also helps explain why our evenings are
particularly filled with failed attempts at self-control—after a long day of
working hard to be good, we get tired of it all. And as night falls, we are
particularly likely to succumb to our desires (think of late-night snacking as the
culmination of a day’s worth of resisting temptation).
WHEN JUDGES GET TIRED
In case you’ve got a parole hearing coming up, make sure it’s first
thing in the morning or right after lunchtime. Why? According to a
study by Shai Danziger (a professor at Tel Aviv University), Jonathan
Levav (a professor at Stanford University), and Liora Avnaim-Pesso (a
professor at Ben-Gurion University of the Negev), judges on parole
boards tend to grant parole more frequently when they are most
refreshed. Investigating a large set of parole rulings in Israel, the
researchers found that parole boards were more likely to grant parole
during their first cases of the day and just after their lunch breaks.
Why? The default decision of parole boards is not to grant parole. But
it seems that when the judges felt rejuvenated, which was first thing in
the morning or after just having eaten and taken a break, they had an
increased ability to override their standard decision, make a more
effortful decision, and grant parole more frequently. But over the many
difficult decisions of the day, as their cognitive burden was building up,
they opted for the simpler, default decision of not granting parole.
I think that PhD students (a slightly different sort of prisoner)
instinctively understand this mechanism, which is why they often bring
doughnuts, muffins, and cookies to their dissertation proposals and
defenses. Based on the results of the parole study, it is likely that their
judges are more likely to grant them academic parole and let them
start their own independent lives.
Testing the Moral Muscle
In the TV series Sex and the City, Samantha Jones (the blondest and most
salacious one, for those not in the know) finds herself in a committed
relationship. She begins eating compulsively and consequently gains weight.
What’s interesting is the reason behind this baffling behavior. Samantha notices
that her eating compulsion started when a good-looking man moved in next door
—just the kind of man she would have gone after when she was single. She
realizes that she’s using food as a bulwark against temptation: “I eat so I don’t
cheat,” she explains to her friends. Fictional Samantha is depleted, just like a real
person. She can’t resist all temptation, so she compromises by falling for food
instead of promiscuity.
Sex and the City is no cinematic or psychological masterpiece, but it poses
an interesting question: Might people who overtax themselves in one domain
end up being less moral in others? Does depletion lead us to cheat? That is what
Nicole Mead (a professor at Católica-Lisbon), Roy Baumeister, Francesca Gino,
Maurice Schweitzer (a professor at the University of Pennsylvania), and I
decided to check out. What would happen to real-life Samanthas who were
depleted by one task and then given an opportunity to cheat on another? Would
they cheat more? Less? Would they predict that they are more likely to succumb
to temptation and therefore try to avoid the tempting situation altogether?
Our first experiment included several steps. First, we split our participants
into two groups. We asked one group to write a short essay about what they had
done the previous day without using the letters “x” and “z.” To get a feeling for
this task, try it yourself: In the space below, write a short synopsis of one of your
favorite books, but don’t use the letters “x” and “z.” Note: you cannot simply
omit the letters from the words—you must use words that do not contain an “x”
or “z” (e.g., “bicycle”).
We called this the nondepleting condition because, as you can tell, it’s pretty
easy to write an essay without using the letters “x” and “z.”
We asked the other group to do the same thing but told them not to use the
letters “a” and “n.” To get a better grasp of how this version of the task is
different, try writing a short synopsis of one of your favorite movies while not
using any words that contain the letters “a” and “n.”
As you probably discovered from your experience with the second task,
trying to tell a story without using “a” and “n” required our storytellers to
constantly repress the words that naturally popped into their minds. You can’t
write that the characters “went for a walk in the park” or “ran into each other at a
restaurant.”
All of those little acts of repression add up to greater depletion.
Once our participants turned in their essays, we asked them to perform a
separate task for a different study, which was the main focus of this experiment.
The other task was our standard matrix test.
How did things turn out? In the two control conditions, we found that both
the depleted and nondepleted folks showed an equal ability to solve the math
problems—which means that depletion did not diminish their basic ability to do
the math. But in the two shredder conditions (in which they could cheat), things
went differently. Those who wrote essays without the letters “x” and “z” and
later shredded their answers indulged in a little bit of cheating, claiming to solve
about one extra matrix correctly. But the participants in the shredder condition
who’d undergone the ordeal of writing essays without the letters “a” and “n”
took the proverbial cake: they claimed to have correctly solved about three extra
matrices. As it turned out, the more taxing and depleting the task, the more
participants cheated.
What do these findings suggest? Generally speaking, if you wear down your
willpower, you will have considerably more trouble regulating your desires, and
that difficulty can wear down your honesty as well.
Dead Grannies
Over the course of many years of teaching, I’ve noticed that there typically
seems to be a rash of deaths among students’ relatives at the end of the semester,
and it happens mostly in the week before final exams and before papers are due.
In an average semester, about 10 percent of my students come to me asking for
an extension because someone has died—usually a grandmother. Of course I
find it very sad and am always ready to sympathize with my students and give
them more time to complete their assignments. But the question remains: what is
it about the weeks before finals that is so dangerous to students’ relatives?
Most professors encounter the same puzzling phenomenon, and I’ll guess
that we have come to suspect some kind of causal relationship between exams
and sudden deaths among grandmothers. In fact, one intrepid researcher has
successfully proven it. After collecting data over several years, Mike Adams (a
professor of biology at Eastern Connecticut State University) has shown that
grandmothers are ten times more likely to die before a midterm and nineteen
times more likely to die before a final exam. Moreover, grandmothers of
students who aren’t doing so well in class are at even higher risk—students who
are failing are fifty times more likely to lose a grandmother compared with nonfailing students.
In a paper exploring this sad connection, Adams speculates that the
phenomenon is due to intrafamilial dynamics, which is to say, students’
grandmothers care so much about their grandchildren that they worry themselves
to death over the outcome of exams. This would indeed explain why fatalities
occur more frequently as the stakes rise, especially in cases where a student’s
academic future is in peril. With this finding in mind, it is rather clear that from a
public policy perspective, grandmothers—particularly those of failing students—
should be closely monitored for signs of ill health during the weeks before and
during finals. Another recommendation is that their grandchildren, again
particularly the ones who are not doing well in class, should not tell their
grandmothers anything about the timing of the exams or how they are
performing in class.
Though it is likely that intrafamilial dynamics cause this tragic turn of
events, there is another possible explanation for the plague that seems to strike
grandmothers twice a year. It may have something to do with students’ lack of
preparation and their subsequent scramble to buy more time than with any real
threat to the safety of those dear old women. If that is the case, we might want to
ask why it is that students become so susceptible to “losing” their grandmothers
(in e-mails to professors) at semesters’ end.
Perhaps at the end of the semester, the students become so depleted by the
months of studying and burning the candle at both ends that they lose some of
their morality and in the process also show disregard for their grandmothers’
lives. If the concentration it takes to remember a longer digit can send people
running for chocolate cake, it’s not hard to imagine how dealing with months of
cumulative material from several classes might lead students to fake a dead
grandmother in order to ease the pressure (not that that’s an excuse for lying to
one’s professors).
Just the same, to all grandmothers out there: take care of yourselves at finals
time.
Red, Green, and Blue
We’ve learned that depletion takes away some of our reasoning powers and with
them our ability to act morally.
Still, in real life we can choose to remove ourselves from situations that
might tempt us to behave immorally. If we are even somewhat aware of our
propensity to act dishonestly when depleted, we can take this into account and
avoid temptation altogether. (For example, in the domain of dieting, avoiding
temptation could mean that we decide not to shop for groceries when we’re
starving.)
In our next experiment, our participants could choose whether or not to put
themselves into a position that would tempt them to cheat in the first place. Once
again, we wanted to create two groups: one depleted, the other not. This time,
however, we used a different method of mental exhaustion called the Stroop
task.
In this task, we presented participants with a table of color names containing
five columns and fifteen rows (for a total of seventy-five words). The words in
the table were color names—red, green, and blue—printed in one of these three
colors and organized in no particular order. Once the list was in front of the
participants, we asked them to say the color of each word on the list aloud. Their
instructions were simple: “If a word is written in red ink, regardless of what the
word is, you should say ‘red.’ If a word is written in green ink, regardless of
what the word is, you should say ‘green.’ And so on. Do this as fast as you can.
If at any point you make a mistake, please repeat the word until you get it right.”
For the participants in the nondepleting condition, the list of colors was
structured such that the name of each color (e.g., green) was written in the same
color of ink (green). The participants in the depleting condition were given the
same instructions, but the list of words had one key difference—the ink color did
not match the name of the color (for instance, the word “blue” would be printed
in green ink, and the participants were asked to say “green”).
To try the nondepleting condition of this experiment yourself, time how long
it takes you to say the colors of all the words in the “Congruent Color Words”
list*. When you are done, try the depleting condition by timing how long it takes
you to say aloud the colors of all the words in the “Incongruent Color Words”
list.
How long did these two tasks take you? If you are like most of our
participants, reading the congruent list (the nondepleting condition) probably
took around sixty seconds, but reading the incongruent list (the depleting
condition) was probably three to four times more difficult and more timeconsuming.
Somewhat ironically, the difficulty of naming the colors in the mismatched
list stems from our skill as readers. For experienced readers, the meaning of the
words we read comes to mind very quickly, creating an almost automatic
reaction to say the corresponding word rather than the color of the ink. We see
the green-colored word “red” and want to say “red!” But that is not what we are
supposed to do in this task, so with some effort we suppress our initial response
and instead name the color of the ink. You may also have noticed that as you
keep at this task, you experience a sort of mental exhaustion resulting from the
repeated suppression of your quick automatic responses in favor of the more
controlled, effortful (and correct) responses.
After completing either the easy or the hard Stroop task, each participant
was given the opportunity to take a multiple-choice quiz about the history of
Florida State University. The test included questions such as “When was the
school founded?” and “How many times did the football team play in the
National Championship game between 1993 and 2001?” In total, the quiz
included fifty questions, each with four possible answers, and participants were
paid according to their performances. The participants were also told that once
they finished answering all the questions, they would be given a bubble sheet so
that they could transfer their answers from the quiz to the sheet, recycle the quiz
itself, and submit only the bubble sheet for payment.
Imagine that you are a student in the condition with the opportunity to cheat.
You have just finished the Stroop task (either the depleting or nondepleting
version). You have been answering the quiz questions for the past few minutes,
and the time allotted for the quiz is up. You walk up to the experimenter to pick
up the bubble sheet so that you can dutifully transfer your answers.
“I’m sorry,” the experimenter says, pursing her lips in self-annoyance. “I’m
almost out of bubble sheets! I only have one unmarked one, and one that has the
answers premarked.” She tells you that she did her best to erase the marks on the
used bubble sheet but the answers are still slightly visible. Annoyed with herself,
she admits that she had hoped to administer one more test today after yours. She
next turns to you and asks you a question: “Since you are the first among the last
two participants of the day, you can choose which form you would like to use:
the clean one or the premarked one.”
Of course you realize that taking the premarked bubble sheet would give you
an edge if you decided to cheat. Do you take it? Maybe you take the premarked
one out of altruism: you want to help the experimenter so that she won’t worry
so much about it. Maybe you take the premarked one to cheat. Or maybe you
think that taking the premarked one would tempt you to cheat, so you reject it
because you want to be an honest, upstanding, moral person. Whichever you
take, you transfer your answers to that bubble sheet, shred the original quiz, and
give the bubble sheet back to the experimenter, who pays you accordingly.
Did the depleted participants recuse themselves from the tempting situation
more often, or did they gravitate toward it? As it turned out, they were more
likely than nondepleted participants to choose the sheet that tempted them to
cheat. As a result of their depletion, they suffered a double whammy: they
picked the premarked bubble sheet more frequently, and (as we saw in the
previous experiment) they also cheated more when cheating was possible. When
we looked at these two ways of cheating combined, we found that we paid the
depleted participants 197 percent more than those who were not depleted.
Depletion in Everyday Life
Imagine you’re on a protein-and-vegetable diet and you go grocery shopping at
the end of the day. You enter the supermarket, vaguely hungry, and detect the
smell of warm bread wafting from the bakery. You see fresh pineapple on sale;
although you adore it, it is off limits. You wheel your cart to the meat counter to
buy some chicken. The crab cakes look good, but they have too many
carbohydrates so you pass them by, too. You pick up lettuce and tomatoes for a
salad, steeling yourself against the cheesy garlic croutons. You make it to the
checkout counter and pay for your goods. You feel very good about yourself and
your ability to resist temptation. Then, as you are safely out of the store and on
the way to your car, you pass a school bake sale, and a cute little girl offers you a
free brownie sample.
Now that you know what you know about depletion, you can predict what
your past heroic attempts of resisting temptation may cause you to do: you will
most likely give in and take a bite. Having tasted the delicious chocolate melting
over your deprived taste buds, you can’t possibly walk away. You’re dying for
more. So you buy enough brownies for a family of eight and end up eating half
of them before you even get home.
NOW THINK ABOUT shopping malls. Say you need a new pair of walking shoes.
As you make your way from Neiman Marcus to Sears across a vast expanse of
gleaming commercial temptation, you see all kinds of things you want but don’t
necessarily need. There’s that new grill set you’ve been drooling over, that fauxshearling coat for next winter, and the gold necklace for the party you will most
likely attend on New Year’s Eve. Every enticing item you pass in the window
and don’t buy is a crushed impulse, slowly whittling away at your reserve of
willpower—making it much more likely that later in the day you will fall for
temptation.
Being human and susceptible to temptation, we all suffer in this regard.
When we make complex decisions throughout the day (and most decisions are
more complex and taxing than naming the colors of mismatched words), we
repeatedly find ourselves in circumstances that create a tug-of-war between
impulse and reason. And when it comes to important decisions (health, marriage,
and so on), we experience an even stronger struggle. Ironically, simple, everyday
attempts to keep our impulses under control weaken our supply of self-control,
thus making us more susceptible to temptation.
NOW THAT YOU know about the effects of depletion, how can you best confront
life’s many temptations? Here’s one approach suggested by my friend Dan
Silverman, an economist at the University of Michigan who was facing grave
temptation on a daily basis.
Dan and I were colleagues at the Institute for Advanced Study at Princeton.
The Institute is a lovely place for lucky researchers who can take a year off to do
little else besides think, go for walks in the woods, and eat well. Every day, after
we’d spent our mornings pondering life, science, art, and the reason for it all, we
enjoyed a delectable lunch: say, duck breast served with polenta and glazed
mushroom caps. Each lunch menu was accompanied by a wonderful dessert: ice
cream, crème brûlée, New York cheesecake, triple chocolate cake with
raspberry-crème filling. It was torturous, particularly for poor Dan, who had a
powerful sweet tooth. Being a smart, rational, cholesterolically challenged
economist, Dan wanted dessert, but he also understood that eating dessert daily
is not advisable.
Dan thought about his problem for a while and concluded that when faced
with temptation, a rational person should sometimes succumb. Why? Because by
doing so, the rational person can keep him- or herself from becoming too
depleted, remaining strong for whatever temptations the future may bring. So for
Dan, who was very careful and concerned about future temptations, it was
always carpe diem when it came to the daily dessert. And yes, along with Emre
Ozdenoren and Steve Salant, Dan wrote an academic paper justifying this
approach.
ON A MORE serious note, these experiments with depletion suggest that, in
general, we would be well served to realize that we are continually tempted
throughout the day and that our ability to fight this temptation weakens with
time and accumulated resistance. If we’re really serious about losing weight, we
should get rid of temptation by clearing our shelves and refrigerator of all the
sugary, salty, fatty, and processed foods and acclimating to the taste of fresh
produce. We should do this not only because we know that fried chicken and
cake are bad for us but also because we know that exposing ourselves to such
temptations throughout the day (and every time we open a cupboard or the
refrigerator) makes it more difficult for us to fight off this and other temptations
throughout the day.
Understanding depletion also means that (to the extent that we can) we
should face the situations that require self-control—a particularly tedious
assignment at work, for example—early in the day, before we are too depleted.
This, of course, is not easy advice to follow because the commercial forces
around us (bars, online shopping, Facebook, YouTube, online computer games,
and so on) thrive on both temptation and depletion, which is why they are so
successful.
Granted, we cannot avoid being exposed to all threats to our self-control. So
is there any hope for us? Here’s one suggestion: once we realize that it is very
hard to turn away when we face temptation, we can recognize that a better
strategy is to walk away from the draw of desire before we are close enough to
be snagged by it. Accepting this advice might not be easy, but the reality is that
it is much easier to avoid temptation altogether rather than to overcome it when
it sits lingering on the kitchen counter. And if we can’t quite do that, we can
always try to work on our ability to fight temptation—perhaps by counting to a
hundred, singing a song, or making an action plan and sticking to it. Doing any
of these can help us build our arsenal of tricks for overcoming temptation so that
we are better equipped to fight those urges in the future.
FINALLY, I SHOULD point out that sometimes depletion can be beneficial.
Occasionally, we may feel that we are too much in control, dealing with too
many restrictions, and that we’re not sufficiently free to follow our impulses.
Perhaps sometimes, we just need to stop being responsible adults and let loose.
So here’s a tip: next time you really want to let it all hang out and indulge your
primal self, try depleting yourself first by writing a long autobiographical essay
without using the letters “a” and “n.” Then go to a mall, try on different things,
but buy nothing. Afterward, with all of this depletion weighing on you, place
yourself in the tempting situation of your choice and let ’er rip. Just don’t use
this trick too often.
AND IF YOU really need a more official-sounding excuse to succumb to
temptation from time to time, just use Dan Silverman’s theory of rational selfindulgence as the ultimate license.
CHAPTER 5
Why Wearing Fakes Makes Us Cheat More
Let me tell you the story of my debut into the world of fashion. When Jennifer
Wideman Green (a friend of mine from graduate school) ended up living in New
York City, she met a number of people in the fashion industry. Through her I
met Freeda Fawal-Farah, who worked for Harper’s Bazaar, a gold standard in
the fashion industry. A few months later Freeda invited me to give a talk at the
magazine, and because it was such an atypical crowd for me, I agreed.
Before I started my talk, Freeda treated me to a quick fashion tutorial as we
sipped our lattes in a balcony café overlooking the escalator in the big downtown
Manhattan building. Freeda gave me a rundown of the outfits worn by every
woman who passed us, including the brands they were wearing and what her
clothes and shoes said about her lifestyle. I found her attention to every detail—
indeed, the whole fashion analysis—fascinating, the way I imagine expert bird
watchers are able to discern minute differences between species.
About thirty minutes later, I found myself on a stage before an auditorium
full of fashion mavens. It was a tremendous pleasure to be surrounded by so
many attractive and well-dressed women. Each woman was like an exhibit in a
museum: her jewelry, her makeup, and, of course, her stunning shoes. Thanks to
Freeda’s tutorial, I was able to recognize a few of the brands when I looked out
into the rows. I could even discern the sense of fashion that inspired each
ensemble.
I wasn’t sure why those fashionistas wanted me there or what they expected
to hear from me. Still, we seemed to have good chemistry. I talked about how
people make decisions, how we compare prices when we are trying to figure out
how much something is worth, how we compare ourselves to others, and so on.
They laughed when I hoped they would, asked thoughtful questions, and offered
plenty of their own interesting ideas. When I finished the talk, Valerie
Salembier, the publisher of Harper’s Bazaar, came onstage, hugged and thanked
me—and gave me a stylish black Prada overnight bag.
AFTER SAYING OUR good-byes, I left the building with my new Prada bag and
headed downtown to my next meeting. I had some time to kill, so I decided to
take a walk. As I wandered, I couldn’t help thinking about my big black leather
bag with its large Prada logo displayed. I debated with myself: should I carry my
new bag with the logo facing outward? That way, other people could see and
admire it (or maybe just wonder how someone wearing jeans and red sneakers
could possibly have procured it). Or should I carry it with the logo facing toward
me, so that no one could recognize that it was a Prada? I decided on the latter
and turned the bag around.
Even though I was pretty sure that with the logo hidden no one realized it
was a Prada bag, and despite the fact that I don’t think of myself as someone
who cares about fashion, something felt different to me. I was continuously
aware of the brand on the bag. I was wearing Prada! And it made me feel
different; I stood a little straighter and walked with a bit more swagger. I
wondered what would happen if I wore Ferrari underwear. Would I feel more
invigorated? More confident? More agile? Faster?
I continued walking and passed through Chinatown, which was bustling with
activity, food, smells, and street vendors selling their wares along Canal Street.
Not far away, I spotted an attractive young couple in their twenties taking in the
scene. A Chinese man approached them. “Handbags, handbags!” he called,
tilting his head to indicate the direction of his small shop. At first they didn’t
react. Then, after a moment or two, the woman asked the Chinese man, “You
have Prada?”
The vendor nodded. I watched as she conferred with her partner. He smiled
at her, and they followed the man to his stand.
The Prada they were referring to, of course, was not actually Prada. Nor
were the $5 “designer” sunglasses on display in his stand really
Dolce&Gabbana. And the Armani perfumes displayed over by the street food
stands? Fakes too.
*
From Ermine to Armani
Let’s pause for a moment and consider the history of wardrobes, thinking
specifically about something social scientists call external signaling, which is
simply the way we broadcast to others who we are by what we wear. Going back
a way, ancient Roman law included a set of regulations called sumptuary laws,
which filtered down through the centuries into the laws of nearly all European
nations. Among other things, the laws dictated who could wear what, according
to their station and class. The laws went into an extraordinary level of detail. For
example, in Renaissance England, only the nobility could wear certain kinds of
fur, fabrics, laces, decorative beading per square foot, and so on, while those in
the gentry could wear decisively less appealing clothing. (The poorest were
generally excluded from the law, as there was little point in regulating musty
burlap, wool, and hair shirts.)
Some groups were further differentiated so as not to be confused with
“respectable” people. For instance, prostitutes had to wear striped hoods to
signal their “impurity,” and heretics were sometimes forced to don patches
decorated with wood bundles to indicate that they could or should be burned at
the stake. In a sense, a prostitute going out without her mandatory striped hood
was in disguise, like someone wearing a pair of fake Gucci sunglasses. A solid,
nonstriped hood sent a false signal of the woman’s livelihood and economic
status. People who “dressed above their station” were silently, but directly, lying
to those around them. Although dressing above one’s station was not a capital
offense, those who broke the law were often hit with fines and other
punishments.
What may seem to be an absurd degree of obsessive compulsion on the part
of the upper crust was in reality an effort to ensure that people were what they
signaled themselves to be; the system was designed to eliminate disorder and
confusion. (It clearly had some signaling advantages, though I am not suggesting
that we revert back to it.) Although our current sartorial class system is not as
rigid as it was in the past, the desire to signal success and individuality is as
strong today as ever. The fashionably privileged now wear Armani instead of
ermine. And just as Freeda knew that Via Spiga platform heels weren’t for
everyone, the signals we send are undeniably informative to those around us.
NOW, YOU MIGHT think that the people who buy knockoffs don’t actually hurt the
fashion manufacturer because many of them would never buy the real thing to
start with. But that is where the effect of external signaling comes in. After all, if
a bunch of people buy knockoff Burberry scarves for $10, others—the few who
can afford the real thing and want to buy it—might not be willing to pay twenty
times more for the authentic scarves. If it is the case that when we see a person
wearing a signature Burberry plaid or carrying a Louis Vuitton LV-patterned
bag, we immediately suspect that it is a fake, then what is the signaling value in
buying the authentic version? This perspective means that the people who
purchase knockoffs dilute the potency of external signaling and undermine the
authenticity of the real product (and its wearer). And that is one reason why
fashion retailers and fashionistas care so much about counterfeits.
WHEN THINKING ABOUT my experience with the Prada bag, I wondered whether
there were other psychological forces related to fakes that go beyond external
signaling. There I was in Chinatown holding my real Prada bag, watching the
woman emerge from the shop holding her fake one. Despite the fact that I had
neither picked out nor paid for mine, it felt to me that there was a substantial
difference between the way I related to my bag and the way she related to hers.
More generally, I started wondering about the relationship between what we
wear and how we behave, and it made me think about a concept that social
scientists call self-signaling. The basic idea behind self-signaling is that despite
what we tend to think, we don’t have a very clear notion of who we are. We
generally believe that we have a privileged view of our own preferences and
character, but in reality we don’t know ourselves that well (and definitely not as
well as we think we do). Instead, we observe ourselves in the same way we
observe and judge the actions of other people—inferring who we are and what
we like from our actions.
For example, imagine that you see a beggar on the street. Rather than
ignoring him or giving him money, you decide to buy him a sandwich. The
action in itself does not define who you are, your morality, or your character, but
you interpret the deed as evidence of your compassionate and charitable
character. Now, armed with this “new” information, you start believing more
intensely in your own benevolence. That’s self-signaling at work.
The same principle could also apply to fashion accessories. Carrying a real
Prada bag—even if no one else knows it is real—could make us think and act a
little differently than if we were carrying a counterfeit one. Which brings us to
the questions: Does wearing counterfeit products somehow make us feel less
legitimate? Is it possible that accessorizing with fakes might affect us in
unexpected and negative ways?
Calling All Chloés
I decided to call Freeda and tell her about my recent interest in high fashion. (I
think she was even more surprised than I was.) During our conversation, Freeda
promised to convince a fashion designer to lend me some items to use in some
experiments. A few weeks later, I received a package from the Chloé label
containing twenty handbags and twenty pairs of sunglasses. The statement
accompanying the package told me that the handbags were estimated to be worth
around $40,000 and the sunglasses around $7,000.
*
With those hot commodities in hand, Francesca Gino, Mike Norton (a
professor at Harvard University), and I set about testing whether participants
who wore fake products would feel and behave differently from those wearing
authentic ones. If our participants felt that wearing fakes would broadcast (even
to themselves) a less honorable self-image, we wondered whether they might
start thinking of themselves as somewhat less honest. And with this tainted selfconcept in mind, would they be more likely to continue down the road of
dishonesty?
Using the lure of Chloé accessories, we enlisted many female MBA students
for our experiment. (We focused on women not because we thought that they
were different from men in any moral way—in fact, in all of our previous
experiments we did not find any sex-related differences—but because the
accessories we had were clearly designed for women.) We wondered whether to
use the sunglasses or the handbags in our first experiments, but when we realized
that it would have been a bit more difficult to explain why we wanted our
participants to walk around the building with handbags, we settled on the
sunglasses.
AT THE START of the experiment, we assigned each woman to one of three
conditions: authentic, fake, or no information. In the authentic condition, we told
participants that they would be donning real Chloé designer sunglasses. In the
fake condition, we told them that they would be wearing counterfeit sunglasses
that looked identical to those made by Chloé (in actuality all the products we
used were the real McCoy). Finally, in the no-information condition, we didn’t
say anything about the authenticity of the sunglasses.
Once the women donned their sunglasses, we directed them to the hallway,
where we asked them to look at different posters and out the windows so that
they could later evaluate the quality and experience of looking through their
sunglasses. Soon after, we called them into another room for another task. What
was the task? You guessed it: while the women were still wearing their
sunglasses we gave them our old friend, the matrix task.
Now imagine yourself as a participant in this study. You show up to the lab,
and you’re randomly assigned to the fake condition. The experimenter informs
you that your glasses are counterfeit and instructs you to test them out to see
what you think. You’re handed a rather real-looking case (the logo is spot-on!),
and you pull out the sunglasses, examine them, and slip them on. Once you’ve
put on the specs, you start walking around the hallway, examining different
posters and looking out the windows. But while you are doing so, what is going
through your head? Do you compare the sunglasses to the pair in your car or the
ones you broke the other day? Do you think, “Yeah, these are very convincing.
No one would be able to tell they’re fake.” Maybe you think that the weight
doesn’t feel right or that the plastic seems cheap. And if you do think about the
fakeness of what you are wearing, would it cause you to cheat more on the
matrix test? Less? The same amount?
Here’s what we found. As usual, lots of people cheated by a few questions.
But while “only” 30 percent of the participants in the authentic condition
reported solving more matrices than they actually had, 74 percent of those in the
fake condition reported solving more matrices than they actually had.
These results gave rise to another interesting question. Did the presumed
fakeness of the product make the women cheat more than they naturally would?
Or did the genuine Chloé label make them behave more honestly than they
would otherwise? In other words, which was more powerful: the negative selfsignaling in the fake condition or the positive self-signaling in the authentic
condition?
This is why we also had the no-information (control) condition, in which we
didn’t mention anything about whether the sunglasses were real or fake. How
would the no-information condition help us? Let’s say that women wearing the
fake glasses cheated at the same level as those in the no-information condition. If
that were the case, we could conclude that the counterfeit label did not make the
women any more dishonest than they were naturally and that the genuine label
was causing higher honesty. On the other hand, if we saw that the women
wearing the real Chloé sunglasses cheated at the same level as those in the noinformation condition (and much less than those in the fake-label condition), we
would conclude that the authentic label did not make the women any more
honest than they were naturally and that the fake label was causing women to
behave less honestly.
As you’ll recall, 30 percent of women in the authentic condition and 73
percent of women in the fake-label condition overreported the number of
matrices they solved. And in the no-information condition? In that condition 42
percent of the women cheated. The no-information condition was between the
two, but it was much closer to the authentic condition (in fact, the two conditions
were not statistically different from each other). These results suggest that
wearing a genuine product does not increase our honesty (or at least not by
much). But once we knowingly put on a counterfeit product, moral constraints
loosen to some degree, making it easier for us to take further steps down the path
of dishonesty.
The moral of the story? If you, your friend, or someone you are dating wears
counterfeit products, be careful! Another act of dishonesty may be closer than
you expect.
The “What-the-Hell” Effect
Now let’s pause for a minute to think again about what happens when you go on
a diet. When you start out, you work hard to stick to the diet’s difficult rules:
half a grapefruit, a slice of dry multigrain toast, and a poached egg for breakfast;
turkey slices on salad with zero-calorie dressing for lunch; baked fish and
steamed broccoli for dinner. As we learned in the preceding chapter, “Why We
Blow It When We’re Tired,” you are now honorably and predictably deprived.
Then someone puts a slice of cake in front of you. The moment you give in to
temptation and take that first bite, your perspective shifts. You tell yourself, “Oh,
what the hell, I’ve broken my diet, so why not have the whole slice—along with
that perfectly grilled, mouthwatering cheeseburger with all the trimmings I’ve
been craving all week? I’ll start anew tomorrow, or maybe on Monday. And this
time I’ll really stick to it.” In other words, having already tarnished your dieting
self-concept, you decide to break your diet completely and make the most of
your diet-free self-image (of course you don’t take into account that the same
thing can happen again tomorrow and the day after, and so on).
To examine this foible in more detail, Francesca, Mike, and I wanted to
examine whether failing at one small thing (such as eating one french fry when
you’re supposedly on a diet) can cause one to abandon the effort altogether.
This time, imagine you’re wearing a pair of sunglasses—whether they are
authentic Chloé, a fake pair, or a pair of unspecified authenticity. Next, you sit
down in front of a computer screen where you’re presented with a square
divided into two triangles by a diagonal line. The trial starts, and for one second,
twenty randomly scattered dots flash within the square (see the diagram below).
Then the dots disappear, leaving you with an empty square, the diagonal line,
and two response buttons, one marked “more-on-right” and the other marked
“more-on-left.” Using these two buttons, your task is to indicate whether there
were more dots on the right-hand or left-hand side of the diagonal. You do this
one hundred times. Sometimes the right-hand side clearly has more dots.
Sometimes they are unmistakably concentrated on the left-hand side. Other
times it’s hard to tell. As you can imagine, you get pretty used to the task, as
tedious as it may be, and after a hundred responses the experimenter can tell how
accurately you can make these sorts of judgments.
Next, the computer asks you to repeat the same task two hundred more
times. Only this time, you will be paid according to your decisions. Here’s the
key detail: regardless of whether your responses are accurate or not, every time
you select the left-hand button, you will receive half a cent and every time you
select the right-hand button, you will receive 5 cents (ten times more money).
With this incentive structure, you are occasionally faced with a basic conflict
of interest. Every time you see more dots on the right, there is no ethical problem
because giving the honest answer (more on the right) is the same response that
makes you the most money. But when you see more dots on the left, you have to
decide whether to give the accurate honest answer (more on the left), as you
were instructed, or to maximize your profit by clicking the more-on-right button.
By creating this skewed payment system, we gave the participants an incentive
to see reality in a slightly different way and cheat by excessively clicking the
more-on-right button. In other words, they were faced with a conflict between
producing an accurate answer and maximizing their profit. To cheat or not to
cheat, that was the question. And don’t forget, you’re doing this while still
wearing the sunglasses.
As it turned out, our dots task showed the same general results as the matrix
task, with lots of people cheating but just by a bit. Interestingly, we also saw that
the amount of cheating was especially large for those wearing the fake
sunglasses. What’s more, the counterfeit wearers cheated more across the board.
They cheated more when it was hard to tell which side had more dots, and they
cheated more even when it was clear that the correct answer was more on the left
(the side with the lower financial reward).
Those were the overall results, but the reason we created the dots task in the
first place was to observe how cheating evolves over time in situations where
people have many opportunities to act dishonestly. We were interested in
whether our participants started the experiment by cheating only occasionally,
trying to maintain the belief that they were honest but at the same time
benefitting from some occasional cheating. We suspected that this kind of
balanced cheating could last for a while but that at some point participants might
reach their “honesty threshold.” And once they passed that point, they would
start thinking, “What the hell, as long as I’m a cheater, I might as well get the
most out of it.” And from then on, they would cheat much more frequently—or
even every chance they got.
The first thing that the results revealed was that the amount of cheating
increased as the experiment went on. And as our intuitions had suggested, we
also saw that for many people there was a very sharp transition where at some
point in the experiment, they suddenly graduated from engaging in a little bit of
cheating to cheating at every single opportunity they had. This general pattern of
behavior is what we would expect from the what-the-hell effect, and it surfaced
in both the authentic and the fake conditions. But the wearers of the fake
sunglasses showed a much greater tendency to abandon their moral constraints
and cheat at full throttle.
*
In terms of the what-the-hell effect, we saw that when it comes to cheating,
we behave pretty much the same as we do on diets. Once we start violating our
own standards (say, with cheating on diets or for monetary incentives), we are
much more likely to abandon further attempts to control our behavior—and from
that point on there is a good chance that we will succumb to the temptation to
further misbehave.
IT SEEMS, THEN, that the clothes do make the man (or woman) and that wearing
knockoffs does have an effect on ethical decisions. As is the case with many
findings in social science research, there are ways to use this information for
both good and ill. On the negative side, one can imagine how organizations
could use this principle to loosen the morality of their employees such that they
will find it easier to “fake out” their customers, suppliers, regulators, and
competitors and, by doing so, increase the company’s revenue at the expense of
the other parties. On the positive side, understanding how slippery slopes operate
can direct us to pay more attention to early cases of transgression and help us
apply the brakes before it’s too late.
Up to No Good
Having completed these experiments, Francesca, Mike, and I had evidence that
wearing counterfeits colors the way we view ourselves and that once we are
painted as cheaters in our own eyes, we start behaving in more dishonest ways.
This led us to another question: if wearing counterfeits changes the way we view
our own behavior, does it also cause us to be more suspicious of others?
To find out, we asked another group of participants to put on what we told
them were either real or counterfeit Chloé sunglasses. Again, they dutifully
walked the hall examining different posters and views from the windows.
However, when we called them back to the lab, we did not ask them to perform
our matrix or dots task. Instead, we asked them to fill out a rather long survey
with their sunglasses on. In this survey, we asked a bunch of irrelevant questions
(filler questions) that are meant to obscure the real goal of the study. Among the
filler questions, we included three sets of questions designed to measure how our
respondents interpreted and evaluated the morality of others.
The questions in set A asked participants to estimate the likelihood that
people they know might engage in various ethically questionable behaviors. The
questions in set B asked them to estimate the likelihood that when people say
particular phrases, they are lying. Finally, set C presented participants with two
scenarios depicting someone who has the opportunity to behave dishonestly, and
they were asked to estimate the likelihood that the person in the scenario would
take the opportunity to cheat. Here are the questions from all three sets:
Set A: How likely are people you know to engage in
the following behaviors?
Stand in the express line with too many groceries.
Try to board a plane before their group number is called.
Inflate their business expense report.
Tell their supervisor that progress has been made on a project when none
has been made.
Take home office supplies from work.
Lie to an insurance company about the value of goods that were damaged.
Buy a garment, wear it, and return it.
Lie to their partner about the number of sex partners they have had.
Set B: When the following lines are uttered, how likely
is it that they are a lie?
Sorry I’m late, traffic was terrible.
My GPA is 4.0.
It was good meeting you. Let’s have lunch sometime.
Sure, I’ll start working on that tonight.
Yes, John was with me last night.
I thought I already sent that e-mail out. I am sure I did.
Set C: How likely are these individuals to take the
action described?
Steve is the operations manager of a firm that produces pesticides and
fertilizers for lawns and gardens. A certain toxic chemical is going to be
banned in a year, and for this reason is extremely cheap now. If Steve buys
this chemical and produces and distributes his product fast enough, he will
be able to make a very nice profit. Please estimate the likelihood that Steve
will sell this chemical while it is still legal.
Dale is the operations manager of a firm that produces health foods. One of
their organic fruit beverages has 109 calories per serving. Dale knows that
people are sensitive to crossing the critical threshold of 100 calories. He
could decrease the serving size by 10 percent. The label will then say that
each serving has 98 calories, and the fine print will say that each bottle
contains 2.2 servings. Please estimate the likelihood that Dale will cut the
serving size to avoid crossing the 100-calorie-per-serving threshold.
What were the results? You guessed it. When reflecting on the behavior of
people they know (set A), participants in the counterfeit condition judged their
acquaintances to be more likely to behave dishonestly than did participants in the
authentic condition. They also interpreted the list of common excuses (set B) as
more likely to be lies, and judged the actor in the two scenarios (set C) as being
more likely to choose the shadier option. In the end, we concluded that
counterfeit products not only tend to make us more dishonest; they cause us to
view others as less than honest as well.
Fake It Till You Make It
So what can we do with all of these results?
First, let’s think about high-fashion companies, which have been up in arms
about counterfeits for years. It may be difficult to sympathize with them; you
might think that outside their immediate circle, no one should really care about
the “woes” of high-end designers who cater to the wealthy. When tempted to
buy a fake Prada bag, you might say to yourself, “Well, designer products are
too expensive, and it’s silly to pay for the real thing.” You might say, “I
wouldn’t consider buying the real product anyway, so the designer isn’t really
losing any money.” Or maybe you would say, “Those fashion companies make
so much money that a few people buying fake products won’t really make a
difference.” Whatever rationalizations we come up with—and we are all very
good at rationalizing our actions so that they are in line with our selfish motives
—it’s difficult to find many people who feel that the alarm on the part of highfashion companies is of grave personal concern.
But our results show that there’s another, more insidious story here. High-
fashion companies aren’t the only ones paying a price for counterfeits. Thanks to
self-signaling and the what-the-hell effect, a single act of dishonesty can change
a person’s behavior from that point onward. What’s more, if it’s an act of
dishonesty that comes with a built-in reminder (think about fake sunglasses with
a big “Gucci” stamped on the side), the downstream influence could be longlived and substantial. Ultimately, this means that we all pay a price for
counterfeits in terms of moral currency; “faking it” changes our behavior, our
self-image, and the way we view others around us.
*
Consider, for example, the fact that academic diplomas hang in many
executive suites around the world and decorate even more résumés. A few years
ago, The Wall Street Journal ran a piece on executives who misrepresent their
academic credentials, pointing to top moguls such as Kenneth Keiser, who at the
time was the president and COO of PepsiAmericas, Inc. Though Keiser had
attended Michigan State University, he never graduated; still, for a long time, he
signed off on papers that claimed he had a BA from Michigan State
1
(of course,
it is possible that this was just a misunderstanding).
Or consider the case of Marilee Jones, who coauthored a popular guidebook
called Less Stress, More Success: A New Approach to Guiding Your Teen
Through College Admissions and Beyond, in which, among other things, she
advocated “being yourself” in order to be successful in college admissions and
job searches. She was MIT’s popular dean of admissions, and for twenty-five
years, by all accounts, she did her job very well. There was just one problem: she
had added several fictitious degrees to her résumé to land that job in the first
place. It was an act of cheating, pure and simple. The irony of her fall from grace
was not lost on Jones, who apologized for not “having the courage” to correct
the “mistakes” on her fake résumé at any point during her employment. When an
extremely popular advocate of “being yourself” is toppled by false credentials,
what are the rest of us to think?
If you think about this type of cheating in the context of the “what-the-hell”
effect, it might be that fake academic credentials often start innocently enough,
perhaps along the lines of “fake it till you make it,” but once one such act has
been established, it can bring about a looser moral standard and a higher
tendency to cheat elsewhere. For example, if an executive holding a fake
graduate degree puts constant reminders of his fake degree on his letterhead,
business cards, résumé, and website, it’s not much of a stretch to imagine that he
could also start cheating on expense reports, misrepresenting billable hours, or
misusing corporate funds. After all, given the what-the-hell effect, it is possible
that one initial act of cheating could increase the executive’s general level of
self-signaled dishonesty, increasing his fudge factor, which would give rise to
further fraud.
THE BOTTOM LINE is that we should not view a single act of dishonesty as just
one petty act. We tend to forgive people for their first offense with the idea that
it is just the first time and everyone makes mistakes. And although this may be
true, we should also realize that the first act of dishonesty might be particularly
important in shaping the way a person looks at himself and his actions from that
point on—and because of that, the first dishonest act is the most important one to
prevent. That is why it is important to cut down on the number of seemingly
innocuous singular acts of dishonesty. If we do, society might become more
honest and less corrupt over time (for more on this, see chapter 8, “Cheating as
an Infection”).
(DON’T) STEAL THIS BOOK
Finally, no discussion of designer counterfeits could be complete
without mentioning their cousin, illegal downloading. (Imagine
experiments similar to the ones on fake sunglasses but using illegally
downloaded music or movies.) Allow me to share a story about a time
when I learned something interesting about illegal downloads. In this
particular case, I was the victim. A few months after Predictably
Irrational was published, I received the following e-mail:
Dear Mr. Ariely,
I just finished listening to the illegally downloaded version of your
audio book this morning, and I wanted to tell you how much I
appreciated it.
I am a 30-year-old African American male from the inner city of
Chicago, and for the last five years, I have been making my living by
illegally selling CDs and DVDs. I am the only person in my family who is
not in prison or homeless. As the last survivor of a family that represents
all that is wrong with America, and as someone breaking the law today, I
know it is only a matter of time before I join my family in prison.
Some time ago I got a 9-to-5 job, and was excited at the idea of
starting a respectable life, but soon after I started, I quit and went back to
my illegal business. This is because of the pain I felt at giving up my
illegal business that I had built and nurtured for five years. I owned it,
and I couldn’t find a job that gave me the same feeling of ownership.
Needless to say, I could really relate to your research on ownership.
But something else was equally important in pushing me back to the
illegal retail business. In the legal retail store where I worked, people
often talked about loyalty and care for their customers, but I don’t think
they understood what this means. In the illegal industry, loyalty and care
are much stronger and more intense than anything I encountered in legal
retail. Over the years I have built a network of about 100 people who
kindly buy from me. We have become real friends with real connections
and developed a level of deep care for one another. These connections
and friendships with my clients made it very hard for me to give up the
business and their friendship in the process.
I’m happy that I listened to your book.
Elijah
After receiving this e-mail from Elijah, I searched the Internet and
found a few free downloadable versions of my audiobook and a few
scanned copies of the printed version (which, I have to admit, were
high-quality scans, including the front and back covers, all the credits
and references, and even the copyright notices, which I particularly
appreciated).
No matter where you stand on the “information wants to be free”
ideological spectrum, seeing your own work distributed for free
without permission makes the whole issue of illegal downloads feel a bit
more personal, less abstract, and more complex. On the one hand, I’m
very happy that people are reading about my research and hopefully
benefitting from it. The more the merrier—after all, that is why I
write. On the other hand, I also understand the annoyance of those
whose work is being illegally copied and sold. Thankfully I have a day
job, but I am certain that if I were to rely on writing as my main source
of income, illegal downloads would be less of an intellectual curiosity
and much more difficult to swallow.
As for Elijah, I think we made a fair exchange. Sure, he illegally
copied my audiobook (and made some money in the process), but I
learned something interesting about loyalty and care for customers in
the illegal industry and even got an idea for possible future research.
WITH ALL OF this in mind, how can we fight our own moral deterioration, the
what-the-hell effect, and the potential of one transgressive act to result in longterm negative effects on our morality? Whether we deal with fashion or other
domains of life, it should be clear that one immoral act can make another more
likely and that immoral acts in one domain can influence our morality in other
domains. That being the case, we should focus on early signs of dishonest
behaviors and do our best to cut them down in their budding stages before they
reach full bloom.
AND WHAT ABOUT the Prada bag that started this whole research project? I made
the only possible rational decision: I gave it to my mother.
CHAPTER 6
Cheating Ourselves
Imagine yourself on a soft, sandy beach. The tide is rolling out, creating a wide
swath of wet sand for you to wander along. You’re heading to the place where
you go from time to time to check out girls. Oh, and you’re a feisty blue crab.
And in reality, you’re going to spar with a few other male crabs to see who will
win the favor of the females.
Ahead you see a pretty little thing with cute claws. At the same time, you
notice that your competition is quickly closing in. You know that the ideal way
to handle the situation is to scare off the other crabs. That way you don’t have to
get into a fight and risk hurting yourself or, worse, lose your chance to mate. So
you have to convince the other crabs that you’re bigger and stronger. As you
inch closer to your competition, you know you need to emphasize your size.
However, if you simply pretend to be larger by standing on your toes and
halfheartedly waving your claws around, you will probably give yourself away.
What to do?
What you need to do is give yourself a pep talk and start believing that you
are, in fact, bigger and tougher than you really are. “Knowing” you’re the
biggest crab on the beach, you stand as high as you can on your hind legs and
spread your claws as far and high above you as possible (antlers, peacock tails,
and general puffing up help other male creatures do the same thing). Believing in
your own fabrication means that you will not flinch. And your (exaggerated)
self-confidence might cow your opponents.
NOW BACK TO us. As humans, we have slightly more sophisticated means of
puffing ourselves up than our animal counterparts. We have the ability to lie—
not just to others but also to ourselves. Self-deception is a useful strategy for
believing the stories we tell, and if we are successful, it becomes less likely that
we will flinch and accidentally signal that we’re anything other than what we
pretend to be. I’m hardly endorsing lying as a means of attaining a partner, a job,
or anything else. But in this chapter, we’ll look at the ways we succeed in
fooling ourselves as we try to fool others.
Of course, we can’t instantly believe every one of our lies. For instance, let’s
say you’re a guy at a speed-dating event and you’re trying to impress an
attractive woman. A wild idea enters your mind: you tell her that you have a
pilot’s license. Even if you sold her this story, it’s unlikely you will convince
yourself that you do, in fact, have such a license and start suggesting to the pilots
on your next flight how to improve their landings. On the other hand, let’s say
you go out running with your buddy and you get into a discussion about best
running times. You tell your friend that you’ve run a mile in under seven
minutes, when in reality your best time was a tiny bit over seven minutes. A few
days later, you tell someone else the same thing. After repeating this slightly
exaggerated claim over and over, you could eventually forget that you hadn’t
actually broken the seven-minute mark. You may come to believe it to such a
degree that you might even be willing to bet money on it.
ALLOW ME TO tell you a story of a time when I embraced my own deception. In
the summer of 1989—about two years after I left the hospital—my friend Ken
and I decided to fly from New York to London to see another friend. We bought
the cheapest flight to London, which happened to be on Air India. When the taxi
dropped us off at the airport, we were dismayed to see a line of people trailing
all the way out of the terminal. Thinking fast, Ken came up with an idea: “Why
don’t we put you in a wheelchair?” I thought about his suggestion. Not only
would I be more comfortable, but we could also get through much faster.
(Truthfully speaking, it is difficult for me to stand for a prolonged time because
the circulation in my legs is far from good. But I don’t need a wheelchair.)
We were both convinced that it was a good plan, so Ken jumped out of the
cab and returned with the wheelchair. We breezed through check-in and, with an
extra two hours to kill, we enjoyed coffee and a sandwich. But then I needed to
use the restroom. So Ken pushed me in the wheelchair to the nearest bathroom,
which unfortunately was not designed to accommodate a wheelchair. I
maintained my role, though; we got the wheelchair as close to the toilet as
possible and I tried to hit the mark from a distance, with limited success.
Once we made it through the bathroom challenge, it was time to board the
plane. Our seats were in row 30, and as we neared the entrance to the plane, I
realized that the wheelchair was going to be too wide for the aisle. So we did
what my new role dictated: I left the wheelchair at the entrance of the plane,
grabbed on to Ken’s shoulders, and he hauled me to our seats.
As I sat waiting for the flight to take off, I was annoyed that the bathroom in
the airport wasn’t handicap-accessible and that the airline hadn’t provided me
with a narrower wheelchair to get to my seat. My irritation increased when I
realized that I shouldn’t drink anything on the six-hour flight because there
would be no way for me to keep up the act and use the bathroom. The next
difficulty arose when we landed in London. Once again, Ken had to carry me to
the entrance of the plane, and when the airline didn’t have a wheelchair waiting
for us, we had to wait.
This little adventure made me appreciate the daily irritations of handicapped
people in general. In fact, I was so annoyed that I decided to go and complain to
the head of Air India in London. Once we got the wheelchair, Ken rolled me to
Air India’s office, and with an overblown air of indignation I described each
difficulty and humiliation and reprimanded the regional head of Air India for the
airline’s lack of concern for disabled people everywhere. Of course he
apologized profusely, and after that we rolled away.
The odd thing is that throughout the process I knew I could walk, but I
adopted my role so quickly and thoroughly that my self-righteousness felt as real
as if I had a legitimate reason to be upset. Then after all that, we got to the
baggage claim, where I simply picked up my backpack and walked away unhampered, like Keyser Söze in the film The Usual Suspects.
TO MORE SERIOUSLY examine self-deception, Zoë Chance (a postdoc at Yale),
Mike Norton, Francesca Gino, and I set out to learn more about how and when
we deceive ourselves into believing our own lies and whether there are ways to
prevent ourselves from doing so.
In the first phase of our exploration, participants took an eight-question IQlike test (one of the questions, for example, was this: “What is the number that is
one half of one quarter of one tenth of 400?”). After they finished taking the
quiz, participants in the control group handed their answers over to the
experimenter who checked their responses. This allowed us to establish the
average performance on the test.
*
In the condition where cheating was possible, participants had an answer key
at the bottom of the page. They were told that the answer key was there so that
they could score how well they did on the test and also to help them estimate in
general how good they were at answering these types of questions. However,
they were told to answer the questions first and only then use the key for
verification. After answering all the questions, participants checked their own
answers and reported their own performance.
What did the results from phase one of the study show? As we expected, the
group that had the opportunity to “check their answers” scored a few points
higher on average, which suggested that they had used the answer key not only
to score themselves but also to improve their performance. As was the case with
all of our other experiments, we found that people cheat when they have a
chance to do so, but not by a whole lot.
Helping Myself to a Higher MENSA Score
The inspiration for this experimental setup came from one of those
complimentary magazines that you find in seat-back pockets on airplanes. On
one particular flight, I was flipping through a magazine and discovered a
MENSA quiz (questions that are supposed to measure intelligence). Since I am
rather competitive, I naturally had to try it. The directions said that the answers
were in the back of the magazine. After I answered the first question, I flipped to
the back to see if I was correct, and lo and behold, I was. But as I continued with
the quiz, I also noticed that as I was checking the answer to the question I just
finished solving, my eyes strayed just a bit to the next answer. Having glanced at
the answer to the next question, I found the next problem to be much easier. At
the end of the quiz, I was able to correctly solve most of the questions, which
made it easier for me to believe that I was some sort of genius. But then I had to
wonder whether my score was that high because I was supersmart or because I
had seen the answers out of the corner of my eye (my inclination was, of course,
to attribute it to my own intelligence).
The same basic process can take place in any test in which the answers are
available on another page or are written upside down, as they often are in
magazines and SAT study guides. We often use the answers when we practice
taking tests to convince ourselves that we’re smart or, if we get an answer
wrong, that we’ve made a silly mistake that we would never make during a real
exam. Either way, we come away with an inflated idea of how bright we actually
are—and that’s something we’re generally happy to accept.
THE RESULTS FROM phase one of our experiments showed that participants
tended to look ahead at the answers as a way to improve their score. But this
finding did not tell us whether they engaged in straight-up old-fashioned
cheating or if they were actually deceiving themselves. In other words, we didn’t
yet know if the participants knew they were cheating or if they convinced
themselves that they legitimately knew the correct answers all along. To figure
this out, we added another component to our next experiment.
Imagine that you are taking part in an experiment similar to the previous
one. You took the eight-question quiz and answered four questions correctly (50
percent), but thanks to the answers at the bottom of the page, you claimed that
you had solved six correctly (75 percent). Now, do you think that your actual
ability is in the 50 percent range, or do you think it is in the 75 percent range?
On the one hand, you may be aware that you used the answer key to inflate your
score, and realize that your real ability is closer to the 50 percent mark. On the
other hand, knowing that you were paid as if you really had solved six problems,
you might be able to convince yourself that your ability to solve such questions
is in reality closer to the 75 percent level.
This is where phase two of the experiment comes in. After finishing the
math quiz, the experimenter asks you to predict how well you will do on the next
test, in which you will be asked to answer a hundred questions of a similar
nature. This time, it’s clear that there are not going to be any answers at the
bottom of the page (and therefore no chance to consult the key). What do you
predict your performance will be on the next quiz? Will it be based on your real
ability in the first phase (50 percent), or will it be based on your exaggerated
ability (75 percent)? Here is the logic: if you are aware that you used the answer
key in the previous test to artificially inflate your score, you would predict that
you would correctly solve the same proportion of questions as you solved
unassisted in the first test (four out of eight, or around 50 percent). But let’s say
you started believing that you really did answer six questions correctly on your
own and not because you looked at the answers. Now you might predict that in
this next test, too, you would correctly solve a much larger percentage of the
questions (closer to 75 percent). In truth, of course, you can solve only about
half of the questions correctly, but your self-deception may puff you up,
crablike, and increase your confidence in your ability.
The results showed that participants experienced the latter sort of selfpuffery. The predictions of how well they would perform on the second phase of
the test showed that participants not only used the answer key in the first phase
to exaggerate their score, but had very quickly convinced themselves that they
truly earned that score. Basically, those who had a chance to check their answers
in the first phase (and cheated) started believing that their exaggerated
performance was a reflection of their true skill.
But what would happen if we paid participants to predict their score
accurately in the second phase? With money on the line, maybe our participants
wouldn’t so patently ignore the fact that in phase one they had used the answer
key to improve their scores. To that end, we repeated the same experiment with a
new group of participants, this time offering them up to $20 if they correctly
predicted their performance on the second test. Even with a financial incentive to
be accurate, they still tended to take full credit for their scores and overestimate
their abilities. Despite having a strong motivation to be accurate, self-deception
ruled the day.
I KNEW IT ALL ALONG
I give a considerable number of lectures about my research to different
groups, from academics to industry types. When I started giving talks,
I would often describe an experiment, the results, and finally what I
thought we could learn from it. But I often found that some people
were rather unsurprised by the results and were eager to tell me so. I
found this puzzling because, as the person who actually carried out the
research, I’d often been surprised by the outcomes myself. I wondered,
were the people in the audience really that insightful? How did they
know the results sooner than I did? Or was it just an ex post facto
feeling of intuition?
Eventually I discovered a way to combat this “I knew it all along”
feeling. I started asking the audience to predict the results of the
experiments. After I finished describing the setup and what we
measured, I gave them a few seconds to think about it. Then I would
ask them to vote on the outcome or write their prediction down. Only
once they committed to their answer would I provide the results. The
good news is that this approach works. Using this ask-first method, I
rarely receive the “I knew it all along” response.
In honor of our natural tendency to convince ourselves that we
knew the right answers all along, I call my research center at Duke
University “The Center for Advanced Hindsight.”
Our Love of Exaggeration
Once upon a time—back in the early 1990s—the acclaimed movie director
Stanley Kubrick began hearing stories through his assistant about a man who
was pretending to be him. The man-who-would-be-Kubrick (whose real name
was Alan Conway and who looked nothing like the dark-bearded director) went
around London telling people who he famously was(n’t). Since the real Stanley
Kubrick was a very private person who shunned the paparazzi, not many people
had any idea of what he looked like. So a lot of gullible people, thrilled to
“know” the famous director personally, eagerly took Conway’s bait. Warner
Bros., which financed and distributed Kubrick’s films, began calling Kubrick’s
office practically every day with new complaints from people who could not
understand why “Stanley” would not get back to them. After all, they had treated
him to drinks and dinner and paid for his cab, and he had promised them a part
in his next film!
One day, Frank Rich (the former theater critic and op-ed columnist of The
New York Times) was having dinner in a London restaurant with his wife and
another couple. As it happened, the Kubrick imitator was sitting at a nearby table
with a knighted MP and a few other young men, regaling them with stories of his
moviemaking marvels. When the imposter saw Rich at the next table, he walked
over to him and told the critic that he was inclined to sue the Times for having
called him “creatively dormant.” Rich, excited to meet the reclusive “Kubrick,”
asked for an interview. Conway told Rich to call him, gave Rich his home phone
number, and … disappeared.
Very shortly after this encounter, things began to unravel for Conway as it
dawned on Rich and others that they’d been conned. Eventually the truth came
out when Conway began selling his story to journalists. He claimed to be a
recovering victim of a mental disorder (“It was uncanny. Kubrick just took me
over. I really did believe I was him!”). In the end Conway died a penniless
alcoholic, just four months before Kubrick.
*
Although this story is rather extreme, Conway may well have believed that
he was Kubrick when he was parading around in disguise, which raises the
question of whether some of us are more prone to believe our own fibs than
others. To examine this possibility, we set up an experiment that repeated the
basic self-deception task, but this time we also measured participants’ general
tendency to turn a blind eye to their own failures. To measure this tendency, we
asked participants to agree or disagree with a few statements, such as “My first
impressions of people are usually right” and “I never cover up my mistakes.” We
wanted to see whether people who answered “yes” to more of these questions
also had a higher tendency for self-deception in our experiment.
Just as before, we saw that those in the answer-key condition cheated and
got higher scores. Again, they predicted that they would correctly answer more
questions in the following test. And once more, they lost money because they
exaggerated their scores and overpredicted their ability. And what about those
who answered “yes” to more of the statements about their own propensities?
There were many of them, and they were the ones who predicted that they would
do best on our second-phase test.
HEROIC VETERANS?
In 1959, America’s “last surviving Civil War veteran,” Walter
Williams, died. He was given a princely funeral, including a parade
that tens of thousands gathered to see, and an official week of
mourning. Many years later, however, a journalist named William
Marvel discovered that Williams had been only five years old when the
war began, which meant he wouldn’t have been old enough at any
point to serve in the military in any capacity. It gets worse, though. The
title that Walter Williams bore falsely to the grave had been passed to
him from a man named John Salling, who, as Marvel discovered, had
also falsely called himself the oldest Civil War veteran. In fact, Marvel
claims that the last dozen of so-called oldest Civil War veterans were
all phony.
There are countless other stories like these, even in recent wars,
where one might think it would be more difficult to make up and
sustain such claims. In one example, Sergeant Thomas Larez received
multiple gunshot wounds fighting the Taliban in Afghanistan while
helping an injured soldier to safety. Not only did he save his friend’s
life, but he rallied from his own wounds and killed seven Taliban
fighters. So went the reporting of Larez’s exploits aired by a Dallas
news channel, which later had to run a retraction when it turned out
that although Larez was indeed a marine, he had never been anywhere
near Afghanistan—the entire story was a lie.
Journalists often uncover such false claims. But once in a while, it’s
the journalist who’s the fibber. With teary eyes and a shaky voice, the
longtime journalist Dan Rather described his own career in the
marines, even though he had never made it out of basic training.
Apparently, he must have believed that his involvement was far more
significant than it actually was.
1
THERE ARE PROBABLY many reasons why people exaggerate their service
records. But the frequency of stories about people lying on their résumés,
diplomas, and personal histories brings up a few interesting questions: Could it
be that when we lie publicly, the recorded lie acts as an achievement marker that
“reminds” us of our false achievement and helps cement the fiction into the
fabric of our lives? So if a trophy, ribbon, or certificate recognizes something
that we never achieved, would the achievement marker help us hold on to false
beliefs about our own ability? Would such certificates increase our capacity for
self-deception?
BEFORE I TELL you about our experiments on this question I should point out that
I proudly hang two diplomas on my office wall. One is an “MIT Bachelor of
Science in Charm,” and the other is a “PhD in Charm,” also from MIT. I was
awarded these diplomas by the Charm School, which is an activity that takes
place at MIT during the cold and miserable month of January. To fulfill the
requirements, I had to take many classes in ballroom dancing, poetry, tie tying,
and other such cotillion-inspired skills. And in truth, the longer I have the
certificates on my office wall, the more I believe that I am indeed quite
charming.
WE TESTED THE effects of certificates by giving our participants a chance to cheat
on our first math test (by giving them access to the answer key). After they
exaggerated their performance, we gave some of them a certificate emphasizing
their (false) achievement on that test. We even wrote their name and score on the
certificate and printed it on nice, official-looking paper. The other participants
did not receive a certificate. Would the achievement markers raise the
participants’ confidence in their overstated performance, which in reality was
partially based on consulting the answer key? Would it make them believe that
their score was, indeed, a true reflection of their ability?
As it turns out, I am not alone in being influenced by diplomas hanging on
the wall. The participants who received a certificate predicted that they would
correctly answer more questions on the second test. It looks as though having a
reminder of a “job well done” makes it easier for us to think that our
achievements are all our own, regardless of how well the job was actually done.
THE NINETEENTH-CENTURY NOVELIST Jane Austen provided a fantastic example
of the way our own selfish interests, together with the help of others around us,
can get us to believe that our selfishness is really a mark of charity and
generosity. In Sense and Sensibility there is a revealing scene in which John, the
first and only son and legal heir, considers what, exactly, is involved in a
promise he made to his father. At his father’s deathbed, John promises the old
man to take care of his very kind but poor stepmother and three half sisters. Of
his own accord, he decides to give the women £3,000, a mere fraction of his
inheritance, which would take care of them nicely. After all, he genially reasons,
“he could spare so considerable a sum with little inconvenience.”
Despite the satisfaction John gets from this idea and the ease with which the
gift can be given, his clever and selfish wife convinces him—without much
difficulty and with a great deal of specious reasoning—that any money he gives
his step-family will leave him, his wife, and their son “impoverished to a most
dreadful degree.” Like a wicked witch from a fairy tale, she argues that his father
must have been light-headed. After all, the old man was minutes from death
when he made the request. She then harps on the stepmother’s selfishness. How
can John’s stepmother and half sisters think they deserve any money? How can
he, her husband, squander his father’s fortune by providing for his greedy
stepmom and sisters? The son, brainwashed, concludes that “It would be
absolutely unnecessary, if not highly indecorous, to do more for the widow and
his father’s three daughters …” Et voilà! Conscience appeased, avarice
rationalized, fortune untouched.
SELF-DECEPTION IN SPORTS
All players know that steroid use is against the rules and that if they
are ever discovered using them it will tarnish their records as well as
the sport. Yet the desire to beat new (steroid-fueled) records and to win
media attention and fan adoration drives many athletes to cheat by
doping. The problem is everywhere and in every sport. There was
Floyd Landis, who was stripped of his Tour de France victory because
of steroid use in 2006. The University of Waterloo in Canada
suspended its entire football team for a year when eight players tested
positive for anabolic steroids. A Bulgarian soccer coach was banned
from the sport for four years for giving players steroids before a match
in 2010. And yet we can only wonder what steroid users think as they
win a match or while receiving a medal. Do they recognize that their
praise is undeserved, or do they truly believe that their performance is
a pure tribute to their own skill?
Then, of course, there’s baseball. Would Mark McGwire hold so
many records if not for steroid use? Did he believe his achievement was
owing to his own skill? After admitting to steroid use, McGwire stated,
“I’m sure people will wonder if I could have hit all those home runs
had I never taken steroids. I had good years when I didn’t take any,
and I had bad years when I didn’t take any. I had good years when I
took steroids, and I had bad years when I took steroids. But no matter
what, I shouldn’t have done it and for that I’m truly sorry.”
2
Sorry he may be, but in the end neither his fans nor McGwire
himself can know exactly how good he really is.
AS YOU CAN see, people tend to believe their own exaggerated stories. Is it
possible to stop or at least decrease this behavior? Since offering money to
people to judge their performance more accurately did not seem to eliminate
self-deception, we decided to intervene beforehand, right at the moment people
were tempted with the opportunity to cheat. (This approach is related to our use
of the Ten Commandments in chapter 2, “Fun with the Fudge Factor.”) Since
our participants were clearly able to ignore the effect that the answer key had on
their scores, we wondered what would happen if we made the fact that they were
relying on the answer key more obvious at the moment that they were using it. If
using the answer key to boost their scores was blatantly obvious, would they be
less able to convince themselves that they had known the correct answer all
along?
In our initial (paper-based) experiments, it was not possible to figure out
exactly when our participants’ eyes wandered to the answer key and the level to
which they were aware of the help that they got from the written answers. So in
our next experiment, we had our participants take a computerized version of the
same test. This time the answer key at the bottom of the screen was initially
hidden from sight. To reveal the answers, participants had to move the cursor to
the bottom of the screen, and when the cursor was moved away, the answer key
was hidden again. That way the participants were forced to think about exactly
when and for how long they used the answer key, and they could not as easily
ignore such a clear and deliberate action.
Although almost all of the participants consulted the answer key at least
once, we found that this time around (in contrast to the paper-based tests) they
did not overestimate their performance in the second test. Despite the fact that
they still cheated, consciously deciding to use the answer key—rather than
merely glancing at the bottom of the page—eliminated their self-deceptive
tendencies. It seems, then, that when we are made blatantly aware of the ways
we cheat, we become far less able to take unwarranted credit for our
performance.
Self-deception and Self-help
So where do we stand on self-deception? Should we maintain it? Eliminate it? I
suspect that self-deception is similar to its cousins, overconfidence and
optimism, and as with these other biases, it has both benefits and disadvantages.
On the positive side, an unjustifiably elevated belief in ourselves can increase
our general well-being by helping us cope with stress; it can increase our
persistence while doing difficult or tedious tasks; and it can get us to try new and
different experiences.
We persist in deceiving ourselves in part to maintain a positive self-image.
We gloss over our failures, highlight our successes (even when they’re not
entirely our own), and love to blame other people and outside circumstances
when our failures are undeniable. Like our friend the crab, we can use selfdeception to boost our confidence when we might not otherwise feel bold.
Positioning ourselves on the basis of our finer points can help us snag a date,
finish a big project, or land a job. (I am not suggesting that you puff up your
résumé, of course, but a little extra confidence can often work in our favor.)
On the negative side, to the extent that an overly optimistic view of
ourselves can form the basis of our actions, we may wrongly assume that things
will turn out for the best and as a consequence not actively make the best
decisions. Self-deception can also cause us to “enhance” our life stories with,
say, a degree from a prestigious university, which can lead us to suffer a great
deal when the truth is ultimately revealed. And, of course, there is the general
cost of deception. When we and those around us are dishonest, we start
suspecting everyone, and without trust our lives become more difficult in almost
every way.
As in other aspects of life, here too the balance lies between happiness
(partially driven by self-deception) and optimal decisions for the future (and a
more realistic view of ourselves). Sure, it is exciting to be bright-eyed, with
hopes for a wonderful future—but in the case of self-deception, our exaggerated
beliefs can devastate us when reality comes crashing in.
Some Upsides of Lying
When we lie for another person’s benefit, we call it a “white lie.” When we tell a
white lie, we’re expanding the fudge factor, but we’re not doing it for selfish
reasons. For example, consider the importance of insincere compliments. We all
know the gold standard of white lies, in which a woman who is less than svelte
puts on a slinky new dress and asks her husband, “Do I look fat in this?” The
man does a quick cost-benefit analysis; he sees his whole life pass before his
eyes if he answers with the brutal truth. So he tells her, “Darling, you look
beautiful.” Another evening (marriage) saved.
Sometimes white lies are just social niceties, but other times they can work
wonders to help people get through the most difficult of circumstances, as I
learned as an eighteen-year-old burn victim.
After an accident that nearly killed me, I found myself in the hospital with
third-degree burns covering over 70 percent of my body. From the beginning,
the doctors and the nurses kept telling me, “Everything will be okay.” And I
wanted to believe them. To my young mind, “Everything will be okay” meant
that the scars from my burns and many, many skin transplants would eventually
fade and go away, just as when someone burns himself while making popcorn or
roasting marshmallows over a campfire.
One day toward the end of my first year in the hospital, the occupational
therapist said she wanted to introduce me to a recovered burn victim who’d
suffered a similar fate a decade earlier. She wanted to demonstrate to me that it
was possible for me to go out into the world and do things that I used to do—
basically, that everything would be okay. But when the visitor came in, I was
horrified. The man was badly scarred—so badly that he looked deformed. He
was able to move his hands and use them in all kinds of creative ways, but they
were barely functional. This image was far from the way I imagined my own
recovery, my ability to function, and the way I would look once I left the
hospital. After this meeting I became deeply depressed, realizing that my scars
and functionality would be much worse than I had imagined up to that point.
The doctors and nurses told me other well-meaning lies about what kind of
pain to expect. During one unbearably long operation on my hands, the doctors
inserted long needles from the tips of my fingers through the joints in order to
hold my fingers straight so that the skin could heal properly. At the top of each
needle they placed a cork so that I couldn’t unintentionally scratch myself or
poke my eyes. After a couple of months of living with this unearthly contraption,
I found that it would be removed in the clinic—not under anesthesia. That
worried me a lot, because I imagined that the pain would be pretty awful. But the
nurses said, “Oh, don’t worry. This is a simple procedure and it’s not even
painful.” For the next few weeks I felt much less worried about the procedure.
When the time came to withdraw the needles, one nurse held my elbow and
the other slowly pulled out each needle with pliers. Of course, the pain was
excruciating and lasted for days—very much in contrast to how they described
the procedure. Still, in hindsight, I was very glad they had lied to me. If they had
told me the truth about what to expect, I would have spent the weeks before the
extraction anticipating the procedure in misery, dread, and stress—which in turn
might have compromised my much-needed immune system. So in the end, I
came to believe that there are certain circumstances in which white lies are
justified.
CHAPTER 7
Creativity and Dishonesty
We Are All Storytellers
Facts are for people who lack the imagination to create their own truth.
—ANONYMOUS
Once upon a time, two researchers named Richard Nisbett (a professor at the
University of Michigan) and Tim Wilson (a professor at the University of
Virginia) set up camp at their local mall and laid out four pairs of nylon
stockings across a table. They then asked female passersby which of the four
they liked best. The women voted, and, by and large, they preferred the pair on
the far right. Why? Some said they liked the material more. Some said they liked
the texture or the color. Others felt that the quality was the highest. This
preference was interesting, considering that all four pairs of stockings were
identical. (Nisbett and Wilson later repeated the experiment with nightgowns,
and found the same results.)
When Nisbett and Wilson questioned each participant about the rationale
behind her choice, not one cited the placement of the stockings on the table.
Even when the researchers told the women that all the stockings were identical
and that there was simply a preference for the right-hand pair, the women
“denied it, usually with a worried glance at the interviewer suggesting that they
felt either that they had misunderstood the question or were dealing with a
madman.”
The moral of this story? We may not always know exactly why we do what
we do, choose what we choose, or feel what we feel. But the obscurity of our
real motivations doesn’t stop us from creating perfectly logical-sounding reasons
for our actions, decisions, and feelings.
YOU CAN THANK (or perhaps blame) the left side of your brain for this incredible
ability to confabulate stories. As the cognitive neuroscientist Michael Gazzaniga
(a professor at the University of California, Santa Barbara) puts it, our left brain
is “the interpreter,” the half that spins a narrative from our experiences.
Gazzaniga came to this conclusion after many years of research with splitbrain patients, a rare group whose corpora callosa—the largest bundle of nerves
connecting our brain’s two hemispheres—had been cut (usually as a way to
reduce epileptic seizures). Interestingly, this brain abnormality means that these
individuals can be presented with a stimulus to one half of the brain without the
other half having any awareness of it.
Working with a female patient who had a severed corpus callosum,
Gazzaniga wanted to find out what happens when you ask the right side of the
brain to do something and then ask the left side (which has no information about
what is going on in the right side) to provide a reason for that action. Using a
device that showed written instructions to the patient’s right hemisphere,
Gazzaniga instructed the right side of the patient’s brain to make her laugh by
flashing the word “laugh.” As soon as the woman complied, he asked her why
she had laughed. The woman had no idea why she laughed, but rather than
responding with “I don’t know,” she made up a story. “You guys come up and
test us every month. What a way to make a living!” she said. Apparently she had
decided that cognitive neuroscientists were pretty amusing.
This anecdote illustrates an extreme case of a tendency we all have. We want
explanations for why we behave as we do and for the ways the world around us
functions. Even when our feeble explanations have little to do with reality.
We’re storytelling creatures by nature, and we tell ourselves story after story
until we come up with an explanation that we like and that sounds reasonable
enough to believe. And when the story portrays us in a more glowing and
positive light, so much the better.
Cheating Myself
In a commencement speech at Cal Tech in 1974, the physicist Richard Feynman
told graduates, “The first principle is that you must not fool yourself—and you
are the easiest person to fool.” As we have seen so far, we human beings are torn
by a fundamental conflict—our deeply ingrained propensity to lie to ourselves
and to others, and the desire to think of ourselves as good and honest people. So
we justify our dishonesty by telling ourselves stories about why our actions are
acceptable and sometimes even admirable. Indeed, we’re pretty skilled at pulling
the wool over our own eyes.
Before we examine in more detail what makes us so good at weaving selfglorifying tales, allow me to tell you a little story about how I once (very
happily) cheated myself. Quite a few years ago (when I was thirty), I decided
that I needed to trade in my motorcycle for a car. I was trying to decide which
car would be the perfect one for me. The Internet was just starting to boom with
what I’ll politely call “decision aids,” and to my delight I found a website that
provided advice for purchasing cars. The website was based on an interview
procedure, and it presented me with a lot of questions that ranged from
preferences for price and safety to what kind of headlights and brakes I wanted.
It took about twenty minutes to answer all the questions. Each time I
completed a page of answers, I could see the progress bar indicating that I was
that much closer to discovering my personalized dream car. I finished the final
page of questions and eagerly clicked the “Submit” button. In just a few seconds
I got my answer. What was the perfect car for me? According to this finely tuned
website, the car for me was … drum roll, please … a Ford Taurus!
I confess that I did not know much about cars. In fact, I know very little
about cars. But I certainly knew that I did not want a Ford Taurus.
*
I’m not sure what you would do in such a situation, but I did what any
creative person might do: I went back into the program and “fixed” my previous
answers. From time to time I checked to see how different answers translated
into different car recommendations. I kept this up until the program was kind
enough to recommend a small convertible—surely the right car for me. I
followed that sage advice, and that’s how I became the proud owner of a
convertible (which, by the way, has served me loyally for many years).
This experience taught me that sometimes (perhaps often) we don’t make
choices based on our explicit preferences. Instead, we have a gut feeling about
what we want, and we go through a process of mental gymnastics, applying all
kinds of justifications to manipulate the criteria. That way, we can get what we
really want, but at the same time keep up the appearance—to ourselves and to
others—that we are acting in accordance with our rational and well-reasoned
preferences.
Coin Logic
If we accept that we frequently make decisions in this way, perhaps we can
make the process of rationalization more efficient and less time-consuming.
Here’s how: Imagine that you’re choosing between two digital cameras. Camera
A has a nice zoom and a hefty battery, while camera B is lighter and has a
snazzier shape. You’re not sure which one to get. You think that camera A is
better quality but camera B will make you happier because you like how it looks.
What should you do? Here is my advice: Pull a quarter out of your pocket and
say to yourself, “Camera A is heads, camera B is tails.” Then toss the coin. If the
coin comes up heads and camera A is the one you wanted, good for you, go buy
it. But if you’re not happy with the outcome, start the process again, saying to
yourself, “The next toss is for real.” Do this until the coin gives you tails. You’ll
not only get camera B, which you really wanted all along, but you can justify
your decision because you only followed the “advice” of the coin. (You could
also replace the coin with your friends and consult them until one of them gives
you the advice you want.)
Perhaps that was the real function of the car recommendation software I used
to get my convertible. Maybe it was designed not only to help me make a better
decision but to create a process that would allow me to justify the choice I really
wanted to make. If that is the case, I think it would be useful to develop many
more of these handy applications for many other areas of life.
The Liar’s Brain
Most of us think that some people are especially good (or bad) at deception. If
this is indeed the case, what characteristics distinguish them? A team of
researchers led by Yaling Yang (a postdoc at the University of California, Los
Angeles) tried to find out the answer to this question by studying pathological
liars—that is, people who lie compulsively and indiscriminately.
To find participants for their study, Yang and her colleagues went to a Los
Angeles temporary employment agency. They figured that at least a few of those
who were without permanent employment would have had difficulty holding a
job because they were pathological liars. (Obviously, this doesn’t apply to all
temps.)
The researchers then gave 108 job seekers a battery of psychological tests
and conducted several one-on-one interviews with them, their coworkers, and
their family members in order to identify major discrepancies that might reveal
the pathological liars. In this group, they found twelve people who had pervasive
inconsistencies in the stories they told about their work, schooling, crimes
committed, and family background. They were also the same individuals who
frequently engaged in malingering, or pretending that they were sick in order to
get sickness benefits.
Next, the team put the twelve pathological liars—plus twenty-one people
who were not pathological liars and were in the same pool of job seekers (the
control group)—through a brain scanner to explore each person’s brain structure.
The researchers focused on the prefrontal cortex, a part of the brain that sits just
behind our foreheads and is considered to be in charge of higher-order thinking,
such as planning our daily schedule and deciding how to deal with temptations
around us. It’s also the part of the brain that we depend on for our moral
judgments and decision making. In short, it’s a kind of control tower for
thinking, reasoning, and morality.
In general, there are two types of matter that fill our brains: gray and white.
Gray matter is just another name for the collections of neurons that make up the
bulk of our brains, the stuff that powers our thinking. White matter is the wiring
that connects those brain cells. We all have both gray and white matter, but Yang
and her collaborators were particularly interested in the relative amounts of the
two types in the participants’ prefrontal cortices. They found that pathological
liars had 14 percent less gray matter than the control group, a common finding
for many psychologically impaired individuals. What could this mean? One
possibility is that since the pathological liars had fewer brain cells (the gray
matter) fueling their prefrontal cortex (an area crucial to distinguishing between
right and wrong), they find it harder to take morality into account, making it
easier for them to lie.
But that’s not all. You might wonder about the extra space that pathological
liars must have in their skulls since they have so much less gray matter. Yang
and her colleagues also found that pathological liars had 22 to 26 percent more
white matter in the prefrontal cortex than non–pathological liars. With more
white matter (remember, this is what links the gray matter), pathological liars are
likely able to make more connections between different memories and ideas, and
this increased connectivity and access to the world of associations stored in their
gray matter might be the secret ingredient that makes them natural liars.
If we extrapolate these findings to the general population, we might say that
higher brain connectivity could make it easier for any of us to lie and at the same
time think of ourselves as honorable creatures. After all, more connected brains
have more avenues to explore when it comes to interpreting and explaining
dubious events—and perhaps this is a crucial element in the rationalization of
our dishonest acts.
More Creativity Equals More Money
These findings made me wonder whether increased white matter could be linked
to both increased lying and increased creativity. After all, people who have more
connections among their different brain parts and more associations are
presumably also more creative. To test this possible link between creativity and
dishonesty, Francesca Gino and I carried out a series of studies. True to the
nature of creativity itself, we approached the question from a variety of angles,
starting with a relatively simple approach.
When our participants showed up at the lab, we informed them that they
would answer some questions followed by a computerized task. The question set
included many irrelevant questions about their general experiences and habits
(these filler questions were designed to obscure the real intent of the study) and
three types of questions that were the focus of the study.
In the first set of questions, we asked the participants to indicate to what
degree they would describe themselves using some “creative” adjectives
(insightful, inventive, original, resourceful, unconventional, and so on). In the
second, we asked them to tell us how often they engage in seventy-seven
different activities, some of which require more creativity and some less
(bowling, skiing, skydiving, painting, writing, and so forth). In the third and last
set of questions, we asked participants to rate how much they identified with
statements such as “I have a lot of creative ideas,” “I prefer tasks that enable me
to think creatively,” “I like to do things in an original way,” and other similar
statements.
Once the participants completed the personality measures, we asked them to
complete the dots task, which was presumably unconnected to the questions. In
case you don’t recall this task, flip back to The “What- the- Hell” Effect in
chapter 5, “Why Wearing Fakes Make Us Cheat More.”
What do you think happened? Would participants who chose a large number
of creative adjectives, engaged in creative activities more frequently, and viewed
themselves as more creative cheat more, less, or about the same as the
participants who were not as creative?
We found that participants who clicked the more-on-right button (the one
with the higher payout) more often tended to be the same people who scored
higher on all three creativity measures. Moreover, the difference between more
and less creative individuals was most pronounced in the cases where the
difference in the number of dots on the right and left sides was relatively small.
This suggested that the difference between creative and less creative
individuals comes into play mostly when there is ambiguity in the situation at
hand and, with it, more room for justification. When there was an obvious
difference between the number of dots on the two sides of the diagonal, the
participants simply had to decide whether to lie or not. But when the trials were
more ambiguous and it was harder to tell if there were more dots to the right or
the left of the diagonal, creativity kicked into action—along with more cheating.
The more creative the individuals, the better they were at explaining to
themselves why there were more dots to the right of the diagonal (the side with
the higher reward).
Put simply, the link between creativity and dishonesty seems related to the
ability to tell ourselves stories about how we are doing the right thing, even
when we are not. The more creative we are, the more we are able to come up
with good stories that help us justify our selfish interests.
Does Intelligence Matter?
Although this was an intriguing result, we didn’t get too excited just yet. This
first study showed that creativity and dishonesty are correlated, but that doesn’t
necessarily mean that creativity is directly linked to dishonesty. For example,
what if a third factor such as intelligence was the factor linked to both creativity
and dishonesty?
The link among intelligence, creativity, and dishonesty seems especially
plausible when one considers how clever people such as the Ponzi schemer
Bernie Madoff or the famous check forger Frank Abagnale (the author of Catch
Me If You Can) must have been to fool so many people. And so our next step
was to carry out an experiment in which we checked to see whether creativity or
intelligence was a better predictor of dishonesty.
Again, picture yourself as one of our participants. This time, the testing
starts before you even set foot in the lab. A week earlier, you sit down at your
home computer and complete an online survey, which includes questions to
assess your creativity and also measure your intelligence. We measure your
creativity using the same three measures from the previous study, and measure
your intelligence in two ways. First, we ask you to answer three questions
designed to test your reliance on logic versus intuition using a set of three
questions collected by Shane Frederick (a professor at Yale University). Along
with the correct answer, each question comes with an intuitive answer that is in
fact incorrect.
To give you an example, try this one: “A bat and a ball cost $1.10 in total.
The bat costs $1.00 more than the ball. How much does the ball cost?”
Quick! What’s the answer?
Ten cents?
Good try, but no. It’s the seductive answer, but not the right one.
Although your intuition prods you to answer “$0.10,” if you rely on logic
more than intuition, you’ll check your answer just to be sure: “If the ball were
$0.10, the bat would be $1.10, which combine to equal $1.20, not $1.10 (.1 + (1
+ .1) = 1.2)! Once you realize that your initial instinct is wrong, you enlist your
memory of high school algebra and produce the correct solution (.05 + (1 + .05)
= 1.1): 5 cents. Doesn’t it feel like the SATs all over again? And congratulations
if you got it right. (If not, don’t worry, you would have most likely aced the two
other questions on this short test.)
Next, we measure your intelligence through a verbal test. Here you’re
presented with a series of ten words (such as “dwindle” and “palliate”), and for
each word you have to choose which of six options is closest in meaning to the
target word.
A week later, you come to the lab and settle into one of the computer-facing
chairs. Once you’re situated, the instructions begin: “You’ll be taking part in
three different tasks today; these will test your problem-solving abilities,
perceptual skills, and general knowledge. For the sake of convenience, we’ve
combined them all into one session.”
First up is the problem-solving task, which is none other than our trusty
matrix task. When the five minutes for the test are over, you fold your worksheet
and drop it into the recycling bin. What do you claim is your score? Do you
report your actual score? Or do you dress it up a little?
Your second task, the perceptual skills task, is the dots test. Once again, you
can cheat all you want. The incentive is there—you can earn $10 if you cheat in
every one of the trials.
Finally, your third and final task is a multiple-choice general-knowledge
quiz comprised of fifty questions of varying difficulty and subject matter. The
questions include a variety of trivia such as “How far can a kangaroo jump?” (25
to 40 feet) and “What is the capital of Italy?” (Rome). For each correct answer,
you receive 10 cents, for a maximum payout of $5. In the instructions for this
last test, we ask that you circle your answers on the question sheet before later
transferring them to a bubble sheet.
When you reach the end of this quiz, you put down your pencil. Suddenly
the experimenter pipes up, “Oh, my gosh! I goofed! I mistakenly photocopied
bubble sheets that are already marked with the correct answers. I’m so sorry.
Would you mind using one of these premarked bubble sheets? I’ll try to erase all
the marks so that they will not show very clearly. Okay?” Of course you agree.
Next the experimenter asks you to copy your answers from the quiz to the
premarked bubble sheet, shred the test sheets with your original answers, and
only then submit the premarked bubble sheet with your answers in order to
collect your payment. Obviously, as you transfer your answers you realize that
you can cheat: instead of transferring your own answers to the bubble sheets,
you can just fill in the premarked answers and take more money. (“I knew all
along that the capital of Switzerland is Bern. I just chose Zurich without thinking
about it.”)
To sum things up, you’ve taken part in three tasks in which you can earn up
to $20 to put toward your next meal, beer, or textbook. But how much you
actually walk away with depends on your smarts and test-taking chops, as well
as your moral compass. Would you cheat? And if so, do you think your cheating
has anything to do with how smart you are? Does it have anything to do with
how creative you are?
Here’s what we found: as in the first experiment, the individuals who were
more creative also had higher levels of dishonesty. Intelligence, however, wasn’t
correlated to any degree with dishonesty. This means that those who cheated
more on each of the three tasks (matrices, dots, and general knowledge) had on
average higher creativity scores compared to noncheaters, but their intelligence
scores were not very different.
We also studied the scores of the extreme cheaters, the participants who
cheated almost to the max. In each of our measures of creativity, they had higher
scores than those who cheated to a lower degree. Once again, their intelligence
scores were no different.
Stretching the Fudge Factor: The Case for Revenge
Creativity is clearly an important means by which we enable our own cheating,
but it’s certainly not the only one. In an earlier book (The Upside of
Irrationality) I described an experiment designed to measure what happens when
people are upset by bad service. Briefly, Ayelet Gneezy (a professor at the
University of California, San Diego) and I hired a young actor named Daniel to
run some experiments for us in local coffee shops. Daniel asked coffee shop
patrons to participate in a five-minute task in return for $5. When they agreed, he
handed them ten sheets of paper covered with random letters and asked them to
find as many identical adjacent letters as they could and circle them with a
pencil. After they finished, he returned to their table, collected their sheets,
handed them a small stack of bills, and told them, “Here is your $5, please count
the money, sign the receipt, and leave it on the table. I’ll be back later to collect
it.” Then he left to look for another participant. The key was that he gave them
$9 rather than $5, and the question was how many of the participants would
return the extra cash.
This was the no-annoyance condition. Another set of customers—those in
the annoyance condition—experienced a slightly different Daniel. In the midst
of explaining the task, he pretended that his cell phone was vibrating. He
reached into his pocket, took out the phone, and said, “Hi, Mike. What’s up?”
After a short pause, he would enthusiastically say, “Perfect, pizza tonight at
eight thirty. My place or yours?” Then he would end his call with “Later.” The
whole fake conversation took about twelve seconds.
After Daniel slipped the cell phone back into his pocket, he made no
reference to the disruption and simply continued describing the task. From that
point on, everything was the same as in the no-annoyance condition.
We wanted to see if the customers who had been so rudely ignored would
keep the extra money as an act of revenge against Daniel. Turns out they did. In
the no-annoyance condition 45 percent of people returned the extra money, but
only 14 percent of those who were annoyed did so. Although we found it pretty
sad that more than half the people in the no-annoyance condition cheated, it was
pretty disturbing to find that the twelve-second interruption provoked people in
the annoyance condition to cheat much, much more.
In terms of dishonesty, I think that these results suggest that once something
or someone irritates us, it becomes easier for us to justify our immoral behavior.
Our dishonesty becomes retribution, a compensatory act against whatever got
our goat in the first place. We tell ourselves that we’re not doing anything
wrong, we are only getting even. We might even take this rationalization a step
further and tell ourselves that we are simply restoring karma and balance to the
world. Good for us, we’re crusading for justice!
MY FRIEND AND New York Times technology columnist David Pogue captured
some of the annoyance we feel toward customer service—and the desire for
revenge that comes with it. Anyone who knows David would tell you that he is
the kind of person who would gladly help anyone in need, so the idea that he
would go out of his way to hurt anyone is rather surprising—but when we feel
hurt, there is hardly a limit to the extent to which we can reframe our moral
code. And David, as you’ll see in a moment, is a highly creative individual. Here
is David’s song (please sing along to the melody of “The Sounds of Silence”):
Hello voice mail, my old friend
I’ve called for tech support again
I ignored my boss’s warning
I called on a Monday morning
Now it’s evening and my dinner
First grew cold and then grew mold …
I’m still on hold!
I’m listening to the sounds of silence.
You don’t seem to understand.
I think your phone lines are unmanned.
I punched every touchtone I was told,
But I’ve still spent 18 hours on hold.
It’s not enough your program crashed my Mac
And it constantly hangs and bombs;
It erased my ROMs!
Now my Mac makes the sounds of silence.
In my dreams I fantasize
Of wreaking vengeance on you guys.
Say your motorcycle crashes;
Blood comes gushing from your gashes.
With your fading strength you call 911
And you pray for a trained MD …
But you get me!
And you listen to the sounds of silence!
An Italian Story of Creative Revenge
When I was seventeen and my cousin Yoav was eighteen, we spent the summer
backpacking in Europe, having a wonderful time. We met lots of people, saw
beautiful cities and places, spent time in museums—it was a perfect European
jaunt for two restless teenagers.
Our travel itinerary went from Rome up through Italy and France and finally
to England. When we originally bought our youth train passes, the nice fellow at
the Rome Eurail office gave us a photocopy of a map of the European train
system, carefully marking the train path that we were going to take with a black
ballpoint pen. He told us that we could use our passes anytime we wanted within
the two-month window but that we could travel only along the particular route
he had drawn. He stapled the flimsy photocopied map to a more official printed
receipt and handed us the package. Initially, we were certain that no conductor
would respect this rather unsophisticated-looking map and ticket combo, but the
ticket seller assured us that it was all we needed, and in fact that proved to be the
case.
After enjoying the sights in Rome, Florence, Venice, and a few smaller
Italian towns, we spent a few nights on the shore of a lake outside Verona. On
our last night by the lake, we woke up to find that someone had been through our
backpacks and strewn our stuff all over the place. After taking a careful
inventory of our belongings, we saw that all of our clothes and even my camera
were still there. The only thing missing was Yoav’s extra pair of sneakers. We
would have considered it a minor loss, except for the fact that Yoav’s mother
(my aunt Nava), in her infinite wisdom, had wanted to make sure that we had
some emergency cash in case someone stole our money. So she had tucked a few
hundred dollars in Yoav’s extra pair of sneakers. The irony of the situation was
painful.
We decided to look around the town to see if we could spot someone
wearing Yoav’s sneakers and went to the police as well. Given the fact that the
local policemen understood little English, it was rather difficult to convey the
nature of the crime—that a pair of sneakers had been stolen and that it was
important because there was cash hidden in the sole of the right shoe. Not
surprisingly, we never recovered Yoav’s sneakers, and that left us somewhat
embittered. In our minds it was an unfair turn of events, and Europe owed us
one.
ABOUT A WEEK after the sneaker-theft incident, we decided that in addition to the
other places on our route we also wanted to visit Switzerland and the
Netherlands. We could have purchased new train tickets for the detour, but
remembering the stolen shoes and the lack of help from the Italian police, we
decided instead to expand our options with a bit of creativity. Using a black
ballpoint pen just like the ticket seller’s, we drew another path on our
photocopied map. This one passed through Switzerland on the way to France
and from there to England. Now the map showed two possible routes for our
journey: the original route and our modified one. When we showed the maps to
the next few conductors, they did not comment on our artwork, so we continued
sketching extra routes on our maps for a few weeks.
Our scam worked until we were en route to Basel. The Swiss conductor
examined our passes, scowled, shook his head, and handed them back to us.
“You are going to have to buy a ticket for this part of your trip,” he informed
us.
“Oh, but you see, sir,” we said ever so politely, “Basel is indeed on our
route.” We pointed to the modified path on our map.
The conductor was unconvinced. “I am sorry, but you will have to pay for
your ticket to Basel, or I will have to ask you to leave the train.”
“But, sir,” we argued, “all the other conductors have accepted our tickets
with no problem.”
The conductor shrugged and shook his head again.
“Please, sir,” pleaded Yoav, “if you allow us to get to Basel, we will give
you this tape of the Doors. They’re a great American rock band.”
The conductor did not seem amused or particularly interested in the Doors.
“Okay,” he said. “You can go to Basel.”
We weren’t sure whether he finally agreed with us, appreciated the gesture,
or had just given up. After that incident we stopped adding lines to our map, and
soon we returned to our original planned path.
LOOKING BACK ON our dishonest behavior, I am tempted to chalk it up to the
stupidity of youth. But I know that’s not the whole picture. In fact, I suspect that
there are a number of aspects of the situation that enabled us to behave that way
and justify our actions as perfectly acceptable.
First, I’m sure that being in a foreign country by ourselves for the first time
helped us feel more comfortable with the new rules we were creating.
*
If we had
stopped to give our actions more thought, we would have certainly recognized
their seriousness, but somehow without thinking much, we imagined that our
creative route enhancements were part of the regular Eurail procedure. Second,
losing a few hundred dollars and Yoav’s sneakers made us feel that it was okay
for us to take some revenge and get Europe to pay us back. Third, since we were
on an adventure, maybe we felt more morally adventurous too. Fourth, we
justified our actions by convincing ourselves that we weren’t really hurting
anything or anyone. After all, we were just drawing a few extra lines on a piece
of paper. The train was going on its track anyway; and besides, the trains were
never full, so we weren’t displacing anyone. It was also the case that we very
easily justified our actions to ourselves because when we originally purchased
the tickets, we could have picked a different route for the same price. And since
the different paths were the same to the Eurail office when we originally
purchased the tickets, why would it matter at what point in time we decided to
choose a different path? (Maybe that’s how people who back-date stock options
justify their actions to themselves.) A final source of justification had to do with
the physical nature of the ticket itself. Because the Eurail ticket seller had given
us just a flimsy piece of photocopied paper with a hand drawing of our planned
route, it was physically easy for us to make our changes—and because we were
just marking the path in the same way as the ticket seller (making lines on a
piece of paper), this physical ease quickly translated into a moral ease as well.
When I think about all of these justifications together, I realize how
extensive and expansive our ability to justify is and how prevalent
rationalization can be in just about every one of our daily activities. We have an
incredible ability to distance ourselves in all kinds of ways from the knowledge
that we are breaking the rules, especially when our actions are a few steps
removed from causing direct harm to someone else.
The Cheater’s Department
Pablo Picasso once said, “Good artists copy, great artists steal.” Throughout
history, there has been no dearth of creative borrowers. William Shakespeare
found his plot ideas in classical Greek, Roman, Italian, and historical sources
and then wrote brilliant plays based on them. Even Steve Jobs occasionally
boasted that much like Picasso, Apple was shameless about stealing great ideas.
Our experiments thus far suggested that creativity is a guiding force when it
comes to cheating. But we didn’t know whether we could take some people,
increase their creativity, and with it also increase their level of dishonesty. This
is where the next step of our empirical investigation came in.
In the next version of our experiments, Francesca and I looked into whether
we could increase the level of cheating simply by getting our participants into a
more creative mind-set (using what social scientists call priming). Imagine that
you’re one of the participants. You show up, and we introduce you to the dots
task. You start off by completing a practice round, for which you do not receive
any payment. Before you transition into the real phase—the one that involves the
biased payment—we ask you to complete a sentence creation task. (This is
where we work our creativity-inducing magic by using a scrambled sentence
task, a common tactic for changing participants’ momentary mind-sets.) In this
task, you are given twenty sets of five words presented in a random order (such
as “sky,” “is,” “the,” “why,” “blue”), and you are asked to construct a
grammatically correct four-word sentence from each set (“The sky is blue”).
What you don’t know is that there are two different versions of this task, and you
are going to see only one of them. One version is the creative set, in which
twelve of the twenty sentences include words related to creativity (“creative,”
“original,” “novel,” “new,” “ingenious,” “imagination,” “ideas,” and so on). The
other version is the control set, in which none of the twenty sentences includes
any words related to creativity. Our aim was to prime some of the participants
into a more innovative, aspiring mind-set à la Albert Einstein or Leonardo da
Vinci by using the words associated with creativity. Everyone else was stuck
with their usual mind-set.
Once you complete the sentence task (in one of the two versions), you go
back to the dots task. But this time you’re doing it for real money. Just as before,
you earn half a cent for choosing the left side and 5 cents for choosing the right.
What kind of picture did the data paint? Did facilitating a more creative
mind-set affect a person’s morality? Although the two groups didn’t differ in
their levels of performance in the practice rounds of the dots task (when there
was no payment), there was a difference after the scrambled sentence task. As
we expected, the participants who had been primed with the creative words
chose “right” (the response with the higher pay) more often than those in the
control condition.
SO FAR, IT appeared that a creative mind-set could make people cheat a bit more.
In the final stage of our investigation, we wanted to see how creativity and
cheating correlate in the real world. We approached a large advertising agency
and got most of the employees to answer a series of questions about moral
dilemmas. We asked questions such as “How likely would you be to inflate your
business expense report?”; “How likely would you be to tell your supervisor that
progress has been made on a project when none has been made at all?”; and
“How likely are you to take home office supplies from work?” We also asked
them which department they worked for within the company (accounting,
copywriting, account management, design, and so on). Finally, we got the CEO
of the advertising agency to tell us how much creativity was required to work in
each of the departments.
Now we knew the basic moral disposition of each employee, their
departments, and the level of creativity expected in each department. With this
data at hand, we computed the moral flexibility of the employees in each of the
different departments and how this flexibility related to the creativity demanded
by their jobs. As it turned out, the level of moral flexibility was highly related to
the level of creativity required in their department and by their job. Designers
and copy-writers were at the top of the moral flexibility scale, and the
accountants ranked at the bottom. It seems that when “creativity” is in our job
description, we are more likely to say “Go for it” when it comes to dishonest
behavior.
The Dark Side of Creativity
Of course, we’re used to hearing creativity extolled as a personal virtue and as
an important engine for the progress of society. It’s a trait we aspire to—not just
as individuals but also as companies and communities. We honor innovators,
praise and envy those who have original minds, and shake our heads when others
aren’t able to think outside the box.
There’s good reason for all of this. Creativity enhances our ability to solve
problems by opening doors to new approaches and solutions. It’s what has
enabled mankind to redesign our world in (sometimes) beneficial ways with
inventions ranging from sewer and clean water systems to solar panels, and from
skyscrapers to nanotechnology. Though we still have a way to go, we can thank
creativity for much of our progress. After all, the world would be a much bleaker
place without creative trailblazers such as Einstein, Shakespeare, and da Vinci.
But that’s only part of the story. Just as creativity enables us to envision
novel solutions to tough problems, it can also enable us to develop original paths
around rules, all the while allowing us to reinterpret information in a self-serving
way. Putting our creative minds to work can help us come up with a narrative
that lets us have our cake and eat it too, and create stories in which we’re always
the hero, never the villain. If the key to our dishonesty is our ability to think of
ourselves as honest and moral people while at the same time benefitting from
cheating, creativity can help us tell better stories—stories that allow us to be
even more dishonest but still think of ourselves as wonderfully honest people.
The combination of positive and desired outcomes, on the one hand, and the
dark side of creativity, on the other, leaves us in a tight spot. Though we need
and want creativity, it is also clear that under some circumstances creativity can
have a negative influence. As the historian (and also my colleague and friend)
Ed Balleisen describes in his forthcoming book Suckers, Swindlers, and an
Ambivalent State, every time business breaks through new technological
frontiers—whether the invention of the postal service, the telephone, the radio,
the computer, or mortgage-backed securities—such progress allows people to
approach the boundaries of both technology and dishonesty. Only later, once the
capabilities, effects, and limitations of a technology have been established, can
we determine both the desirable and abusive ways to use these new tools.
For example, Ed shows that one of the first uses of the U.S. postal service
was for selling products that did not exist. It took some time to figure that out,
and eventually the problem of mail fraud ushered in a strong set of regulations
that now help ensure the high quality, efficiency, and trust in this important
service. If you think about technological development from this perspective, it
means that we should be thankful to some of the creative swindlers for some of
their innovation and some of our progress.
Where does this leave us? Obviously, we should keep hiring creative people,
we should still aspire to be creative ourselves, and we should continue to
encourage creativity in others. But we also need to understand the links between
creativity and dishonesty and try to restrict the cases in which creative people
might be tempted to use their skills to find new ways to misbehave.
BY THE WAY—I am not sure if I mentioned it, but I think that I am both incredibly
honest and highly creative.
CHAPTER 8
Cheating as an Infection
How We Catch the Dishonesty Germ
I spend a lot of my time giving talks around the world about the effects of
irrational behavior. So naturally, I’m a very frequent flyer. One typical itinerary
included flying from my home in North Carolina to New York City, then on to
São Paulo, Brazil; Bogotá, Colombia; Zagreb, Croatia; San Diego, California;
and back to North Carolina. A few days later I flew to Austin, Texas; New York
City; Istanbul, Turkey; Camden, Maine; and finally (exhausted) back home. In
the process of accumulating all those miles, I’ve sustained an endless number of
insults and injuries while grinding through security checkpoints and attempting
to retrieve lost baggage. But those pains have been nothing compared to the pain
of getting sick while traveling, and I am always trying to minimize my chances
of falling ill.
On one particular transatlantic flight, while I was preparing a talk to give the
next day on conflicts of interest, my neighbor seemed to have a bad cold. Maybe
it was his sickness, my fear of catching something in general, sleep deprivation,
or just the random and amusing nature of free associations that made me wonder
about the similarity between the germs my seatmate and I were passing back and
forth and the recent spread of corporate dishonesty.
As I’ve mentioned, the collapse of Enron spiked my interest in the
phenomenon of corporate cheating—and my interest continued to grow
following the wave of scandals at Kmart, WorldCom, Tyco, Halliburton, BristolMyers Squibb, Freddie Mac, Fannie Mae, the financial crisis of 2008, and, of
course, Bernard L. Madoff Investment Securities. From the sidelines, it seemed
that the frequency of financial scandals was increasing. Was this due to
improvements in the detection of dishonest and illegal behavior? Was it due to a
deteriorating moral compass and an actual increase in dishonesty? Or was there
also an infectious element to dishonesty that was getting a stronger hold on the
corporate world?
Meanwhile, as my sniffling neighbor’s pile of used tissues grew, I began
wondering whether someone could become infected with an “immorality bug.”
If there was a real increase in societal dishonesty, could it be spreading like an
infection, virus, or communicable bacteria, transmitted through mere observation
or direct contact? Might there be a connection between this notion of infection
and the continually unfolding story of deception and dishonesty that we have
increasingly seen all around us? And if there were such a connection, would it be
possible to detect such a “virus” early and prevent it from wreaking havoc?
To me, this was an intriguing possibility. Once I got home, I started reading
up on bacteria, and I learned that we have innumerable bacteria in, on, and
around our bodies. I also learned that as long as we have only a limited amount
of the harmful bacteria, we manage rather well. But problems tend to arise when
the number of bacteria becomes so great that it disturbs our natural balance or
when a particularly bad strain of bacteria makes it through our bodies’ defenses.
To be fair, I am hardly the first to think of this connection. In the eighteenth
and nineteenth centuries, prison reformers believed that criminals, like the ill,
should be kept separated and in well-ventilated places in order to avoid
contagion. Of course, I didn’t take the analogy between the spread of dishonesty
and diseases as literally as my predecessors. Some sort of airborne miasma
probably won’t transform people into criminals. But at the risk of overstretching
the metaphor, I thought that the natural balance of social honesty could be upset,
too, if we are put into close proximity to someone who is cheating. Perhaps
observing dishonesty in people who are close to us might be more “infectious”
than observing the same level of dishonesty in people who aren’t so close or
influential in our lives. (Consider, for example, the catchphrase “I learned it by
watching you” from the antidrug campaign of the 1980s: the ad warned that
“Parents who use drugs have children who use drugs.”)
Keeping with the infection metaphor, I wondered about the intensity of
exposure to cheating and how much dishonest behavior it might take to tilt the
scale of our own actions. If we see a colleague walking out of the office supply
room with a handful of pens, for example, do we immediately start thinking that
it’s all right to follow in his footsteps and grab some office supplies ourselves? I
suspect that this is not the case. Instead, much like our relationship with bacteria,
there might be a slower and more subtle process of accretion: perhaps when we
see someone cheat, a microscopic impression is left with us and we become ever
so slightly more corrupt. Then, the next time we witness unethical behavior, our
own morality erodes further, and we become more and more compromised as the
number of immoral “germs” to which we are exposed increases.
A FEW YEARS ago I purchased a vending machine, thinking it would be an
interesting tool for running experiments related to pricing and discounts. For a
few weeks, Nina Mazar and I used it to see what would happen if we gave
people a probabilistic discount instead of a fixed discount. Translated, that
means that we set up the machine so that some candy slots were marked with a
30 percent discount off the regular price of $1, while other slots gave users a 70
percent chance of paying the full price of $1.00 and a 30 percent chance of
getting all their money back (and therefore paying nothing). In case you are
interested in the results of this experiment, we almost tripled sales by
probabilistically giving people back their money. This probabilistic discounting
is a story for another time, but the idea of people getting their money back gave
us an idea for testing another path for cheating.
One morning, I had the machine moved near a classroom building at MIT
and set the internal price of the machine to zero for each of the candies. On the
outside, each candy allegedly cost 75 cents. But the moment students shelled out
three quarters and made their selection, the machine served both the candy and
the money. We also put a prominent sign on the machine with a number to call if
the machine malfunctioned.
A research assistant sat within eyeshot of the machine and pretended to work
on her laptop. But instead she recorded what people did when confronted with
the surprise of free candy. After doing this for a while, she observed two types of
behavior. First, people took approximately three pieces of candy. When they got
their first candy together with their payment, most people checked to see
whether it would happen again (which, of course, it did). And then many people
decided to go for it a third time. But no one tried more often than that. People
undoubtedly remembered a time when a vending machine ate their money
without dispensing anything, so they probably felt as though this generous
machine was evening out their vending-machine karma.
We also found that more than half of the people looked around for a friend,
and when they saw someone they knew, they invited their friend over to partake
in the sugar-laden boon. Of course, this was just an observational study, but it
led me to suspect that when we do something questionable, the act of inviting
our friends to join in can help us justify our own questionable behavior. After all,
if our friends cross the ethical line with us, won’t that make our action seem
more socially acceptable in our own eyes? Going to such lengths to justify our
bad behavior might seem over the top, but we often take comfort when our
actions fall in line with the social norms of those around us.
Infectious Cheating in Class
After my experience with the vending machine, I started observing the infectious
nature of cheating in other places as well—including in my own classes. At the
start of the semester a few years ago, I asked the five hundred undergraduate
students in my behavioral economics class how many of them believed that they
could listen carefully in class while using their computers for non-class-related
activities (Facebook, Internet, e-mail, and so on). Thankfully, most of them
indicated that they couldn’t really multitask very well (which is true). I then
asked how many of them had enough self-control to avoid using their laptop for
non-class-related activities if it was open in front of them. Almost no one raised
a hand.
At that point I was conflicted between prohibiting laptops in the classroom
(which are of course useful for taking notes) or allowing laptops but, to help the
students fight their lack of self-control, adding some intervention. Being an
optimist, I asked the students to raise their right hands and repeat after me, “I
will never, never, never use my computer in this course for anything that is not
class-related. I will not read or send e-mail; I will not use Facebook or other
social networks; and I will not use the Internet to explore any non-class-related
material during class time.”
The students repeated these words after me, and I was rather pleased with
myself—for a while.
From time to time I show videos in class both to illustrate a point and to give
the students a change in pace and attention. I usually take this time to walk to the
back of the class and watch the videos with the students from there. Of course,
standing at the back of the class also gives me a direct line of sight to the screens
of the students’ laptops. During the first few weeks of the semester their screens
shone only with class-related material. But as the semester drew on—like
mushrooms after the rain—I noticed that every week more and more of the
screens were opened to very familiar but non-class-related websites and that
Facebook and e-mail programs were often front and center.
In retrospect, I think that the darkness that accompanied the videos was one
of the culprits in the deterioration of the students’ promise. Once the class was in
darkness and one student used his laptop for a non-class-related activity, even
for just one minute, many of the other students, not just me, could see what he
was doing. That most likely led more students to follow the same pattern of
misbehavior. As I discovered, the honesty pledge was helpful in the beginning,
but ultimately it was no match for the power of the emerging social norm that
came from observing the misbehavior of others.
*
One Bad Apple
My observations of on-campus cheating and my 30,000-foot musings about
social infection were, of course, just speculations. To acquire a more informed
view of the infectious nature of cheating, Francesca Gino, Shahar Ayal (a
professor at the Interdisciplinary Center in Israel), and I decided to set up a few
experiments at Carnegie Mellon University, where Francesca was visiting at the
time. We set up the matrix task in the same general way I described earlier
(although we used an easier version of the task), but with a few important
differences. The first was that along with the worksheets containing the matrices,
the experimenter handed out a manila envelope containing $10 worth of cash
(eight $1 bills and four half-dollar coins) to each participant. This change in
payment procedure meant that at the end of the experiment, the participants paid
themselves and left behind their unearned cash.
In the control condition, in which there was no opportunity for cheating, a
student who solved seven questions in the allotted time counted how many
problems she solved correctly, withdrew the appropriate amount of money from
the manila envelope, and placed the money in her wallet. Then the participant
handed the worksheet and envelope with the unearned cash back to the
experimenter, who checked the worksheet, counted the remaining money in the
envelope, and sent the student away with her earnings. So far, so good.
In the shredder condition, the instructions were a bit different. In this
condition the experimenter told the participants, “After you count your answers,
head over to the shredder at the back of the room, shred your questionnaire, then
walk back to your seat and take the amount of money you have earned from the
manila envelope. After that, you are free to leave. On your way out, toss the
envelope with the unearned money into the box by the door.” Then she told the
participants to start on the test and began reading a thick book (to make it clear
that no one was watching). After the five minutes were over, the experimenter
announced that the time was up. The participants put down their pencils, counted
the number of their correct answers, shredded their worksheets, walked back to
their seat, paid themselves, and on their way out tossed their envelopes
containing the leftover money into the box. Not surprisingly, we found that
participants in the shredder condition claimed to have solved more matrices than
those in the control condition.
These two conditions created the starting point from which we could test
what we really wanted to look at: the social component of cheating. Next, we
took the shredder condition (in which cheating was possible) and added a social
element to it. What would happen if our participants could observe someone else
—a Madoff in the making—cheating egregiously? Would it alter their level of
cheating?
Imagine that you are a participant in our so-called Madoff condition. You’re
seated at a desk, and the experimenter gives you and your fellow participants the
instructions. “You may begin!” she announces. You dive into the problem set,
trying to solve as many matrices as possible to maximize your earnings. About
sixty seconds pass, and you’re still on the first question. The clock is ticking.
“I’ve finished!” a tall, skinny, blond-haired guy says as he stands up and
looks at the experimenter. “What should I do now?”
“Impossible,” you think. “I haven’t even solved the first matrix!” You and
everyone else stare at him in disbelief. Obviously, he’s cheated. Nobody could
have completed all twenty matrices in less than sixty seconds.
“Go shred your worksheet,” the instructor tells him. The guy walks to the
back of the room, shreds his worksheet, and then says, “I solved everything, so
my envelope for the extra money is empty. What should I do with it?”
“If you don’t have money to return,” the experimenter replies, unfazed, “put
the empty envelope in the box, and you are free to go.” The student thanks her,
waves good-bye to everyone, and leaves the room smiling, having pocketed the
entire amount. Having observed this episode, how do you react? Do you become
outraged that the guy cheated and got away with it? Do you change your own
moral behavior? Do you cheat less? More?
It may make you feel slightly better to know that the fellow who cheated so
outrageously was an acting student named David, whom we hired to play this
role. We wanted to see if observing David’s outrageous behavior would cause
the real participants to follow his example, catching the “immorality virus,” so to
speak, and start cheating more themselves.
Here’s what we found. In the Madoff condition, our participants claimed to
have solved an average of fifteen out of twenty matrices, an additional eight
matrices beyond the control condition, and an additional three matrices beyond
the shredder condition. In short, those in the Madoff condition paid themselves
for roughly double the number of answers they actually got right.
Here’s a quick summary:
THOSE RESULTS, THOUGH interesting, still don’t tell us why the participants in the
Madoff condition were cheating more. Given David’s performance, participants
could have made a quick calculation and said to themselves, “If he can cheat and
get away with it, it must mean that I can do the same without any fear of getting
caught.” If this were the case, David’s action would have changed participants’
cost-benefit analysis by clearly demonstrating that in this experiment, they could
cheat and get away with it. (This is the SMORC perspective that we described in
chapter 1, “Testing the Simple Model of Rational Crime.”)
A very different possibility is that David’s actions somehow signaled to the
other participants in the room that this type of behavior was socially acceptable,
or at least possible, among their peers. In many areas of life, we look to others to
learn what behaviors are appropriate and inappropriate. Dishonesty may very
well be one of the cases where the social norms that define acceptable behavior
are not very clear, and the behavior of others—David, in this case—can shape
our ideas about what’s right and wrong. From this perspective, the increased
cheating we observed in the Madoff condition could be due not to a rational
cost-benefit analysis, but rather to new information and mental revision of what
is acceptable within the moral boundaries.
To examine which of the two possibilities better explains the increased
cheating in the Madoff condition, we set up another experiment, with a different
type of social-moral information. In the new setup, we wanted to see whether
erasing any concern about being caught but without giving an enacted example
of cheating would also cause participants to cheat more. We got David to work
for us again, but this time he interjected a question as the experimenter was
wrapping up the instructions. “Excuse me,” he said to the experimenter in a loud
voice, “Given these instructions, can’t I just say I solved everything and walk
away with all the cash? Is this okay?” After pausing for a few seconds, the
experimenter answered, “You can do whatever you want.” For obvious reasons,
we called this the question condition. Upon hearing this exchange, participants
quickly understood that in this experiment they could cheat and get away with it.
If you were a participant, would this understanding encourage you to cheat
more? Would you conduct a quick cost-benefit analysis and figure that you
could walk away with some unearned dough? After all, you heard the
experimenter say, “Do whatever you want,” didn’t you?
Now let’s stop and consider how this version of the experiment can help us
understand what happened in the Madoff condition. In the Madoff condition the
participants were provided with a live example of cheating behavior, which
provided them with two types of information: From a cost-benefit perspective,
watching David walk out with all the money showed them that in this
experiment there are no negative consequences to cheating. At the same time,
David’s action provided them with a social cue that people just like them seem
to be cheating in this experiment. Because the Madoff condition included both
elements, we couldn’t tell if the increased cheating that followed was due to a
reevaluation of the cost-benefit analysis, to the social cue, or to both.
This is where the question condition comes in handy. In this condition, only
the first element (cost-benefit perspective) was present. When David asked the
question and the experimenter confirmed that cheating was not only possible but
also without a consequence, it became clear to the participants that cheating in
this setup had no downside. And most important, the question condition changed
the participants’ understanding of the consequence without giving them a live
example and social cue of someone from their social group who cheated. If the
amount of cheating in the question condition were the same as in the Madoff
condition, we would conclude that what caused the increased level of cheating in
both conditions was most likely the information that there was no consequence
to cheating. On the other hand, if the amount of cheating in the question
condition were much lower than in the Madoff condition, we would conclude
that what caused the extra-high level of cheating in the Madoff condition was the
social signal—the realization that people from the same social group find it
acceptable to cheat in this situation.
What do you think happened? In the question condition, our participants
claimed to have solved an average of ten matrices—about three more matrices
than in the control condition (which means they did cheat) but by about two
fewer matrices than in the shredder condition and by five fewer than in the
Madoff condition. After observing the experimenter telling David that he could
do what he wanted, cheating actually decreased. That was the opposite of what
would have happened if our participants had engaged solely in a rational costbenefit analysis. Moreover, this result suggests that when we become aware of
the possibility of immoral behavior, we reflect on our own morality (similar to
the Ten Commandments and the honor code experiments in chapter 2, “Fun with
the Fudge Factor”). And as a consequence, we behave more honestly.
A Fashion Statement
Although those results were promising, we still wanted to get more direct
support and evidence for the idea that cheating might be socially contagious. So
we decided to go into the fashion business. Well, sort of.
The structure of our next experiment was the same as in the Madoff
condition: our actor stood up a few seconds into the experiment and announced
that he had solved everything and so forth. But this time there was one fashionrelated difference: the actor wore a University of Pittsburgh sweatshirt.
Let me explain. Pittsburgh has two world-class universities, the University
of Pittsburgh (UPitt) and Carnegie Mellon University (CMU). Like many
institutions of higher learning that are in close proximity, these two have a longstanding rivalry. This competitive spirit was just what we needed to further test
our cheating-as-a-social-contagion hypothesis.
We conducted all of these experiments at Carnegie Mellon University, and
all our participants were Carnegie Mellon students. In the basic Madoff
condition, David had worn just a plain T-shirt and jeans and had therefore been
assumed to be a Carnegie Mellon student, just like all the other participants. But
in our new condition, which we named the “outsider-Madoff condition,” David
wore a blue-and-gold UPitt sweatshirt. This signaled to the other students that he
was an outsider—a UPitt student—and not part of their social group; in fact, he
belonged to a rival group.
The logic of this condition was similar to the logic of the question condition.
We reasoned that if the increased cheating we observed in the Madoff condition
was due to the realization that if David could cheat and get away with it, so
could the other participants, and it would not matter if David was dressed as a
CMU or a UPitt student. After all, the information that there were no negative
consequences to egregious cheating was the same regardless of his outfit. On the
other hand, if the increase in cheating in the Madoff condition was due to an
emerging social norm that revealed to our participants that cheating was
acceptable in their social group, this influence would operate only when our
actor was part of their in-group (a Carnegie Mellon student) and not when he
was a member of another, rival group (a UPitt student). The crucial element in
this design, therefore, was the social link connecting David to the other
participants: when he was dressed in a UPitt sweatshirt, would the CMU
students continue to play copycat, or would they resist his influence?
To recap the results so far, here’s what we saw: When cheating was possible
in the shredder condition but not publicized by David, students claimed to have
solved, on average, twelve matrices—five more than they did in the control
condition. When David stood up wearing regular CMU attire in the Madoff
condition, the participants claimed to have solved about fifteen matrices. When
David asked a question about the possibility of cheating and he was assured that
it was possible, participants claimed to have solved only ten matrices. And
finally, in the outsider-Madoff condition (when David wore a UPitt sweatshirt),
the students observing him cheat, claimed to have solved only nine matrices.
They still cheated relative to the control condition (by about two matrices), but
they cheated by about six fewer matrices than when David was assumed to be a
part of their CMU social group.
Here’s how our results looked:
Together, these results show not only that cheating is common but that it is
infectious and can be increased by observing the bad behavior of others around
us. Specifically, it seems that the social forces around us work in two different
ways: When the cheater is part of our social group, we identify with that person
and, as a consequence, feel that cheating is more socially acceptable. But when
the person cheating is an outsider, it is harder to justify our misbehavior, and we
become more ethical out of a desire to distance ourselves from that immoral
person and from that other (much less moral) out-group.
More generally, these results show how crucial other people are in defining
acceptable boundaries for our own behavior, including cheating. As long as we
see other members of our own social groups behaving in ways that are outside
the acceptable range, it’s likely that we too will recalibrate our internal moral
compass and adopt their behavior as a model for our own. And if the member of
our in-group happens to be an authority figure—a parent, boss, teacher, or
someone else we respect—chances are even higher that we’ll be dragged along.
In with the In-Crowd
It’s one thing to get riled up about a bunch of college students cheating their
university out of a few dollars (although even this cheating accumulates
quickly); it’s quite another when cheating is institutionalized on a larger scale.
When a few insiders deviate from the norm, they infect those around them, who
in turn infect those around them, and so on—which is what I suspect occurred at
Enron in 2001, on Wall Street leading up to 2008, and in many other cases.
One can easily imagine the following scenario: A well-known banker named
Bob at Giantbank engages in shady dealings—overpricing some financial
products, delaying reporting losses until the next year, and so on—and in the
process he makes boatloads of money. Other bankers at Giantbank hear about
what Bob is up to. They go out to lunch and, over their martinis and steaks,
discuss what Bob is doing. In the next booth, some folks from Hugebank
overhear them. Word gets around.
In a relatively short time, it is clear to many other bankers that Bob isn’t the
only person to fudge some numbers. Moreover, they consider him as part of their
in-group. To them, fudging the numbers now becomes accepted behavior, at
least within the realm of “staying competitive” and “maximizing shareholder
value.”
*
Similarly, consider this scenario: one bank uses its government bailout
money to pay out dividends to its shareholders (or maybe the bank just keeps the
cash instead of lending it). Soon, the CEOs of other banks start viewing this as
appropriate behavior. It is an easy process, a slippery slope. And it’s the kind of
thing that happens all around us every day.
BANKING, OF COURSE, is not the only place this unfortunate kind of escalation
takes place. You can find it anywhere, including governing bodies such as the
U.S. Congress. One example of deteriorating social norms in the U.S. legislative
halls involves political action committees (PACs). About thirty years ago, these
groups were established as a way for members of Congress to raise money for
their party and fellow lawmakers to use during difficult election battles. The
money comes primarily from lobbyists, corporations, and special-interest
groups, and the amounts they give are not restricted to the same degree as
contributions to individual candidates. Aside from being taxed and having to be
reported to the FEC, few restrictions are placed on the use of PAC money.
As you might imagine, members of Congress have gotten into the habit of
using their PAC funds for a gamut of non-election-related activities—from
babysitting bills to bar tabs, Colorado ski trips, and so on. What’s more, less than
half of the millions of dollars raised by PACs has gone to politicians actually
running in elections; the rest is commonly put toward different perks: fundraising, overhead, staff, and other expenses. As Steve Henn of the NPR show
Marketplace put it, “PACs put the fun in fundraising.”
1
To deal with the misuse of PAC money, the very first law that Congress
passed after the 2006 congressional election was intended to limit the
discretionary spending of Congress members, forcing them to publicly disclose
how they spent their PAC money. However, and somewhat predictably from our
perspective, the legislation seemed to have no effect. Just a few weeks after
passing the law, the congressmen were behaving as irresponsibly as they had
before; some spent the PAC money going to strip clubs, blowing thousands of
dollars on parties, and generally conducting themselves without a semblance of
accountability.
How can this be? Very simple. Over time, as congressmen have witnessed
fellow politicians using PAC funds in dubious ways, their collective social norm
has taken a turn for the worse. Little by little, it’s been established that PACs can
be used for all kinds of personal and “professional” activities—and now the
misuse of PAC funds is as common as suits and ties in the nation’s capital. As
Pete Sessions (a Republican congressman from Texas) responded when he was
questioned about dropping several grand at the Forty Deuce in Las Vegas, “It’s
hard for me to know what is normal or regular anymore.”
2
You might suspect, given the polarization in Congress, that such negative
social influences would be contained within parties. You might think that if a
Democrat breaks the rules, his behavior would influence only other Democrats
and that bad behavior by Republicans would influence only Republicans. But my
own (limited) experience in Washington, D.C., suggests that away from the
watchful eye of the media, the social practices of Democrats and Republicans
(however disparate their ideologies) are much closer than we think. This creates
the conditions under which the unethical behavior of any congressman can
extend beyond party lines and influence other members, regardless of their
affiliation.
ESSAY MILLS
In case you’re unfamiliar with them, essay mills are companies whose
sole purpose is to generate essays for high school and college students
(in exchange for a fee, of course). Sure, they claim that the papers are
intended to help the students write their own original papers, but with
names such as eCheat.com, their actual purpose is pretty clear. (By the
way, the tagline of eCheat.com was at one point “It’s Not Cheating, It’s
Collaborating.”)
Professors, in general, worry about essay mills and their impact on
learning. But without any personal experience using essay mills and
without any idea about what they really do or how good they are, it is
hard to know how worried we should be. So Aline Grüneisen (the lab
manager of my research center at Duke University) and I decided to
check out some of the most popular essay mills. We ordered a set of
typical college term papers from a few of the companies, and the topic
of the paper we chose was (surprise!) “Cheating.”
Here is the task that we outsourced to the essay mills:
When and why do people cheat? Consider the social circumstances
involved in dishonesty, and provide a thoughtful response to the topic of
cheating. Address various forms of cheating (personal, at work, etc.) and
how each of these can be rationalized by a social culture of cheating.
We requested a twelve-page term paper for a university-level social
psychology class, using fifteen references, formatted in American
Psychological Association (APA) style, to be completed in two weeks.
This was, to our minds, a pretty basic and conventional request. The
essay mills charged us from $150 to $216 per paper in advance.
Two weeks later, what we received would best be described as
gibberish. A few of the papers attempted to mimic APA style, but none
achieved it without glaring errors. The citations were sloppy and the
reference lists abominable—including outdated and unknown sources,
many of which were online news stories, editorial posts, or blogs, and
some that were simply broken links. In terms of the quality of the
writing itself, the authors of all of the papers seemed to have a tenuous
grasp of the English language and the structure of a basic essay.
Paragraphs jumped clumsily from one topic to another and often
collapsed into list form, counting off various forms of cheating or
providing a long stream of examples that were never explained or
connected to the thesis of the paper. Of the many literary affronts, we
found the following gems:
Cheating by healers. Healing is different. There is harmless healing,
when healers-cheaters and wizards offer omens, lapels, damage to
withdraw, the husband-wife back and stuff. We read in the newspaper
and just smile. But these days fewer people believe in wizards.
If the large allowance of study undertook on scholar betraying is any
suggestion of academia and professors’ powerful yearn to decrease
scholar betraying, it appeared expected these mind-set would component
into the creation of their school room guidelines.
By trusting blindfold only in stable love, loyalty, responsibility and
honesty the partners assimilate with the credulous and naïve persons of
the past.
The future generation must learn for historical mistakes and develop
the sense of pride and responsibility for its actions.
At that point we were rather relieved, figuring that the day had not
yet arrived when students can submit papers from essay mills and get
good grades. Moreover, we concluded that if students did try to buy a
paper from an essay mill, just like us, they would feel they had wasted
their money and wouldn’t try it again.
But the story does not end there. We submitted the essays we
purchased to WriteCheck.com, a website that inspects papers for
plagiarism, and found that half of the papers we received were largely
copied from existing works. We decided to take action and contacted
the essay mills to request our money back. Despite the solid proof from
WriteCheck.com, the essay mills insisted that they had not plagiarized
anything. One company even threatened us with litigation and claimed
that they would get in touch with the dean’s office at Duke to alert him
to the fact that I had submitted work that was not mine. Needless to
say, we never received that refund …
The bottom line? Professors shouldn’t worry too much about essay
mills, at least for now. The technological revolution has not yet solved
this particular challenge for students, and they still have no other
option but to write their own papers (or maybe cheat the old-fashioned
way and use a paper from a student who took the class during a
previous semester).
But I do worry about the existence of essay mills and the signal that
they send to our students—that is, the institutional acceptance of
cheating, not only while they are in school but after they graduate.
How to Regain Our Ethical Health?
The idea that dishonesty can be transmitted from person to person via social
contagion suggests that we need to take a different approach to curbing
dishonesty. In general, we tend to view minor infractions as just that: trivial and
inconsequential. Peccadilloes may be relatively insignificant in and of
themselves, but when they accumulate within a person, across many people, and
in groups, they can send a signal that it’s all right to misbehave on a larger scale.
From this perspective, it’s important to realize that the effects of individual
transgressions can go beyond a singular dishonest act. Passed from person to
person, dishonesty has a slow, creeping, socially erosive effect. As the “virus”
mutates and spreads from one person to another, a new, less ethical code of
conduct develops. And although it is subtle and gradual, the final outcome can
be disastrous. This is the real cost of even minor instances of cheating and the
reason we need to be more vigilant in our efforts to curb even small infractions.
So what can we do about it? One hint may lie in the Broken Windows
Theory, which was the basis of a 1982 Atlantic article by George Kelling and
James Wilson. Kelling and Wilson proposed a critical component of keeping
order in dangerous neighborhoods, and it wasn’t just putting more police on the
beat. They argued that if people in a run-down area of town see a building with a
few broken, long-unrepaired windows, they will be tempted to break even more
windows and create further damage to the building and its surroundings, creating
a blight effect. Based on the Broken Windows Theory, they suggested a simple
strategy for preventing vandalism: fix problems when they are small. If you
repair each broken window (or other misbehaviors) immediately, other potential
offenders are going to be much less likely to misbehave.
Although the Broken Windows Theory has been difficult to prove or refute,
its logic is compelling. It suggests that we should not excuse, overlook, or
forgive small crimes, because doing so can make matters worse. This is
especially important for those in the spotlight: politicians, public servants,
celebrities, and CEOs. It might seem unfair to hold them to higher standards, but
if we take seriously the idea that publicly observed behavior has a broader
impact on those viewing the behavior, this means that their misbehavior can
have greater downstream consequences for society at large. In contrast to this
view, it seems that celebrities are too often rewarded with lighter punishments
for their crimes than the rest of the population, which might suggest to the public
that these crimes and misdemeanors are not all that bad.
THE GOOD NEWS is that we can also take advantage of the positive side of moral
contagion by publicizing the individuals who stand up to corruption. For
example, Sherron Watkins of Enron, Coleen Rowley of the FBI, and Cynthia
Cooper of WorldCom are great examples of individuals who stood up to internal
misconduct in their own organizations, and in 2002 Time magazine selected
them as People of the Year.
Acts of honesty are incredibly important for our sense of social morality.
And although they are unlikely to make the same sensational news, if we
understand social contagion, we must also recognize the importance of publicly
promoting outstanding moral acts. With more salient and vivid examples of
commendable behavior, we might be able to improve what society views as
acceptable and unacceptable behaviors, and ultimately improve our actions.
CHAPTER 9
Collaborative Cheating
Why Two Heads Aren’t Necessarily Better than One
If you’ve ever worked in just about any organization, you know that working in
teams accounts for a lot of your time. A great deal of economic activity and
decision making takes place through collaboration. In fact, the majority of U.S.
companies depend on group-based work, and more than half of all U.S.
employees currently spend at least part of their day working in a group setting.
1
Try to count the number of meetings, project teams, and collaborative
experiences you’ve had over the last six months, and you will quickly realize
how many working hours these group activities consume. Group work also plays
a prominent role in education. For example, the majority of MBA students’
assignments consist of group-based tasks, and many undergraduate classes also
require group-based projects.
In general, people tend to believe that working in groups has a positive
influence on outcomes and that it increases the overall quality of decisions.
2
(In
fact, much research has shown that collaboration can decrease the quality of
decisions. But that’s a topic for another time.) In general, the belief is that there
is little to lose and everything to gain from collaboration—including
encouraging a sense of camaraderie, increasing the level of fun at work, and
benefitting from sharing and developing new ideas—all of which add up to more
motivated and effective employees. What’s not to love?
A FEW YEARS ago, in one of my graduate classes, I lectured about some of my
research related to conflicts of interest (see chapter 3, “Blinded by Our Own
Motivations”). After class, a student (I’ll call her Jennifer) told me that the
discussion had struck a chord with her. It reminded her of an incident that had
taken place a few years earlier, when she was working as a certified public
accountant (CPA) for a large accounting firm.
Jennifer told me that her job had been to produce the annual reports, proxy
statements, and other documents that would inform shareholders about the state
of their companies’ affairs. One day her boss asked her to have her team prepare
a report for the annual shareholders’ meeting of one of their larger clients. The
task involved going over all of the client’s financial statements and determining
the company’s financial standing. It was a large responsibility, and Jennifer and
her team worked hard to put together a comprehensive and detailed report that
was honest and realistic. She did her best to prepare the report as accurately as
possible, without, for example, overclaiming the company’s profits or delaying
reporting any losses to the next accounting year. She then left the draft of the
report on her boss’s desk, looking forward (somewhat anxiously) to his
feedback.
Later that day, Jennifer got the report back with a note from her boss. It read,
“I don’t like these numbers. Please gather your team and get me a revised
version by next Wednesday.” Now, there are many reasons why her boss might
not have “liked” the numbers, and it wasn’t entirely clear to her what he meant.
Moreover, not “liking” the numbers is an entirely different matter from the
numbers being wrong—which was never implied. A multitude of questions ran
through Jennifer’s head: “What exactly did he want? How different should I
make the numbers? Half a percent? One percent? Five percent?” She also didn’t
understand who was going to be accountable for any of the “improvements” she
made. If the revisions turned out to be overly optimistic and someone was going
to take the blame for it down the road, would it be her boss or her?
THE PROFESSION OF accounting is itself a somewhat equivocal trade. Sure, there
are some clear-cut rules. But then there is a vaguely titled body of suggestions—
known as Generally Accepted Accounting Principles (GAAP)—that accountants
are supposed to follow. These guidelines afford accountants substantial leeway;
they are so general that there’s considerable variation in how accountants can
interpret financial statements. (And often there are financial incentives to “bend”
the guidelines to some degree.) For instance, one of the rules, “the principle of
sincerity,” states that the accountant’s report should reflect the company’s
financial status “in good faith.” That’s all well and good, but “in good faith” is
both excessively vague and extremely subjective. Of course, not everything (in
life or accounting) is precisely quantifiable, but “in good faith” begs a few
questions: Does it mean that accountants can act in bad faith?
* And toward
whom is this good faith directed? The people who run the company? Those who
would like the books to look impressive and profitable (which would increase
their bonuses and compensation)? Or should it be directed toward the people
who have invested in the company? Or is it about those who want a clear idea of
the company’s financial condition?
Adding to the inherent complexity and ambiguity of her original task,
Jennifer was now put under additional pressure by her boss. She’d prepared the
initial report in what seemed to her to be good faith, but she realized that she was
being asked to bend the accounting rules to some degree. Her boss wanted
numbers that reflected more favorably upon the client company. After
deliberating for a while, she concluded that she and her team should comply with
his request; after all, he was her boss, and he certainly knew a lot more than she
did about accounting, how to work with clients, and the client’s expectations. In
the end, although Jennifer started the process with every intention of being as
accurate as possible, she wound up going back to the drawing board, reviewing
the statements, reworking the numbers, and returning with a “better” report. This
time, her boss was satisfied.
AFTER JENNIFER TOLD me her story, I continued to think about her work
environment and the effect that working on a team with her boss and teammates
had on her decision to push the accounting envelope a bit further. Jennifer was
certainly in the kind of situation that people frequently face in the workplace, but
what really stood out for me was that in this case the cheating took place in the
context of a team, which was different from anything we had studied before.
In all of our earlier experiments on cheating, one person alone made the
decision to cheat (even if he or she was spurred along by a dishonest act of
another person). But in Jennifer’s case, more than one person was directly
involved, as is frequently the case in professional settings. In fact, it was clear to
Jennifer that in addition to herself and her boss, her teammates would be affected
by her actions. At the end of the year, the whole team would be evaluated
together as a group—and their bonuses, raises, and future prospects were
intertwined.
I started to wonder about the effects of collaboration on individual honesty.
When we are part of a group, are we tempted to cheat more? Less? In other
words, is a group setting conducive or destructive to honesty? This question is
related to a topic we discussed in the previous chapter (“Cheating as an
Infection”): whether it’s possible that people can “catch” cheating from one
another. But social contagion and social dependency are different. It’s one thing
to observe dishonest behavior in others and, based on that, alter our perceptions
of what acceptable social norms are; it’s quite another if the financial welfare of
others depends on us.
Let’s say you’re working on a project with your coworkers. You don’t
necessarily observe them doing anything shady, but you know that they (and
you) will benefit if you bend the rules a bit. Will you be more likely to do so if
you know that they too will get something out of it? Jennifer’s account suggests
that collaboration can cause us to take a few extra liberties with moral
guidelines, but is this the case in general?
Before we take a tour of some experiments examining the impact of
collaboration on cheating, let’s take a step back and think about possible positive
and negative influences of teams and collaboration on our tendency to be
dishonest.
Altruistic Cheating: Possible Costs of Collaboration
Work environments are socially complex, with multiple forces at play. Some of
those forces might make it easy for group-based processes to turn collaborations
into cheating opportunities in which individuals cheat to a higher degree because
they realize that their actions can benefit people they like and care about.
Think about Jennifer again. Suppose she was a loyal person and liked to
think of herself that way. Suppose further that she really liked her supervisor and
team members and sincerely wanted to help them. Based on such considerations,
she might have decided to fulfill her boss’s request or even take her report a step
further—not because of any selfish reasons but out of concern for her boss’s
well-being and deep regard for her team members. In her mind, “bad” numbers
might get her boss and team members to fall out of favor with the client and the
accounting company—meaning that Jennifer’s concern for her team might lead
her to increase the magnitude of her misbehavior.
Underlying this impulse is what social scientists call social utility. This term
is used to describe the irrational but very human and wonderfully empathetic
part of us that causes us to care about others and take action to help them out
when we can—even at a cost to ourselves. Of course, we are all motivated to act
in our own self-interest to some degree, but we also have a desire to act in ways
that benefit those around us, particularly those we care about. Such altruistic
feelings motivate us to help a stranger who is stuck with a flat tire, return a
wallet we’ve found in the street, volunteer at a homeless shelter, help a friend in
need, and so on.
This tendency to care about others can also make it possible to be more
dishonest in situations where acting unethically will benefit others. From this
perspective, we can think about cheating when others are involved as altruistic—
where, like Robin Hood, we cheat because we are good people who care about
the welfare of those around us.
Watch Out: Possible Benefits of Collaboration
In Plato’s “Myth of the King of Gyges,” a shepherd named Gyges finds a ring
that makes him invisible. With this new-found power, he decides to go on a
crime spree. So he travels to the king’s court, seduces the queen, and conspires
with her to kill the king and takes control of the kingdom. In telling the story,
Plato wonders whether there is anyone alive who could resist taking advantage
of the power of invisibility. The question, then, is whether the only force that
keeps us from carrying out misdeeds is the fear of being seen by others (J. R. R.
Tolkien elaborated on this theme a couple millennia later in The Lord of the
Rings). To me, Plato’s myth offers a nice illustration of the notion that group
settings can inhibit our propensity to cheat. When we work within a team, other
team members can act informally as monitors, and, knowing that we are being
watched, we may be less inclined to act dishonorably.
A CLEVER EXPERIMENT by Melissa Bateson, Daniel Nettle, and Gilbert Roberts
(all from the University of Newcastle) illustrated the idea that the mere feeling of
being watched can inhibit bad behavior. This experiment took place in the
kitchen of the psychology department at the University of Newcastle where tea,
coffee, and milk were available for the professors and staff. Over the tea-making
area hung a sign saying that beverage drinkers should contribute some cash to
the honesty box located nearby. For ten weeks the sign was decorated with
images, but the type of image alternated every week. On five of the weeks the
sign was decorated with images of flowers, and on the other five weeks the sign
was decorated with images of eyes that stared directly at the beverage drinkers.
At the end of every week, the researchers counted the money in the honesty box.
What did they find? There was some money in the box at the end of the weeks
when the image of flowers was hung, but when the glaring eyes were
“watching,” the box contained almost three times more money.
As is the case with many findings in behavioral economics, this experiment
produced a mix of good and bad news. On the negative side, it showed that even
members of the psychology department—who you would think would know
better—tried to sneak off without paying their share for a common good. On the
positive side, it showed that the mere suggestion that they were being watched
made them behave more honestly. It also shows that a full-blown Orwellian “Big
Brother is watching” approach is not necessary and that much more subtle
suggestions of being watched can be effective in increasing honesty. Who
knows? Perhaps a warning sign, complete with watchful eyes, on Jennifer’s
boss’s wall might have made a difference in his behavior.
IN PONDERING JENNIFER’S situation, Francesca Gino, Shahar Ayal, and I began to
wonder how dishonesty operates in collaborative environments. Does
monitoring help to reduce cheating? Do social connections in groups increase
both altruism and dishonesty? And if both of these forces exert their influence in
opposite directions, which of the two is more powerful? In order to shed light on
this question, we turned once again to our favorite matrix experiment. We
included the basic control condition (in which cheating was not possible), the
shredder condition (in which cheating was possible), and we added a new
condition that introduced a collaborative element to the shredder condition.
As our first step in exploring the effects of groups, we didn’t want the
collaborators to have an opportunity to discuss their strategy or to become
friends, so we came up with a collaboration condition that included no
familiarity or connection between the two team members. We called it the
distant-group condition. Let’s say you are one of the participants in the distantgroup condition. As in the regular shredder condition, you sit at a desk and use a
number 2 pencil to work on the matrices for five minutes. When the time is up,
you walk to the shredder and destroy your test sheet.
Up to that point, the procedure is the same as in the basic shredder condition,
but now we introduce the collaborative element. The experimenter tells you that
you are part of a two-person team and that each of you will be paid half of the
group’s total earnings. The experimenter points out that your collection slip is
either blue or green and has a number printed in the top-right corner. The
experimenter asks you to walk around the room and find the person whose
collection slip is different in color but with the same number in the top-right
corner. When you find your partner, you sit down together, and each of you
writes the number of matrices you correctly solved on your collection slip. Next,
you write the other person’s score on your collection slip. And finally, you
combine the numbers for a total performance measure. Once that’s done, you
walk over to the experimenter together and hand him both collection slips. Since
your worksheets have been shredded, the experimenter has no way to check the
validity of your reported earnings. So he takes your word for it, pays you
accordingly, and you split the takings.
Do you think people in this situation would cheat more than they did in the
individual shredder condition? Here’s what we found: when participants learned
that both they and someone else would benefit from their dishonesty if they
exaggerated their scores more, they ended up engaging in even higher levels of
cheating, claiming to have solved three more matrices than when they were
cheating just for themselves. This result suggests that we humans have a
weakness for altruistic cheating, even if we barely know the person who might
benefit from our misbehavior. Sadly, it seems that even altruism can have a dark
side.
That’s the bad news, and it’s not all of it.
HAVING ESTABLISHED ONE negative aspect of collaboration—that people are
more dishonest when others, even strangers, can benefit from their cheating—we
wanted to turn our experimental sights on a possible positive aspect of
collaboration and see what would happen when team members watch each other.
Imagine that you’re in a room with a few other participants, and you’re
randomly paired up with someone you have never met before. As luck would
have it, you’ve ended up with a friendly-looking young woman. Before you have
a chance to talk to her, you have to complete the matrix task in complete silence.
You are player 1, so you start first. You tear into the first matrix, then the
second, and then the third. All the while, your partner watches your attempts,
successes, and failures. When the five minutes are up, you silently put your
pencil down and your partner picks hers up. She starts working on her matrix
task while you observe her progress. When the time is up, you walk to the
shredder together and shred your worksheets. Then you each write down your
own score on the same slip of paper, combine the two numbers for your joint
performance score, and walk over to the experimenter’s desk to collect your
payment—all without saying a word to each other.
What level of cheating did we find? None at all. Despite the general
inclination to cheat that we observe over and over, and despite the increase in the
propensity to cheat when others can benefit from such actions, being closely
supervised eliminated cheating altogether.
SO FAR, OUR experiments on cheating in groups showed two forces at play:
altruistic tendencies get people to cheat more when their team members can
benefit from their dishonesty, but direct supervision can reduce dishonesty and
even eliminate it altogether. Given the coexistence of these two forces, the next
question is: which force is more likely to overpower the other in more standard
group interactions?
To answer this question, we needed to create an experimental setting that
was more representative of how group members interact in a normal, day-to-day
environment. You probably noticed that in the first two experiments, our
participants didn’t really interact with each other, whereas in daily life, group
discussion and friendly chatter are an essential and inherent part of group-based
collaborations. Hoping to add this important social element to our experimental
setup, we devised our next experiment. This time, participants were encouraged
to talk to each other, get to know each other, and become friendly. We even gave
them lists of questions that they could ask each other in order to break the ice.
They then took turns monitoring each other while each of them solved the
matrices.
Sadly, we found that cheating reared its ugly head when we added this social
element to the mix. When both elements were in the mix, the participants
reported that they correctly solved about four extra matrices. So whereas
altruism can increase cheating and direct supervision can decrease it, altruistic
cheating overpowers the supervisory effect when people are put together in a
setting where they have a chance to socialize and be observed.
LONG-TERM RELATIONSHIPS
Most of us tend to think that the longer we are in a relationship with
our doctors, accountants, financial advisers, lawyers, and so on, the
more likely it is that they will care more deeply about our well-being,
and as a consequence, they will more likely put our needs ahead of
their own. For example, imagine that you just received a (nonterminal)
diagnosis from your physician and you are faced with two treatment
options. One is to start an aggressive, expensive therapy; the other is to
wait awhile and see how your body deals with the problem and how it
progresses (“watchful waiting” is the official term for this). There is not
a definite answer as to which of the two options is better for you, but it
is clear that the expensive, aggressive one is better for your physician’s
pocket. Now imagine that your physician tells you that you should pick
the aggressive treatment option and that you should schedule it for
next week at the latest. Would you trust his advice? Or would you take
into account what you know about conflicts of interests, discount his
advice, and maybe go for a second opinion? When faced with such
dilemmas, most people trust their service providers to a very high
degree and we are even more likely to trust them the longer we have
known them. After all, if we have known our advisers for many years,
wouldn’t they start caring about us more? Wouldn’t they see things
from our perspective and give us better advice?
Another possibility, however, is that as the relationship extends and
grows, our paid advisers—intentionally or not—become more
comfortable recommending treatments that are in their own best
interest. Janet Schwartz (the Tulane professor who, along with me,
enjoyed dinner with the pharmaceutical reps), Mary Frances Luce (a
professor at Duke University), and I tackled this question, sincerely
hoping that as relationships between clients and service providers
deepened, professionals would care more about their clients’ welfare
and less about their own. What we found, however, was the opposite.
We examined this question by analyzing data from millions of
dental procedures over twelve years. We looked at instances when
patients received fillings and whether the fillings were made of silver
amalgam or white composite. You see, silver fillings last longer, cost
less, and are more durable; white fillings, on the other hand, are more
expensive and break more easily but are more aesthetically pleasing. So
when it comes to our front teeth, aesthetics often reign over
practicality, making white fillings the preferred option. But when it
comes to our less visible back teeth, silver fillings are the way to go.
3
What we found was that about a quarter of all patients receive
attractive and expensive white fillings in their hidden teeth rather than
the functionally superior silver fillings. In those cases, it was most likely
that the dentists were making decisions that favored their own interests
(higher initial pay and more frequent repairs) over the patients’
interests (lower cost and longer-lasting treatment).
As if that weren’t bad enough, we also found that this tendency is
more pronounced the longer the patient sees the same dentist (we
found the same pattern of results for other procedures as well). What
this suggests is that as dentists become more comfortable with their
patients, they also more frequently recommend procedures that are in
their own financial interest. And long-term patients, for their part, are
more likely to accept the dentist’s advice based on the trust that their
relationship has engendered.
*
The bottom line: there are clearly many benefits to continuity of
care and ongoing patient-provider relationships. Yet, at the same time,
we should also be aware of the costs these long-term relationships can
have.
HERE’S WHAT WE’VE learned about collaborative cheating so far:
BUT WAIT, THERE’S MORE! In our initial experiments, both the cheater and the
partner benefited from every additional exaggeration of their score. So if you
were the cheater in the experiment and you exaggerated the number of your
correct responses by one, you would get half of the additional payment and your
partner would get the same. This is certainly less financially rewarding than
snagging the whole amount for yourself, but you would still benefit from your
exaggeration to some degree.
To look into purely altruistic cheating, we introduced a condition in which
the fruit of each participant’s cheating would benefit only their partner. What did
we find? As it turns out, altruism is indeed a strong motivator for cheating.
When cheating was carried out for purely altruistic reasons and the cheaters
themselves did not gain anything from their act, overclaiming increased to an
even larger degree.
Why might this be the case? I think that when both we and another person
stand to benefit from our dishonesty, we operate out of a mix of selfish and
altruistic motives. In contrast, when other people, and only other people, stand to
benefit from our cheating, we find it far easier to rationalize our bad behavior in
purely altruistic ways and subsequently we further relax our moral inhibitions.
After all, if we are doing something for the pure benefit of others, aren’t we
indeed a little bit like Robin Hood?
*
FINALLY, IT IS worthwhile to say something more explicit about performance in
the many control conditions that we had in this set of experiments. For each of
our cheating conditions (individual shredder, group with shredder, distant group
with shredder, friendly group with shredder, altruistic payoff with shredder), we
also had a control condition in which there was no opportunity to cheat (that is,
no shredder). Looking across these many different control conditions allowed us
to see if the nature of collaboration influenced the level of performance. What
we found was that performance was the same across all of these control
conditions. Our conclusion? It seems that performance doesn’t necessarily
improve when people work in groups—at least not as much as we’ve all been led
to believe.
OF COURSE, WE cannot survive without the help of others. Working together is a
crucial element of our lives. But clearly, collaboration is a double-edged sword.
On the one hand, it increases enjoyment, loyalty, and motivation. On the other
hand, it carries with it the increased potential for cheating. In the end—and very
sadly—it may be that the people who care the most about their coworkers end up
cheating the most. Of course, I am not advocating that we stop working in
groups, stop collaborating, or stop caring about one another. But we do need to
recognize the potential costs of collaboration and increased affinity.
The Irony of Collaborative Work
If collaboration increases dishonesty, what can we do about it? One obvious
answer is to increase monitoring. In fact, this seems to be the default response of
the government’s regulators to every instance of corporate misconduct. For
example, the Enron fiasco brought about a large set of reporting regulations
known as the Sarbanes-Oxley Act, and the financial crisis of 2008 ushered in an
even larger set of regulations (largely emerging from the Dodd-Frank Wall
Street Reform and Consumer Protection Act), which were designed to regulate
and increase the supervision of the financial industry.
To some degree, there is no question that monitoring can be helpful, but it is
also clear from our results that increased monitoring alone is unlikely to
completely overcome our ability to justify our own dishonesty—particularly
when others stand to gain from our misbehavior (not to mention the high
financial costs of compliance with such regulations).
In some cases, instead of adding layers and layers of rules and regulations,
perhaps we could set our sights on changing the nature of group-based
collaboration. An interesting solution to this problem was recently implemented
in a large international bank by a former student of mine named Gino. To allow
his team of loan officers to work together without risking increased dishonesty
(for example, by recording the value of the loans as higher than they really were
in an effort to show larger short-run profits), he set up a unique supervisory
system. He told his loan officers that an outside group would review their
processing and approval of loan applications. The outside group was socially
disconnected from the loan-making team and had no loyalty or motivation to
help out the loan officers. To make sure that the two groups were separated,
Gino located them in different office buildings. And he ensured that they had no
direct dealings with each other or even knew the individuals in the other group.
I tried to get the data from Gino in order to evaluate the success of his
approach, but the lawyers of this large bank stopped us. So, I don’t know
whether this approach worked or how his employees felt about the arrangement,
but I suspect that this mechanism had at least some positive outcomes. It
probably decreased the fun that the loan work group had during their meetings. It
likely also increased the stress surrounding the groups’ decisions, and it was
certainly not cheap to implement. Nevertheless, Gino told me that overall,
adding the objective and anonymous monitoring element seemed to have a
positive effect on ethics, morals, and the bottom line.
CLEARLY, THERE ARE no silver bullets for the complex issue of cheating in group
settings. Taken together, I think that our findings have serious implications for
organizations, especially considering the predominance of collaborative work in
our day-to-day professional lives. There is also no question that better
understanding the extent and complexity of dishonesty in social settings is rather
depressing. Still, by understanding the possible pitfalls involved in collaboration,
we can take some steps toward rectifying dishonest behavior.
CHAPTER 10
A Semioptimistic Ending
People Don’t Cheat Enough!
Throughout this book, we’ve seen that honesty and dishonesty are based on a
mixture of two very different types of motivation. On the one hand, we want to
benefit from cheating (this is the rational economic motivation), while on the
other, we want to be able to view ourselves as wonderful human beings (this is
the psychological motivation). You might think that we can’t achieve both of
these objectives at the same time—that we can’t have our cake and eat it too, so
to speak—but the fudge factor theory we have developed in these pages suggests
that our capacity for flexible reasoning and rationalization allows us to do just
that. Basically, as long as we cheat just a little bit, we can have the cake and eat
(some of) it too. We can reap some of the benefits of dishonesty while
maintaining a positive image of ourselves.
As we’ve seen, certain forces—such as the amount of money we stand to
gain and the probability of being caught—influence human beings surprisingly
less than one might think. And at the same time other forces influence us more
than we might expect: moral reminders, distance from money, conflicts of
interest, depletion, counterfeits, reminders of our fabricated achievements,
creativity, witnessing others’ dishonest acts, caring about others on our team,
and so on.
ALTHOUGH THE FOCUS of the various experiments presented here was on
dishonesty, it is also important to remember that most of the participants in our
experiments were nice people from good universities who will likely attain
positions of some power and influence later on in life. They were not the kind of
people one typically associates with cheating. In fact, they were just like you,
me, and most of the people on this planet, which means that all of us are
perfectly capable of cheating a little bit.
Though that may sound pessimistic, the half-full part of the story is that
human beings are, by and large, more moral than standard economic theory
predicts. In fact, seen from a purely rational (SMORC) perspective, we humans
don’t cheat nearly enough. Consider how many times in the last few days you’ve
had the opportunity to cheat without getting caught. Perhaps a colleague left her
purse on her desk while she was away for a long meeting. Maybe a stranger in a
coffee shop asked you to watch her laptop while she went to the restroom.
Maybe a grocery clerk missed an item in your cart or you passed an unlocked
bicycle on an empty street. In any of those situations, the SMORC thing to do
would be to take the money, laptop, or bike or not mention the missed item. Yet
we pass up the vast majority of these opportunities every day without thinking
that we should take them. This means that we’re off to a good start in our effort
to improve our moral fiber.
What About “Real” Criminals?
Across all of our experiments we’ve tested thousands of people, and from time
to time, we did see aggressive cheaters who keep as much money as possible. In
the matrix experiment, for example, we have never seen anyone claim to solve
eighteen or nineteen out of the twenty matrices. But once in a while, a
participant claimed to have solved all twenty matrices correctly. These are the
people who, having made a cost-benefit analysis, decided to get away with as
much money as possible. Fortunately, we didn’t encounter many of those folks,
and because they seemed to be the exception and not the rule, we lost only a few
hundred dollars to them. (Not exactly thrilling, but not too bad.) At the same
time, we had thousands and thousands of participants who cheated by “just” a
few matrices, but because there were so many of them, we lost thousands and
thousands of dollars to them—much, much more than we lost to the aggressive
cheaters.
I suspect that in terms of my financial losses to the aggressive and to the
small cheaters, our experiments are indicative of dishonesty in society at large.
Very few people steal to a maximal degree. But many good people cheat just a
little here and there by rounding up their billable hours, claiming higher losses
on their insurance claims, recommending unnecessary treatments, and so on.
Companies also find many ways to cheat a little bit. Think about credit card
companies that raise interest rates ever so slightly for no apparent reason and
invent all kinds of hidden fees and penalties (which are often referred to, within
companies, as “revenue enhancements”). Think about banks that slow down
check processing so that they can hold on to our money for an extra day or two
or charge exorbitant fees for overdraft protection and for using ATMs. All of this
means that although it is obviously important to pay attention to flagrant
misbehaviors, it is probably even more important to discourage the small and
more ubiquitous forms of dishonesty—the misbehaviors that affect all of us most
of the time—both as perpetrators and as victims.
A Word About Cultural Differences
I travel a lot, which means that I get to meet people from all over the world, and
when I do, I often ask them about honesty and morality in their countries. As a
result, I’m beginning to understand how cultural differences—whether regional,
national, or corporate—contribute to dishonesty.
If you grew up outside the United States, think about this for a minute: do
people from your home country cheat more or less than Americans do? After
asking many people from various countries this question, I’ve discovered that
people have very strong beliefs about cheating in their own countries, and most
believe that people in their home country cheat more than Americans do (with
the somewhat predictable exception of people from Canada and the Nordic
countries).
Understanding that these are only subjective impressions, I was curious to
see whether there really was something to them. So I decided to test some of
these cultural perceptions more directly. In order to explore cultural differences,
we first had to come up with a way to equate the financial incentives across the
various locations. If we always paid, for example, an amount equivalent to $1 for
a correctly solved question, this would range from being a very high payment in
some places to a rather low one in others. Our first idea of how to equate the size
of the incentives was to use a product that would be internationally recognized,
such as a McDonald’s hamburger. Following this approach, for each matrix
solved correctly, participants could receive one-quarter of the cost of a
McDonald’s hamburger in that location. (This approach assumed that the people
setting prices at McDonald’s understand the economic buying power in each
location and set their prices accordingly.)
In the end we decided on a related approach and used the “beer index.” We
set up shop in local bars and paid participants one-quarter of the cost of a pint of
beer for every matrix that they claimed to have solved. (To make sure that our
participants were sober, we only approached bargoers as they were entering the
bar.)
BECAUSE I GREW up in Israel, I especially wanted to see how Israelis measured
up (I admit that I suspected that Israelis would cheat more than Americans). But
as it turned out, our Israeli participants cheated in the matrix experiments just as
much as the Americans. We decided to check other nationalities, too. Shirley
Wang, one of my Chinese collaborators, was convinced that Chinese people
would cheat more than Americans. But again, the Chinese showed the same
levels of dishonesty. Francesca Gino, from Italy, was positive that Italians would
cheat the most. “Come to Italy, and we will show you what cheating is all
about,” she said in her fantastic accent. But she was proven wrong too. We
discovered the same results in Turkey, Canada, and England. In fact, the amount
of cheating seems to be equal in every country—at least in those we’ve tested so
far.
How can we reconcile the fact that our experiments don’t show any real
differences in dishonesty among various countries and cultures with the very
strong personal conviction that people from different countries cheat to different
degrees? And how can we reconcile the lack of differences we see in our results
with the clear differences in corruption levels among countries, cultures, and
continents? I think that both perspectives are correct. Our data reflect an
important and real aspect of cheating, but so do cultural differences. Here’s why.
Our matrix test exists outside any cultural context. That is, it’s not an
ingrained part of any social or cultural environment. Therefore, it tests the basic
human capacity to be morally flexible and reframe situations and actions in ways
that reflect positively on ourselves. Our daily activities, on the other hand, are
entwined in a complex cultural context. This cultural context can influence
dishonesty in two main ways: it can take particular activities and transition them
into and out of the moral domain, and it can change the magnitude of the fudge
factor that is considered acceptable for any particular domain.
Take plagiarism, for example. At American universities, plagiarism is taken
very seriously, but in other cultures it is viewed as a kind of poker game between
the students and faculty. In those cultures getting caught, rather than the act of
cheating itself, is viewed negatively. Similarly, in some societies, different kinds
of cheating—not paying taxes, having an affair, downloading software illegally,
and running red lights when there is no traffic around—are frowned upon, while
in other societies the same activities are viewed as neutral or even confer
bragging rights.
Of course, there’s a great deal more to learn about the influence of culture on
cheating, both in terms of the societal influences that help curb dishonesty and in
terms of the social forces that make dishonesty and corruption more likely.
P.S. I SHOULD point out that throughout all of our cross-cultural experiments,
there was one time we did find a difference. At some point Racheli Barkan and I
carried out our experiment in a bar in Washington, D.C., where many
congressional staffers gather. And we carried out the same experiment in a bar in
New York City where many of the customers are Wall Street bankers. That was
the one place where we found a cultural difference. Who do you think cheated
more, the politicians or the bankers? I was certain that it was going to be the
politicians, but our results showed the opposite: the bankers cheated about twice
as much. (But before you begin suspecting your banker friends more and your
politician friends less, you should take into account that the politicians we tested
were junior politicians—mainly congressional staffers. So they had plenty of
room for growth and development.)
CHEATING AND INFIDELITY
Of course, no book about cheating would be complete if it didn’t
contain something about adultery and the kinds of complex and
intricate subterfuges that extramarital relationships inspire. After all,
in the popular vernacular, cheating is practically synonymous with
infidelity.
In fact, infidelity can be considered one of the main sources of the
world’s most dramatic entertainment. If modern-day adulterers such
as Liz Taylor, Prince Charles, Tiger Woods, Eliot Spitzer, Arnold
Schwarzenegger, and many others hadn’t cheated on their spouses, the
tabloid magazine and various entertainment news outlets would
probably go belly-up (so to speak).
In terms of the fudge factor theory, infidelity is most likely the
prototypical illustration of all the characteristics of dishonesty that we
have been talking about. To start with, it is the poster child (or at least
one of them) of a behavior that does not stem from a cost-benefit
analysis. I also suspect that the tendency toward infidelity depends to a
great extent on being able to justify it to ourselves. Starting with one
small action (maybe a kiss) is another force that can lead to deeper
kinds of involvement over time. Being away from the usual day-to-day
routine, for example on a tour or a set, where the social rules are not as
clear, can further enhance the ability to self-justify infidelity. And
creative people, such as actors, artists, and politicians—all known for a
tendency to be unfaithful—are likely to be more adept at spinning
stories about why it’s all right or even desirable for them to behave
that way. And similar to other types of dishonesty, infidelity is
influenced by the actions of those around us. Someone who has a lot of
friends and family who have had affairs will likely be influenced by
that exposure.
With all of this complexity, nuance, and social importance, you
might wonder why there isn’t a chapter in this book about infidelity
and why this rather fascinating topic is relegated to one small section.
The problem is data. I generally like to stick to conclusions I can draw
from experiments and data. Conducting experiments on infidelity
would be nearly impossible, and the data by their very nature are
difficult to estimate. This means that for now we are left to speculate—
and only speculate—about infidelity.
What Should We Do Next?
So here we are, surrounded by dishonesty. As one Apoth E. Cary put it in 1873:
Swindle, swindle, everywhere,
Every shape and size;
Take the swindle out of a man,
And you’ve nothing left but lies.
Philanthropy is made to cover a fraud,
Charity keeps humbugs in tow;
And we’re swindled at home, swindled abroad,
And swindled wherever we go.
For the world is full of humbugs
Managed by dishonest men;
One moves on, another comes,
And we’re swindled again and again.
—APOTH E. CARY, “RECOLLECTIONS OF THE SWINDLE FAMILY”
1
As we have seen, we are all capable of cheating, and we are very adept at
telling ourselves stories about why, in doing so, we are not dishonest or immoral.
Even worse, we are prone to “catch” the cheating bug from other people, and
once we start acting dishonestly, we are likely to continue misbehaving that way.
So what should we do about dishonesty? We recently experienced a
tremendous financial crisis, which has provided an excellent opportunity to
examine human failure and the role that irrationality plays in our lives and in
society at large. In response to this man-made disaster, we’ve taken some steps
toward coming to terms with some of our irrational tendencies, and we’ve begun
reevaluating our approach to markets accordingly. The temple of rationality has
been shaken, and with our improved understanding of irrationality we should be
able to rethink and reinvent new kinds of structures that will ultimately help us
avoid such crises in the future. If we don’t do this, it will have been a wasted
crisis.
MEMENTO MORI
There are a lot of possible connections one can draw between Roman
times and modern-day banking, but perhaps the most important of
them is memento mori. At the peak of Rome’s power, Roman generals
who had won significant victories marched through the middle of the
city displaying their spoils. The marching generals wore purple-andgold ceremonial robes, a crown of laurels, and red paint on their face
as they were carried through the city on a throne. They were hailed,
celebrated, and admired. But there was one more element to the
ceremony: throughout the day a slave walked next to the general, and
in order to prevent the victorious general from falling into hubris, the
slave whispered repeatedly into his ear, “Memento mori,” which means
“Remember your mortality.”
If I were in charge of developing a modern version of the phrase, I
would probably pick “Remember your fallibility” or maybe
“Remember your irrationality.” Whatever the phrase is, recognizing
our shortcomings is a crucial first step on the path to making better
decisions, creating better societies, and fixing our institutions.
THAT SAID, OUR next task is to try to figure out more effective and practical ways
to combat dishonesty. Business schools include ethics classes in their curricula,
companies make employees sit through seminars on the code of conduct, and
governments have disclosure policies. Any casual observer of the state of
dishonesty in the world will quickly realize that such measures don’t get the job
done. And the research presented here suggests that such Band-Aid approaches
are doomed to fail for the very simple reason that they don’t take into account
the psychology of dishonesty. After all, every time policies or procedures are
created to prevent cheating, they target a certain set of behaviors and motivations
that need to change. And generally when interventions are set forth, they assume
that the SMORC is at play. But as we have seen, this simple model has little to
do with the driving forces behind cheating.
If we are really interested in curbing cheating, what interventions should we
try? I hope it is clear by now that if we are to stand a chance of curbing
dishonesty, we must start with an understanding of why people behave
dishonestly in the first place. With this as a starting point, we can come up with
more effective remedies. For example, based on our knowledge that people in
general want to be honest but are also tempted to benefit from dishonesty, we
could recommend reminders at the moment of temptation, which, as we’ve seen,
are surprisingly effective. Similarly, understanding how conflicts of interest
work and how deeply they influence us makes it clear that we need to avoid and
regulate conflicts of interest to a much higher degree. We also need to
understand the effects that the environment, as well as mental and physical
depletion, plays in dishonesty. And of course, once we understand the social
infectiousness of dishonesty, we could take a cue from the Broken Windows
Theory to combat the social contagion of cheating.
INTERESTINGLY, WE ALREADY have many social mechanisms in place that seem
to be designed specifically for resetting our moral compass and overcoming the
“what-the-hell” effect. Such resetting rituals—ranging from the Catholic
confession to Yom Kippur, and Ramadan to the weekly Sabbath—all present us
with opportunities to collect ourselves, stop the deterioration, and turn a new
page. (For the nonreligious, think of New Year’s resolutions, birthdays, changes
of job, and romantic breakups as “resetting” opportunities.) We have recently
started carrying out basic experiments on the effectiveness of these types of
resetting approaches (using a nonreligious version of the Catholic confession),
and so far it seems that they can rather successfully reverse the what-the-hell
effect.
From the social science perspective, religion has evolved in ways that can
help society counteract potentially destructive tendencies, including the tendency
to be dishonest. Religion and religious rituals remind people of their obligations
to be moral in various ways; recall, for example, the Jewish man with the tzitzit
from chapter 2 (“Fun with the Fudge Factor”). Muslims use beads called tasbih
or misbaha on which they recount the ninety-nine names of God several times a
day. There’s also daily prayer and the confessional prayer (“Forgive me, Father,
for I have sinned”), the practice of prayaschitta in Hinduism, and countless other
religious reminders that work very much as the Ten Commandments did in our
experiments.
To the extent that such approaches are useful, we might think about creating
related (albeit nonreligious) mechanisms in business and politics. Maybe we
should get our public servants and businesspeople to take an oath, use a code of
ethics, or even ask for forgiveness from time to time. Perhaps such secular
versions of repentance and appeal for forgiveness would help potential cheaters
pay attention to their own actions, turn a new page, and by doing so increase
their moral adherence.
ONE OF THE more intriguing forms of resetting ceremonies is the purification
rituals that certain religious sects practice. One such group is Opus Dei, a
secretive Catholic society, in which members flagellate themselves with cattail
whips. I don’t remember exactly how we started discussing Opus Dei, but, at
some point Yoel Inbar (a professor at Tilburg University), David Pizarro and
Tom Gilovich (both from Cornell University), and I wondered if self-flagellation
and similar behaviors capture a basic human desire for self-cleansing. Can the
feeling of having done something wrong be erased by self-punishment? Can
self-inflicted pain help us ask for forgiveness and start anew?
Following the physically painful approach of Opus Dei, we decided to
conduct an experiment using a more modern and less bloody version of cattail
whips—so we picked mildly painful electric shocks as our experimental
material. Once participants came to the lab at Cornell University, we asked some
of them to write about a past experience that made them feel guilty; we asked
other participants to write about a past experience that made them feel sad (a
negative emotion but not related to guilt); and we asked a third group to write
about an experience that made them feel neither good nor bad. After they
reflected on one of these three types of experiences, we asked the participants to
take part in “another” experiment involving self-administered electrical shocks.
In this next phase of the experiment, we connected the participant’s wrist to
a shock-generating machine. Once the connection was secure, we showed the
participants how to set the level of the electrical shock and which button to press
to give themselves the painful jolt. We set the machine to the lowest possible
level of shock and asked participants to press the switch, increase the level of the
shock, press the switch, increase the level of the shock, press the switch, and so
on until they could no longer tolerate the intensity of the shock.
We really aren’t as sadistic as it might sound, but we wanted to see how far
participants would push themselves on the pain scale and to what extent their
level of self-administered pain would depend on the experimental condition they
were in. Most important, we wanted to see whether being reminded of a guiltrelated past experience would cause our participants to cleanse themselves by
seeking more pain. As it turned out, in the neutral and sad conditions, the degree
of self-inflicted pain was similar and rather low, which means that negative
emotions by themselves do not create a desire for self-inflicted pain. However,
those in the guilty condition were far more disposed to self-administering higher
levels of shocks.
As difficult as it might be to appreciate this experimental support for the
practice of Opus Dei, the results suggest that purification through the pain of
self-flagellation might tap into a basic way we deal with feelings of guilt.
Perhaps recognizing our mistakes, admitting them, and adding some form of
physical punishment is a good recipe for asking forgiveness and opening a new
page. Now, I am not recommending that we adopt this approach just yet, but I
can think of some politicians and businessmen whom I would not mind trying it
out on—just to see if it works.
A MORE SECULAR (and more elegant) example of resetting was told to me by a
woman I met at a conference a few years ago. The woman’s sister lived in South
America, and one day the sister realized that her maid had been stealing a little
bit of meat from the freezer every few days. The sister didn’t mind too much
(other than the fact that sometimes she didn’t have enough meat to make dinner,
which became rather frustrating), but she clearly needed to do something about
it. The first part of her solution was to put a lock on the freezer. Then the sister
told her maid that she suspected that some of the people who were working at
the house from time to time had been taking some meat from the freezer, so she
wanted only the two of them to have keys. She also gave her maid a small
financial promotion for the added responsibility. With the new role, the new
rules, and the added control, the stealing ceased.
I think this approach worked for a number of reasons. I suspect that the
maid’s habit of stealing developed much like the cheating we’ve been
discussing. Perhaps it began with a single small action (“I’ll just take a little bit
of meat while I’m cleaning up”), but having stolen once, it became much easier
to continue doing so. By locking the freezer and giving the maid an additional
responsibility, the sister offered the maid a way to reset her honesty level. I also
think that trusting the maid with the key was an important element in changing
her view on stealing meat and in establishing the social norm of honesty in that
household. On top of that, now that a key was needed to open the freezer, any
act of stealing would have to be more deliberate, more intentional, and far more
difficult to self-justify. That is not unlike what happened when we forced
participants to deliberately move the mouse to the bottom of the computer screen
to reveal an answer key (as we saw in chapter 6, “Cheating Ourselves”).
The point is that the more we develop and adopt such mechanisms, the more
we will be able to curb dishonesty. It is not always going to be simple, but it is
possible.
IT’S IMPORTANT TO note that creating an endpoint and the opportunity for a new
beginning can take place on a broader social scale. The Truth and Reconciliation
Commission in South Africa is an example of this kind of process. The purpose
of this courtlike commission was to enable the transition from the apartheid
government, which had sharply oppressed the vast majority of South Africans
for decades, to a new beginning and to democracy. Similar to other methods of
stopping negative behavior, pausing, and starting again, the goal of the
commission was reconciliation, not retribution. I’m sure that no one would claim
that the commission erased all memories and remnants of the apartheid era or
that anything as deeply scarring as apartheid could ever be forgotten or fully
healed. But it remains an important example of how acknowledging bad
behavior and asking for forgiveness can be an important step in the right
direction.
FINALLY, IT IS worth trying to examine what we have learned about dishonesty
from a broader perspective and see what it can teach us about rationality and
irrationality more generally. Through the different chapters, we have seen that
there are rational forces that we think drive our dishonest behavior—but don’t.
And there are irrational forces that we think don’t drive our dishonest behavior
—but do. This inability to recognize which forces are at work and which are
irrelevant is something we consistently see in decision making and behavioral
economics research.
Viewed from this perspective, dishonesty is a prime example of our
irrational tendencies. It’s pervasive; we don’t instinctively understand how it
works its magic on us; and, most important, we don’t see it in ourselves.
The good news in all of this is that we are not helpless in the face of our
human foibles (dishonesty included). Once we better understand what really
causes our less-than-optimal behavior, we can start to discover ways to control
our behavior and improve our outcomes. That is the real goal of social science,
and I am sure that the journey will only become more important and interesting
in the years to come.
Irrationally yours,
Dan Ariely
If your ereading device does not support color, this experiment won’t work – go
to the online color version at http://danariely.com/stroop/
If your ereading device does not support color, this experiment won’t work – go
to the online color version at http://danariely.com/stroop/
List of Collaborators
Aline Grüneisen
Aline joined my research team soon after I moved to Duke, and she has been a
major force of energy and excitement ever since. I am not sure if this is part of
her plan, but over time I have found myself depending on her to a larger and
larger degree. Aline and I have been working together on a broad range of
topics, and the unifying theme of all of them is that they are innovative and fun.
Aline is currently the lab manager of the Center for Advanced Hindsight at Duke
University, and I hope she will continue working with me for many more years.
Ayelet Gneezy
I met Ayelet many years ago at a picnic organized by mutual friends. I had a
very positive first impression of her, and my appreciation of her has only
increased with time. Ayelet is a wonderful person and a great friend, so it is a bit
odd that the topics we decided to collaborate on were mistrust and revenge.
Whatever initially drove us to explore these topics ended up being very useful,
both academically and personally. Ayelet is currently a professor at the
University of California, San Diego.
David Pizarro
David and I first met at an academic summer retreat at Stanford University. We
shared a wall between our offices, and that was my first real introduction to rap
music. A few weeks into it, I started enjoying the music, and David was kind
enough to share his music collection with me (not sure how legal this was). Over
the years I have gotten to spend a lot of time with David, and I always learn a
lot, get energized, and wish I had more time with him. David is currently a
professor at Cornell University.
Eynav Maharabani
I met Eynav in one of my visits to Israel. At the time she was a graduate student
who just started working with Racheli Barkan. I was very impressed with her
mix of intelligence, politeness, and assertiveness from the get-go, and it is the
mix of these abilities that made her such a wonderful collaborator. Eynav is
currently working at Abilities Solution, a unique company that focuses on
employing people with disabilities for high-tech companies.
Francesca Gino
Francesca is a rare combination of kindness, caring, knowledge, creativity, and
style. She also has endless energy and enthusiasm, and the number of projects
she is involved with at any one time is generally what other people do in a
lifetime. As an Italian, she is also one of the best people to share a meal and
wine with. It was a deeply sad day for me when she decided to move from North
Carolina to Boston. Francesca is currently a professor at Harvard University.
Janet Schwartz
I was lucky enough to tempt Janet to spend a few years with me at the Center for
Advanced Hindsight. Janet is particularly interested in irrationalities related to
health care (of which there are many), and together we have explored eating,
dieting, advice, conflicts of interests, second opinions, and different approaches
to getting people to behave as if they cared about their long-term health. Janet
has a keen sense of observation about the world around her, and she is a fantastic
storyteller, making fun of herself and everyone around her. Janet is currently a
professor at Tulane University, but in spirit she is still at The Center.
Lisa Shu
Lisa is as bright as she is fun to be with. She has a sort of sixth sense for food,
good research ideas, and fashion. These qualities make her not only a perfect
collaborator but also a great shopping partner. In addition to studying ethical
behavior she is interested in negotiation. And although I have never had the
opportunity to personally negotiate with her, I have no doubt that if I did I would
lose badly. Lisa is currently a PhD student at Harvard University.
Mary Frances Luce
Mary Frances was a PhD student at Duke a few years ahead of me and came
back to Duke as a faculty member, also a few years ahead of me. Naturally this
has made her a good source for advice over the years, and she has always been
very supportive and helpful. A few years ago she moved to the dean’s office, and
both for my own sake and for the sake of the school, I hope that I am not going
to continue following in her footsteps. Mary Frances is currently a professor at
Duke University.
Maurice Schweitzer
Maurice finds almost anything around him interesting, and he approaches new
projects with a big smile and great curiosity. For years now he has told me that
he is a good squash player, and though I want to personally check how good he
really is, I am also a bit worried that I will find out that he is much better than
me. Maurice is also always a good source of wisdom on work, family, and life.
Maurice is currently a professor at the University of Pennsylvania.
Max Bazerman
Max is insightful about pretty much any topic that comes up in research, politics,
and personal life. And he always has something unexpected and interesting to
say. After finding out that many of his students solve their own dilemmas and
make decisions by asking themselves, “What would Max do?,” I tried this
approach a few times myself and can attest to its usefulness. Max is currently a
professor at Harvard University.
Michael Norton
Mike is an interesting mix of brilliance, self-deprecation, and a sarcastic sense of
humor. He has a unique perspective on life, and he finds almost any topic
interesting. Mike is a great person to bounce ideas off of, and his feedback is
always a mix of wacky, unexpected, insightful, and constructive. I often think
about research projects as journeys, and with Mike I get to go on adventures that
would be impossible with anyone else. Mike is currently a professor at Harvard
University.
Nicole Mead
I first met Nicole when she was a graduate student at Florida State University. It
was late, after a lecture I gave, and we ended up drinking a bit too much. I
remember that I was very impressed with the ideas we were exchanging, but at
some point I asked Nicole whether she thought that they were really good ideas
or if it was the alcohol. Nicole assured me that it was not the alcohol, and I think
she was mostly correct. Nicole has had many good ideas then and since, and she
is currently a professor at Católica-Lisbon in Portugal.
Nina Mazar
Nina first came to MIT for a few days to get feedback on her research and ended
up staying for five years. During this time we had oodles of fun working
together and I came to rely on her greatly. Nina is impervious to obstacles, and
her willingness to take on large challenges led us to carry out some particularly
difficult experiments in rural India. For many years I hoped that she would never
decide to leave, but, alas, the time came. She is currently a professor at the
University of Toronto. In an alternate reality, Nina is a high-fashion designer in
Milan.
On Amir
On joined MIT as a PhD student a year after I joined as a new professor and
became “my” first student. In that capacity, he had a tremendous role in shaping
what I expect from students and how I see the professor-student relationship. In
addition to being exceptionally smart, On has an amazing set of skills, and what
he does not know he is able to learn within a day or two. It is always exciting to
work and spend time with him. On is currently a professor at the University of
California, San Diego.
Racheli Barkan
Racheli (Rachel) and I became friends many years ago when we were both
graduate students. Over the years we talked about starting various research
projects together, but we really only got started when she came to spend a year at
Duke. As it turned out, coffee is an important ingredient for translating ideas into
action, and we had lots of fun during her visit and made a lot of progress on a
wide range of projects. Racheli is incredibly knowledgeable, smart, and
insightful, and I only wish we had more time together. Racheli is currently a
professor at Ben-Gurion University of the Negev in Israel.
Roy Baumeister
Roy is a unique mixture of philosopher, musician, poet, and keen observer of
human life. His interests span everything, and his perspective often looks
puzzling to me at first, but then I realize the wisdom in it and end up thinking
about his views for a long while—often adopting them. Roy is an ideal person to
travel and explore with. He is currently a professor at Florida State University.
Scott McKenzie
Scott was an enthusiastic Duke undergraduate when he joined the Center for
Advanced Hindsight. He was highly social and had a natural knack for getting
people to do what he wanted them to do, including participating in our studies.
When it was time for him to pick a topic for an independent research project, he
picked cheating in golf, and through the process I learned a lot about that noble
game. Scott is currently putting in the consulting world.
Shahar Ayal
I first met Shahar socially through common friends and then again when he was
studying for his PhD under the supervision of another friend. So when he
graduated, our personal and professional paths combined and he came to spend a
few years at the Center for Advanced Hindsight as a postdoctoral fellow. Over
those years we got to understand each other to a deeper level and think even
more alike (mostly for the better). Shahar is a delight to be with and work with,
and I am looking forward to many years of joint research. Shahar is currently a
professor at the Interdisciplinary Institute in Israel.
Tom Gilovich
When I was a PhD student, I attended one of Tom’s presentations, and I was
amazed by the quality of his thought and creativity. Tom has a unique ability to
ask important questions and find answers in interesting places. For example, he
has shown that teams with black uniforms receive more penalties than their
opponents; that basketball players don’t really get a “hot hand”; and that NBA
players miss more free throws when they don’t think they deserve the penalty. I
have always wanted to be a bit more like Tom. He is currently a professor at
Cornell University.
Yoel Inbar
I first met Yoel when he was a student of Tom Gilovich and David Pizarro, and
that is how we started working together. Yoel is the epitome of the modern
hipster—equal parts cool and geek with a deep knowledge of indie rock bands
(you probably haven’t heard of them) and UNIX. One of Yoel’s interests is
disgust, and he is an expert in finding interesting ways to disgust people (fart
spray, feces-shaped chocolate, odd foods, etc.). Yoel is currently a professor at
Tilburg University in the Netherlands.
Zoë Chance
Zoë is a force of creativity and kindness. Talking to her is a bit like being in an
amusement park—you know it is going to be exciting and interesting, but it is
hard to anticipate which direction her comments will take. Together with her
love of life and mankind, she is the ideal blend of researcher and friend. Zoë is
currently a postdoctoral fellow at Yale University.
Bibliography and Additional Readings
Introduction: Why Is Dishonesty So Interesting?
Based on
Tim Harford, The Logic of Life: The Rational Economics of an Irrational
World (New York: Random House, 2008).
Chapter 1. Testing the Simple Model of Rational Crime (SMORC)
Based on
Jerome K. Jerome, Three Men in a Boat (to Say Nothing of the Dog) (1889;
reprint, New York: Tom Doherty Associates, 2001).
Jeff Kreisler, Get Rich Cheating: The Crooked Path to Easy Street (New
York: HarperCollins, 2009).
Eynav Maharabani, “Honesty and Helping Behavior: Testing Situations
Involving Temptation to Cheat a Blind Person,” master’s thesis, BenGurion University of the Negev, Israel (2007).
Nina Mazar, On Amir, and Dan Ariely, “The Dishonesty of Honest People:
A Theory of Self-concept Maintenance,” Journal of Marketing
Research (2008).
Nina Mazar and Dan Ariely, “Dishonesty in Everyday Life and Its Policy
Implications,” Journal of Public Policy and Marketing (2006).
Chapter 2. Fun with the Fudge Factor
Based on
Nina Mazar, On Amir, and Dan Ariely, “The Dishonesty of Honest People:
A Theory of Self-concept Maintenance,” Journal of Marketing
Research (2008).
Lisa Shu, Nina Mazar, Francesca Gino, Max Bazerman, and Dan Ariely,
“When to Sign on the Dotted Line? Signing First Makes Ethics Salient
and Decreases Dishonest Self-Reports,” working paper, Harvard
Business School NOM Unit (2011).
Related readings
Jason Dana, Roberto A. Weber, and Jason Xi Kuang, “Exploiting Moral
Wiggle Room: Behavior Inconsistent with a Preference for Fair
Outcomes,” Economic Theory (2007).
Christopher K. Hsee, “Elastic Justification: How Tempting but TaskIrrelevant Factors Influence Decisions,” Organizational Behavior and
Human Decision Processes (1995).
Christopher K. Hsee, “Elastic Justification: How Unjustifiable Factors
Influence Judgments,” Organizational Behavior and Human Decision
Processes (1996).
Maurice Schweitzer and Chris Hsee, “Stretching the Truth: Elastic
Justification and Motivated Communication of Uncertain Information,”
The Journal of Risk and Uncertainty (2002).
Chapter 2b. Golf
Related readings
Robert L. Goldstone and Calvin Chin, “Dishonesty in Self-report of Copies
Made—Moral Relativity and the Copy Machine,” Basic and Applied
Social Psychology (1993).
Robert A. Wicklund, “The Influence of Self-awareness on Human
Behavior,” American Scientist (1979).
Chapter 3. Blinded by Our Own Motivations
Based on
Daylian M. Cain, George Loewenstein, and Don A. Moore, “The Dirt on
Coming Clean: The Perverse Effects of Disclosing Conflicts of
Interest,” Journal of Legal Studies (2005).
Ann Harvey, Ulrich Kirk, George H. Denfield, and P. Read Montague,
“Monetary Favors and Their Influence on Neural Responses and
Revealed Preference,” The Journal of Neuroscience (2010).
Related readings
James Bader and Daniel Shugars, “Agreement Among Dentists’
Recommendations for Restorative Treatment,” Journal of Dental
Research (1993).
Max H. Bazerman and George Loewenstein, “Taking the Bias Out of Bean
Counting,” Harvard Business Review (2001).
Max H. Bazerman, George Loewenstein, and Don A. Moore, “Why Good
Accountants Do Bad Audits: The Real Problem Isn’t Conscious
Corruption. It’s Unconscious Bias,” Harvard Business Review (2002).
Daylian M. Cain, George Loewenstein, and Don A. Moore, “When
Sunlight Fails to Disinfect: Understanding the Perverse Effects of
Disclosing Conflicts of Interest,” Journal of Consumer Research (in
press).
Carl Elliot, White Coat, Black Hat: Adventures on the Dark Side of
Medicine (Boston: Beacon Press, 2010).
Chapter 4. Why We Blow It When We’re Tired
Based on
Mike Adams, “The Dead Grandmother/Exam Syndrome and the Potential
Downfall of American Society,” The Connecticut Review (1990).
Shai Danziger, Jonathan Levav, and Liora Avnaim-Pesso, “Extraneous
Factors in Judicial Decisions,” Proceedings of the National Academy of
Sciences of the United States of America (2011).
Nicole L. Mead, Roy F. Baumeister, Francesca Gino, Maurice E.
Schweitzer, and Dan Ariely, “Too Tired to Tell the Truth: Self-Control
Resource Depletion and Dishonesty,” Journal of Experimental Social
Psychology (2009).
Emre Ozdenoren, Stephen W. Salant, and Dan Silverman, “Willpower and
the Optimal Control of Visceral Urges,” Journal of the European
Economic Association (2011).
Baba Shiv and Alexander Fedorikhin, “Heart and Mind in Conflict: The
Interplay of Affect and Cognition in Consumer Decision Making,” The
Journal of Consumer Research (1999).
Related readings
Roy F. Baumeister and John Tierney, Willpower: Rediscovering the
Greatest Human Strength (New York: The Penguin Press, 2011).
Roy F. Baumeister, Kathleen D. Vohs, and Dianne M. Tice, “The Strength
Model of Self-control,” Current Directions in Psychological Science
(2007).
Francesca Gino, Maurice E. Schweitzer, Nicole L. Mead, and Dan Ariely,
“Unable to Resist Temptation: How Self-Control Depletion Promotes
Unethical Behavior,” Organizational Behavior and Human Decision
Processes (2011).
C. Peter Herman and Janet Polivy, “A Boundary Model for the Regulation
of Eating,” Research Publications—Association for Research in
Nervous and Mental Disease (1984).
Walter Mischel and Ozlem Ayduk, “Willpower in a Cognitive-Affective
Processing System: The Dynamics of Delay of Gratification,” in
Handbook of Self-regulation: Research, Theory, and Applications,
edited by Kathleen D. Vohs and Roy F. Baumeister (New York:
Guilford, 2011).
Janet Polivy and C. Peter Herman, “Dieting and Binging, A Causal
Analysis,” American Psychologist (1985).
Chapter 5. Why Wearing Fakes Makes Us Cheat More
Based on
Francesca Gino, Michael I. Norton, and Dan Ariely, “The Counterfeit Self:
The Deceptive Costs of Faking It,” Psychological Science (2010).
Related readings
Dan Ariely and Michael L. Norton, “How Actions Create—Not Just Reveal
—Preferences,” Trends in Cognitive Sciences (2008).
Roy F. Baumeister, Kathleen D. Vohs, and Dianne M. Tice, “The Strength
Model of Self-control,” Current Directions in Psychological Science
(2007).
C. Peter Herman and Deborah Mack, “Restrained and Unrestrained Eating,”
Journal of Personality (1975).
Chapter 6. Cheating Ourselves
Based on
Zoë Chance, Michael I. Norton, Francesca Gino, and Dan Ariely, “A
Temporal View of the Costs and Benefits of Self-Deception,” Proceedings
of the National Academy of Sciences (2011).
Related readings
Ziva Kunda, “The Case for Motivated Reasoning,” Psychological Bulletin
(1990).
Danica Mijović-Prelec and Dražen Prelec, “Self-deception as SelfSignalling: A Model and Experimental Evidence,” Philosophical
Transactions of the Royal Society (2010).
Robert Trivers, “The Elements of a Scientific Theory of Self-Deception,”
Annals of the New York Academy of Sciences (2000).
Chapter 7. Creativity and Dishonesty: We Are All Storytellers
Based on
Edward J. Balleisen, “Suckers, Swindlers, and an Ambivalent State: A
History of Business Fraud in America,” manuscript.
Shane Frederick, “Cognitive Reflection and Decision Making,” Journal of
Economic Perspectives (2005).
Michael S. Gazzaniga, “Consciousness and the Cerebral Hemispheres,” in
The Cognitive Neurosciences, edited by Michael S. Gazzaniga
(Cambridge, Mass.: MIT Press, 1995).
Francesca Gino and Dan Ariely, “The Dark Side of Creativity: Original
Thinkers Can Be More Dishonest,” Journal of Personality and Social
Psychology (2011).
Ayelet Gneezy and Dan Ariely, “Don’t Get Mad, Get Even: On
Consumers’ Revenge,” working paper, Duke University (2010).
Richard Nisbett and Timothy DeCamp Wilson, “Telling More Than We
Can Know: Verbal Reports on Mental Processes,” Psychological
Review (1977).
Yaling Yang, Adrian Raine, Todd Lencz, Susan Bihrle, Lori Lacasse, and
Patrick Colletti, “Prefrontal White Matter in Pathological Liars,” The
British Journal of Psychiatry (2005).
Related readings
Jesse Preston and Daniel M. Wegner, “The Eureka Error: Inadvertent
Plagiarism by Misattributions of Effort,” Journal of Personality and
Social Psychology (2007).
Chapter 8. Cheating as an Infection: How We Catch the
Dishonesty Germ
Based on
Nicholas A. Christakis and James H. Fowler, Connected: The Surprising
Power of Our Social Networks and How They Shape Our Lives (New
York: Little, Brown, 2009).
Robert B. Cialdini, Influence: The Psychology of Persuasion (New York:
William Morrow, 1993).
Francesca Gino, Shahar Ayal, and Dan Ariely, “Contagion and
Differentiation in Unethical Behavior: The Effect of One Bad Apple on
the Barrel,” Psychological Science (2009).
George L. Kelling and James Q. Wilson, “Broken Windows: The Police
and Neighborhood Safety,” The Atlantic (March 1982).
Nina Mazar, Kristina Shampanier, and Dan Ariely, “Probabilistic Price
Promotions—When Retailing and Las Vegas Meet,” working paper,
Rotman School of Management, University of Toronto (2011).
Related readings
Ido Erev, Paul Ingram, Ornit Raz, and Dror Shany, “Continuous
Punishment and the Potential of Gentle Rule Enforcement,”
Behavioural Processes (2010).
Chapter 9. Collaborative Cheating: Why Two Heads Aren’t Necessarily
Better than One
Based on
Melissa Bateson, Daniel Nettle, and Gilbert Roberts, “Cues of Being
Watched Enhance Cooperation in a Real-World Setting,” Biology Letters
(2006).
Francesca Gino, Shahar Ayal, and Dan Ariely, “Out of Sight, Ethically
Fine? The Effects of Collaborative Work on Individuals’ Dishonesty,”
working paper (2009).
Janet Schwartz, Mary Frances Luce, and Dan Ariely, “Are Consumers Too
Trusting? The Effects of Relationships with Expert Advisers,” Journal
of Marketing Research (2011).
Related readings
Francesca Gino and Lamar Pierce, “Dishonesty in the Name of Equity,”
Psychological Science (2009).
Uri Gneezy, “Deception: The Role of Consequences,” American Economic
Review (2005).
Nina Mazar and Pankaj Aggarwal, “Greasing the Palm: Can Collectivism
Promote Bribery?” Psychological Science (2011).
Scott S. Wiltermuth, “Cheating More When the Spoils Are Split,”
Organizational Behavior and Human Decision Processes (2011).
Chapter 10. A Semioptimistic Ending: People Don’t Cheat Enough!
Based on
Rachel Barkan and Dan Ariely, “Worse and Worst: Daily Dishonesty of
Business-men and Politicians,” working paper, Ben-Gurion University
of the Negev, Israel (2008).
Yoel Inbar, David Pizarro, Thomas Gilovich, and Dan Ariely, “Moral
Masochism: Guilt Causes Physical Self-punishment,” working paper
(2009).
Azim Shariff and Ara Norenzayan, “Mean Gods Make Good People:
Different Views of God Predict Cheating Behavior,” International
Journal for the Psychology of Religion (2011).
Related readings
Keri L. Kettle and Gerald Häubl, “The Signature Effect: How Signing
One’s Name Influences Consumption-Related Behavior by Priming
Self-Identity,” Journal of Consumer Research (2011).
Deepak Malhotra, “(When) Are Religious People Nicer? Religious Salience
and the ‘Sunday Effect’ on Pro-Social Behavior,” Judgment and
Decision Making (2010).
Searchable Terms
The page numbers in this index relate to the printed version of this book; they do
not match the pages of your ebook. You can use your ebook reader’s search tool
to find a specific word or passage.
Abagnale, Frank, 173
academia:
conflicts of interest in, 82, 84–85
financial services industry’s influence in, 84–85
group-based projects in, 217–18
pharmaceutical companies’ influence in, 82
academic credentials, misrepresentation of, 135–36, 153, 154
accounting firms:
collaborative dishonesty in, 218–21
“in good faith” notion and, 219–20
Adam and Eve, 98
Adams, Mike, 107
advertising agencies, link between creativity and dishonesty in, 186–87
aesthetic preferences, impact of favors on, 75–77
Afghanistan War, 152
altruistic cheating, 222–23, 225–26, 232
supervisory effect and, 227–28
American Medical Association, 79
Amir, On, 15, 18, 31–32, 39, 262
Apple, 184
atheists, swearing on bible and, 40, 41, 42
Atlantic, 214–15
Austen, Jane, 154–55
Avnaim-Pesso, Liora, 102
Ayal, Shahar, 197, 225, 263
bacterial infections, 192–93
Balleisen, Ed, 188
bankers, cheating among politicians vs., 243
banks:
small misbehaviors of, 240
see also financial services industry
Barkan, Racheli, 21, 23, 262
Barlow, John Perry, 1, 2
baseball, steroids in, 156
Bateson, Melissa, 224
Baumeister, Roy, 100, 104, 262–63
Baylor College of Medicine, 75–77
Bazerman, Max, 45, 260
Becker, Gary, 3–4, 14, 26
Be’er Sheva, Israel, farmer’s market in, 23–24
being caught, probability of, 4–5, 13, 14, 27
varying, in matrix task, 20–22
benevolent behavior, 23–24
Bible, as moral reminder, 40, 41, 42
billable hours, overstating of, 35–37
blind customers, benevolent behavior toward, 23–26
brain:
higher connectivity in, 170
left-right split in, 164–65
of pathological liars, 169–70
Broken Windows Theory, 214–15, 249
businesspeople, self-monitoring of, 56–57
business schools, 248
group-based projects in, 217–18
cab drivers, benevolent behavior of, toward blind customer, 25–26
CAD/CAM equipment, in dentistry, 67–71
Cain, Daylian, 89
Canada, cheating in, 242
care for customers, in illegal businesses, 138–39
car mechanics, 93
Carnegie Mellon University, 197–207
car recommendation software, “fixing” answers in, 166–67
Cary, Apoth E., 246
cashless society, implications for dishonesty in, 34
Catch Me If You Can (Abagnale), 173
certificates for (false) achievements, 153–54
Chance, Zoë, 145, 264
charitable behavior, 23–24
cheating:
aggressive cheaters and, 239
altruistic, 222–23, 225–26, 227–28, 232
being made blatantly aware of, 156–57
being watched and, 223–25, 227
collaborative, see collaborative cheating
desire to benefit from, 12–14, 27, 29, 237
ego depletion, 104–6, 111–12
fake products’ impact on, 125–31
in golf, 55–65
honor codes and, 41–45
increasing creativity to increase level of, 184–87
as infection, 191–216; see also infectious nature of cheating
infidelity and, 244–45
on IQ-like tests, self-deception and, 145–49, 151, 153–54, 156–57
reducing amount of, 39–51, 248–54
removing oneself from tempting situation and, 108–11
signing forms at top and, 46–51
Ten Commandments and, 39–40, 41, 44
what-the-hell effect and, 127–31, 136
see also dishonesty
China, cheating in, 241–42
Chloé accessories, studies with, 123–34
Civil War veterans, 152
classes, infectious nature of cheating in, 195–97
Coca-Cola, stealing money vs., 32–33
cognitive dissonance, 81
cognitive load:
ability to resist temptation and, 99–100
judges’ parole rulings and, 102–3
Cognitive Reflection Test (CRT), 173–74
coin logic, 167–68
collaborative cheating, 217–35
altruism and, 222–23, 225–26, 227–28, 232
being watched or monitored and, 223–25, 227–28, 234–35
emphasis on working as group or team and, 217–18
infectious nature of cheating in relation to, 221–22
social utility and, 222–23
companies:
being one step removed from money and, 34–37
irrationality of, 51
see also corporate dishonesty
compliments, insincere, 159
conflicts of interest, 67–95, 238, 248
in academia, 82, 84–85
in dentistry, 67–71, 93, 94, 230
disclosure and, 88–92
dots task and, 129
eradication of, 92–95
exclusion of experimental data and, 86–88
expert witnesses and, 85–86
in financial services industry, 83–85, 93, 94
governmental lobbyists and, 77–78, 94
honesty threshold and, 130–31
inherent inclination to return favors and, 74–75
medical procedures and, 71–74, 92–94, 229
pharmaceutical companies’ influence in academia and, 82
pharma reps and, 78–82
what-the-hell effect and, 129–31
congressional staffers, cheating among, 243
Congress members, PAC money misused by, 208–10
contractors, 93
Conway, Alan, 150–51
Cooper, Cynthia, 215
Cornell University, 250–51
corpora callosa, 164–65
corporate dishonesty:
cheating a little bit and, 239–40
Enron collapse and, 1–3, 192, 207, 215, 234
recent spread of, 192, 207–8
cost-benefit analysis, 4–5, 26–27, 237, 239
infectious nature of cheating and, 201–3, 205
see also Simple Model of Rational Crime
counterfeits, see fake products
creativity, 88, 163–89, 238
brain structure and, 164–65
dark side of, 187–89
fooling oneself and, 165–67
increasing, to increase level of cheating, 184–87
infidelity and, 244
intelligence vs., as predictor of dishonesty, 172–77
link between dishonesty and, 170–72, 186–89
logical-sounding rationales for choices and, 163–64
measures of, 171
moral flexibility and, 186–87
pathological liars and, 168–70
revenge and, 177–84
credit card companies, 239–40
crime, reducing, 52
cultural differences, 240–43
Danziger, Shai, 102
decision making:
creating efficient process for, 167–68
effectiveness of group work in, 217–18
rationalization process and, 163–67
Denfield, George, 75
dentists:
continuity of care and, 228–31
treating patients using equipment that they own, 67–68, 93–94
unnecessary work and, 67–71
depletion, see ego depletion
dieting, 98, 109, 112–13, 114–15
what-the-hell effect and, 127, 130 “dine-and-dash,” 79
diplomas, lying about, 135–36, 153, 154
disabled person, author’s adoption of role of, 143–44
disclosure, 88–92, 248
study on impact of, 89–92
discounting, fixed vs. probabilistic, 194
dishonesty:
causes of, 3–4, 5
collaborative, see collaborative cheating
cultural differences and, 240–43
discouraging small and ubiquitous forms of, 239–40
importance of first act of, 137
infectious nature of, 191–216; see also infectious nature of cheating
intelligence vs. creativity as predictor of, 172–77
link between creativity and, 170–72, 186–89
opportunities for, passed up by vast majority, 238
of others, fake products and assessing of, 131–34
rational and irrational forces in, 254
reducing amount of, 39–51, 248–54
society’s means for dealing with, 4–5
summary of forces that shape (figure), 245
when traveling, 183n
see also cheating
dissertation proposals and defenses, 101
distance factors, 238
in golf, 58–59
stealing Coca-Cola vs. money and, 32–33
token experiment and, 33–34
doctors:
consulting for or investing in drug companies, 82, 93
continuity of care and, 228–29
lecturing about drugs, 81
pharma reps and, 78–82
treating or testing patients with equipment that they own, 92–94
Dodd-Frank Wall Street Reform and Consumer Protection Act, 234
dots task:
conflict of interest and, 129
description of, 127–29
link between creativity and dishonesty and, 171–72, 185–86
what-the-hell effect and, 129–31
downloads, illegal, 137–39
dressing above one’s station, 120–21
Ebbers, Bernie, 13
ego depletion, 100–116, 238, 249
basic idea behind, 101
cheating and, 104–6
in everyday life, 112–16
removing oneself from tempting situations and, 108–11, 115–16
of Sex and the City’s Samantha Jones, 103
sometimes succumbing to temptation and, 114–15
sudden deaths among students’ grandmothers at exam time and, 106–8
ego motivation, 27
England, cheating in, 242
Enron, 1–3, 192, 207, 215, 234
essay mills, 210–13
exams, sudden deaths among students’ grandmothers and, 106–8
exhaustion, 249
consumption of junk food and, 97–98
judges’ parole rulings and, 102–3
see also ego depletion
experimental data, exclusion of, 86–88
expert witnesses, 85–86
explanations, logical-sounding, creation of, 163–65
external signaling, 120–22
dressing above one’s station and, 120–21
fake products and, 121–22
failures, tendency to turn blind eye to, 151
“fair,” determination of what is, 57
fake products, 119, 121–40, 238
illegal downloads and, 137–39
misrepresentation of academic credentials and, 135–36
rationalizations and, 134–35
self-signaling and, 123–26, 135
signaling value of authentic version diluted by, 121–22
suspiciousness of others and, 131–34
what-the-hell effect and, 127–31, 135
farmer’s market, benevolent behavior toward blind customer in, 23–24
fashion, 117–26
counterfeit goods and, 119, 121–22, 121–40, 123–26; see also fake
products
dressing above one’s station and, 120–21
external signaling and, 120–22
self-signaling and, 122–26
Fastow, Andrew, 2
favors, 74–82
aesthetic preferences and, 75–77
governmental lobbyists and, 77–78
inherent inclination to return, 74–75
pharma reps and, 78–82
see also conflicts of interest
Fawal-Farah, Freeda, 117, 118
FBI, 215
Fedorikhin, Sasha, 99–100
Feynman, Richard, 165
financial crisis of 2008, 83–85, 192, 207, 234, 246–47
financial favors, aesthetic preferences and, 77
financial services industry:
anonymous monitoring and, 234–35
cheating among politicians vs., 243
conflicts of interest in, 83–85, 93, 94
government regulation of, 234
fishing, lying about, 28
Frederick, Shane, 173
friends, invited to join in questionable behavior, 195
fudge factor theory, 27–29, 237
acceptable rate of lying and, 28–29, 91
distance between actions and money and, 34–37
getting people to cheat less and, 39–51
infidelity and, 244
rationalization of selfish desires and, 53
stealing Coca-Cola vs. money and, 32–33
Gazzaniga, Michael, 164–65
Generally Accepted Accounting Principles (GAAP), 219–20
generous behavior, 23–24
Get Rich Cheating (Kreisler), 14
Gilovich, Tom, 250, 263–64
Gino, Francesca, 45, 104, 123, 127, 131, 145, 170, 184, 197, 225, 234–35, 242,
258–59
Glass, Ira, 6
Gneezy, Ayelet, 177, 257–58
golf, 55–65
cheating by “average golfer” vs. study participants and, 63–64
mistallying score in, 61–64
moving location of ball in, 58–59, 63
mulligans in, 60–61, 63–64
self-monitoring in, 56–57
survey on cheating in, 57–64
government regulations, 234
grandmothers, sudden deaths of, at exam time, 106–8
gray matter, 169–70
Green, Jennifer Wideman, 117
grocery shopping, ego depletion and, 109, 112–13
group or team work, 220–23
performance unaffected by, 233
possible benefits of, 223
predominance of, in professional lives, 217–18, 235
social utility and, 222–23
see also collaborative cheating
Grüneisen, Aline, 210–11, 257
guilt, self-inflicted pain and, 250–52
Harford, Tim, 3–4
Harper’s Bazaar, 117–18
Harvard Medical School, 82
Harvey, Ann, 75
Henn, Steve, 209
heretics, external signaling of, 120
Hinduism, 25
honesty threshold, 130–31
honor codes, 41–45, 204
ideological organizations, 232n
“I knew it all along” feeling, 149
illegal businesses, loyalty and care for customers in, 138–39
impulsive (or emotional) vs. rational (or deliberative) parts of ourselves, 97–106
cognitive load and, 99–100
ego depletion and, 100–106
exhaustion and, 97–98
Inbar, Yoel, 250, 264
infectious nature of cheating, 191–216, 249
bacterial infections compared to, 192–93
in class, 195–97
collaborative cheating in relation to, 221–22
Congress members’ misuse of PAC money and, 208–10
corporate dishonesty and, 192, 207–8
cost-benefit analysis and, 201–3, 205
essay mills and, 210–13
matrix task and, 197–204
positive side of moral contagion and, 215–16
regaining ethical health and, 214–15
slow and subtle process of accretion in, 193–94, 214–15
social norms and, 195, 201–3, 205–7, 209
social outsiders and, 205–7
vending machine experiment and, 194–95
infidelity, 244–45
“in good faith” notion, 219–20
Inside Job, 84–85
insurance claims, 49–51
intelligence:
creativity vs., as predictor of dishonesty, 172–77
measures of, 173–75
IQ-like tests, cheating and self-deception on, 145–49
certificates emphasizing (false) achievement and, 153–54
increasing awareness of cheating and, 156–57
individuals’ tendency to turn a blind eye to their own failures and, 151
IRS, 47–49
Islam, 249
Israel, cheating in, 241
Italy, cheating in, 242
Jerome, Jerome K., 28
Jobs, Steve, 184
Jones, Bobby, 56
Jones, Marilee, 136
Judaism, 45, 249
judges, exhausted, parole decisions and, 102–3
junk food, exhaustion and consumption of, 97–98
Keiser, Kenneth, 135
Kelling, George, 214–15
John F. Kennedy Center for the Performing Arts, Washington, D.C., 6–7
Kirk, Ulrich, 75
Kreisler, Jeff, 13–14
Kubrick, Stanley, 150–51
Landis, Floyd, 155
Larez, Thomas, 152
law firms, overstating of billable hours in, 35–37
lawyers, conflicts of interest and, 93
Lay, Kenneth, 2
left brain, 164–65
Legend of Bagger Vance, The, 55–56
Less Stress, More Success (Jones), 136
Levav, Jonathan, 102
lobbyists, governmental, 77–78, 94
locks, as protection from mostly honest people, 38
Loewenstein, George, 89
Logic of Life, The (Harford), 3–4
long-term relationships with service providers, 228–31
Lord of the Rings, The (Tolkien), 223
loyalty, in illegal businesses, 138–39
Luce, Mary Frances, 229, 259–60
lying:
acceptable rate of, 28–29
dressing above one’s station as, 120–21
to ourselves, 141–61; see also self-deception
pathological, brain structure and, 168–70
publicly, capacity for self-deception and, 153–54
white lies and, 159–61
Madoff, Bernie, 173, 192
Maharabani, Eynav, 21, 24–26, 258
Marvel, William, 152
Marx, Groucho, 1
matrix task, 15–23
aggressive cheaters and, 239
cheating one step removed from money in (token condition), 33–34
with close supervision, 226–27
with collaborative element, 225–28
concerns about standing out and, 22–23
control and shredder conditions in, 17–18
cultural differences and, 240–43
ego depletion and, 106
fake products and, 125–26
honor codes and, 41–44
infectious nature of cheating and, 197–204
with moral reminders, 39–44, 46–47
self-paying condition in, 20, 21
sign-at-the-top vs. sign-at-the-bottom conditions in, 46–47
task in, 15–16
tax reporting and, 45–47
varying amount of money in, 18–20
varying probability of getting caught in, 20–22
Mazar, Nina, 15, 18, 31–32, 39, 45, 194, 261
McGwire, Mark, 156
McKenzie, Scott, 57, 263
Mead, Nicole, 104, 261
medical device reps, 80
medical schools, pharmaceutical companies’ influence in, 82
medicine, conflicts of interest in, 71–74, 78–82, 92–94
see also pharma reps
memento mori, 247
Middle Tennessee State University, 44–45
MIT:
Charm School at, 153
honor code study at, 41–42, 43
matrix task study at, 15–21
money:
directly stealing, 32–33
distance between our actions and, 34–37
monitoring or watching, as disincentive to cheating, 223–25, 227–28, 234–35
Montague, Read, 75
Moore, Don, 89
moral considerations, 4, 13, 14
amount of cheating and, 23, 27
cognitive flexibility and, 27–28, 186–87, 242
moral reminders, 39–52, 238, 248, 249–50
decline in effectiveness of, over time, 44n
honor codes and, 41–45
infectious nature of cheating and, 203–4
signing forms at top and, 46–51
Ten Commandments and, 39–40, 41, 44, 250
mortgage-backed securities, 83–85
Mulligan, David, 60
mulligans, 60–61, 63–64
“Myth of the King of Gyges” (Plato), 223
Nettle, Daniel, 224
New York Times, 82, 150
Nisbett, Richard, 163–64
nonmonetary objects, dishonesty in presence of, 32–34
stealing Coca-Cola vs. money and, 32–33
token condition and, 33–34
Norton, Michael, 123, 127, 131, 145, 260–61
not-for-profits, 232n
Odysseus, 98
Opus Dei, 250–52
Ozdenoren, Emre, 114–15
Palmer, Arnold, 62
parking tickets, 4
parole hearings, judges’ exhaustion and, 102–3
pharmaceutical companies, 93
impact in academia of, 82
pharma reps, 78–82
“dine-and-dash” strategy of, 79
doctors’ lectures and, 81
small gifts and free drug samples from, 78
Picasso, Pablo, 184
Pizarro, David, 250, 258
plagiarism, 213
cultural differences and, 242–43
Plato, 223
Pogue, David, 178–80
political action committees (PACs), 208–10
political organizations, 232n
politicians, cheating among bankers vs., 243
postal service, U.S., 188
Prada bags:
fake, 119, 122
real, given to author, 118–19, 122, 140
Predictably Irrational (Ariely), illegal downloads of, 137–39
preferences, creating logical-sounding reasons for, 163–64
prefrontal cortex, 169–70
Princeton University, honor code study at, 42–44
probabilistic discounting, 194
prostitutes, external signaling of, 120
prudence, principle of, 220n
punishment, 13, 52
cost-benefit analysis and, 5, 13, 14
self-cleansing, in resetting rituals, 250–52
Rather, Dan, 152
rationalization of selfish desires:
of Austen characters, 154–55
fake products and, 134–35
fudge factor and, 27–28, 53, 237
link between creativity and dishonesty and, 172
revenge and, 177–84
tax returns and, 27–28
see also self-justification
reason vs. desire, 97–106
cognitive load and, 99–100
ego depletion and, 100–106
exhaustion and, 97–98
“Recollections of the Swindle Family” (Cary), 246
religion:
reminders of moral obligations and, 45, 249–50; see also Ten
Commandments
resetting rituals and, 249, 250–52
reminders:
of made-up achievements, 153–54, 238
see also moral reminders
resetting rituals, 249, 250–54
to change views on stealing, 252–53
self-inflicted pain and, 249, 250–52
Truth and Reconciliation Commission in South Africa and, 253–54
résumés, fake credentials in, 135–36, 153
revenge, 177–84
annoyance at bad service and, 177–80
author’s tale of, during European travels, 180–84
Rich, Frank, 150
right brain, 164–65
Roberts, Gilbert, 224
Rogers, Will, 55, 57
Rome, ancient:
memento mori reminders in, 247
sumptuary laws in, 120
Romeo and Juliet, 98
Rowley, Coleen, 215
Salant, Steve, 115
Salling, John, 152
Sarbanes-Oxley Act, 234
Schrödinger’s cat, 62–63
Schwartz, Janet, 80, 229, 259
Schweitzer, Maurice, 104, 260
scorekeeping, dishonesty in, 61–64
self-deception, 141–61
author’s personal experience of, 143–44
cheating on IQ-like tests and, 145–49, 151, 153–54, 156–57
“I knew it all along” feeling and, 149
Kubrick imitator and, 150–51
negative aspects of, 158–59
people with higher tendency for, 151
positive aspects of, 158
reducing tendency for, 156–57
reminders of made-up achievements and, 153–54, 238
repeating lies over and over and, 142–43
selfishness of Austen characters and, 154–55
in sports, 155–56
veterans’ false claims and, 152
white lies and, 159–61
self-flagellation, 250–52
self-image:
amount of cheating and, 23, 27
fudge factor and, 27–29
self-indulgence, rational, 115–16
selfishness, see rationalization of selfish desires
self-justification:
creation of logical-sounding explanations and, 163–65
link between creativity and dishonesty and, 172
mulligans and, 60–61
repositioning golf ball and, 61
see also rationalization of selfish desires
self-signaling, 122–26
basic idea of, 122
charitable acts and, 122–23
fake products and, 123–26, 135
what-the-hell effect and, 127–31
Sense and Sensibility (Austen), 154–55
service providers, long-term relationships with, 228–31
service records, exaggerated, 152–53
Sessions, Pete, 209
Sex and the City, 103–4
Shakespeare, William, 184
shareholder value, maximizing of, 208n
Shiv, Baba, 99–100
shopping malls, susceptibility to temptation in, 113
Shu, Lisa, 45, 259
signing forms at top vs. bottom, 46–51
insurance claims and, 49–51
tax reporting and, 46–49
Silverman, Dan, 114–15
Simple Model of Rational Crime (SMORC), 4–6, 11–29, 53, 201, 238, 248
author’s alternative theory to, 27–28; see also fudge factor theory
guest lecturer’s satirical presentation on, 11–14
life in hypothetical world based on, 5–6
matrix task and, 15–23
tested in real-life situations, 23–26
sincerity, principle of, 220n
Skilling, Jeffrey, 2
social norms, infectious nature of cheating and, 195, 201–3, 205–7, 209
social utility, collaborative cheating and, 222–23
South Africa, Truth and Reconciliation Commission in, 253–54
split-brain patients, 164
sports, self-deception in, 155–56
stealing:
Coca-Cola vs. money, 32–33
joke about, 31
resetting mechanisms and, 252–53
from workplace, 31, 33, 193
steroids, in sports, 155–56
storytelling:
creation of logical-sounding explanations and, 163–65
reinterpreting information in self-serving way in, 187–88
self-deception and, 142–43
Stroop task, 109–12
opportunity to cheat on, 111–12
Suckers, Swindlers, and an Ambivalent State (Balleisen), 188
sumptuary laws, 120
sunshine policies, 88, 91–92
suspiciousness of others:
fake products and, 131–34
self-deception and, 158–59
Tali (research assistant), 21, 24–26
Taliban, 152
Talmud, 45
Tang, Thomas, 44
tax returns, 45–49
IRS reaction to author’s findings on, 47–49
rationalization of exaggerated deductions in, 27–28
signing at top vs. bottom, 46–49
technological frontiers, potential for dishonesty and, 188
temptation, resisting of:
cognitive load and, 99–100
dieting and, 98, 109, 112–13, 114–15
ego depletion and, 100–116
evenings as difficult time for, 102
physical exhaustion and, 97–98
removing oneself from tempting situations and, 108–11, 115–16
in shopping malls, 113
Ten Commandments, 39–40, 41, 44, 204, 250
This American Life, 6–7
Three Men in a Boat (to Say Nothing of the Dog) (Jerome), 28
Time, 215
token experiment, 33–34
Tolkien, J. R. R., 223
Tour de France, 155
tragedy-of-the-commons situations, 40–41
travel reimbursements, 46, 47
Truth and Reconciliation Commission, 253–54
Turkey, cheating in, 242
University of California, Los Angeles (UCLA), 39–40
University of Newcastle, 224
University of Pittsburgh, 204–7
University of Waterloo, Canada, 155
Upside of Irrationality, The (Ariely), 177
U.S. Open (1925), 56
vending machine study, 194–95
veterans, exaggerated service records and, 152–53
Wall Street Journal, 135
Wang, Shirley, 241–42
Warner Bros., 150
watching or monitoring, as disincentive to cheating, 223–25, 227–28, 234–35
Watkins, Sherron, 215
Weiss, Dan, 6–7
what-the-hell effect, 127–31
combating moral deterioration of, 140
dieting and, 127, 130
fake academic credentials and, 136
fake products and, 127–31, 135
honesty threshold and, 130–31
resetting rituals and, 249, 250–53
white lies, 159–61
white matter, in brain, 170
Wilde, Oscar, 28
willpower, see temptation, resisting of
Wilson, Duff, 82
Wilson, James, 214–15
Wilson, Wim, 163–64
wishful blindness, 2
work hours, viewing decisions in terms of, 86n
workplace, stealing at, 31, 33, 193
WorldCom, 13, 215
Yale, honor code experiment at, 41–42
Yang, Yaling, 168–70
Thanks
I find writing about academic research to be fulfilling and stimulating, but the
pleasure that I get day in and day out comes from working jointly with amazing
researchers/friends—coming up with ideas, designing experiments, finding out
what works and doesn’t work, and figuring out what the results mean. The
research described here is largely a product of my collaborators’ ingenuity and
efforts (see the following biographies of my outstanding colleagues), and I am
grateful that we have been able to travel together in the landscape of dishonesty
and together learn a bit about this important and fascinating topic.
In addition, I am also thankful to social scientists at large. The world of
social science is an exciting place in which new ideas are constantly generated,
data collected, and theories revised (some more than others). Every day I learn
new things from my fellow researchers and am reminded of how much I don’t
know (for a partial list of references and additional readings, see the end of this
book).
This is my third book, and by now one might expect that I would know what
I am doing. But the reality is that I would not be able to do much without the
help of many people. My deepest thanks go to Erin Allingham, who helped me
write; Bronwyn Fryer, who helped me see more clearly; Claire Wachtel, who
conducted the process with grace and humor that is rare in editors; Elizabeth
Perrella and Katherine Beitner, who managed to be my human substitutes for
both Adderall and Xanax. And the team at Levine Greenberg Literary Agency,
who were there to help in every possible way. Aline Grüneisen made many
suggestions, some that were very insightful and others that made me smile. I am
also grateful to Ania Jakubek, Sophia Cui, and Kacie Kinzer. Very special
thanks also go to the person who functions as my external memory, hands, and
alter ego: Megan Hogerty.
Finally, where would I be without my lovely wife, Sumi? It takes a very
special person to be willing to share a life with me, and my hectic life and
workaholism don’t make it any easier. Sumi, I will move the boxes to the attic
when I get home tonight. Actually, I will probably be late, so I will do it
tomorrow. Well, you know what? I will definitely do it this weekend. I promise.
Loving, Dan
About the Author
Dan Ariely is the James B. Duke Professor of Psychology and Behavioral
Economics at Duke University, with appointments at the Fuqua School of
Business, the Center for Cognitive Neuroscience, the Department of Economics,
and the School of Medicine. Dan earned one PhD in cognitive psychology and
another PhD in business administration. He is the founder and director of the
Center for Advanced Hindsight. His work has been featured in many outlets,
including The New York Times, The Wall Street Journal, The Washington Post,
The Boston Globe, and others. He lives in Durham, North Carolina, with his
wife, Sumi, and their two creative children, Amit and Neta.
www.danariely.com
Notes
Introduction: Why Is Dishonesty So Interesting?
1. Ira Glass, “See No Evil,” This American Life, National Public Radio,
April 1, 2011.
Chapter 1. Testing the Simple Model of Rational Crime (SMORC)
1. “Las Vegas Cab Drivers Say They’re Driven to Cheat,” Las Vegas Sun,
January 31, 2011, www.lasvegassun.com/news/2011/jan/31/drivencheat/.
Chapter 3. Blinded by Our Own Motivations
1. A. Wazana, “Physicians and the Pharmaceutical Industry: Is a Gift Ever
Just a Gift?” Journal of the American Medical Association (2000).
2. Duff Wilson, “Harvard Medical School in Ethics Quandary,” The New
York Times, March 2, 2009.
Chapter 5. Why Wearing Fakes Makes Us Cheat More
1. K. J. Winstein, “Inflated Credentials Surface in Executive Suite,” The
Wall Street Journal, November 13, 2008.
Chapter 6. Cheating Ourselves
1. Anne Morse, “Whistling Dixie,” The Weekly Standard (blog), November
10, 2005.
2. Geoff Baker, “Mark McGwire Admits to Steroids Use: Hall of Fame
Voting Becoming a Pain in the Exact Place He Used to Put the Needle,”
http://seattletimes.nwsource.com/html/marinersblog/
2010767251_mark_mcgwire_admits_to_steroid.html.
Chapter 8. Cheating as an Infection: How We Can Catch the Dishonesty
Germ
1. Steve Henn, “Oh, Waiter! Charge It to My PAC,” Marketplace, July 21,
2008, and “PACs Put the Fun in Fundraising,” Marketplace, July 22,
2008.
2. Steve Henn, “PACs Put the Fun in Fundraising,” Marketplace, July 22,
2008.
Chapter 9. Collaborative Cheating
1. Dennis J. Devine, Laura D. Clayton, Jennifer L. Philips, Benjamin B.
Dunford, and Sarah P. Melner, “Teams in Organizations, Prevalence,
Characteristics, and Effectiveness,” Small Group Research (1999). John
Gordon, “Work Teams: How Far Have They Come?” Training (1992).
Gerald E. Ledford, Jr., Edward E. Lawler III, and Susan A. Mohrman,
“Reward Innovations in Fortune 1000 Companies,” Compensation &
Benefits Review (1995). Susan A. Mohrman, Susan G. Cohen, and Allan
M. Mohrman, Jr., Designing Team-Based Organizations: New Forms
for Knowledge Work (San Francisco: Jossey-Bass, 1995). Greg L.
Stewart, Charles C. Manz, and Henry P. Sims, Team Work and Group
Dynamics (New York: Wiley, 1999).
2. Bernard Nijstad, Wolfgang Stroebe, and Hein F. M. Lodewijkx, “The
Illusion of Group Productivity: A Reduction of Failures Explanation,”
European Journal of Social Psychology (2006).
3. ADA Council on Scientific Affairs, “Direct and Indirect Restorative
Materials,” The Journal of the American Dental Association (2003).
Chapter 10. A Semioptimistic Ending: People Don’t Cheat Enough!
1. Montpelier [Vermont] Argus & Patriot, March 6, 1873.
OTHER BOOKS BY DAN ARIELY
The Upside of Irrationality: The Unexpected
Benefits of Defying Logic
Predictably Irrational: The Hidden Forces
That Shape Our Decisions
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* For the full references to all the materials used in each chapter, and for related readings, see the
Bibliography and Additional Readings at the back of the book.
* Beyond exploring the topic of dishonesty, this book is fundamentally about rationality and
irrationality. And although dishonesty is fascinating and important in human endeavors its own
right, it is also important to keep in mind that it is but a single component of our interesting and
intricate human nature.
* Readers of Predictably Irrational might recognize some of the material presented in this chapter
and in chapter 2, “Fun with the Fudge Factor.”
* X stands for the number of questions that the participants claimed to have solved correctly.
* One important question about the usage of moral reminders is whether over time people will get
used to signing such honor codes, causing such reminders to lose their effectiveness. That is
why I think that the right approach is to ask people to write their own version of the honor code
—that way it will be difficult to sign without thinking about morality, and more ethical behavior
should follow.
* As it turned out, I was audited by the IRS a few years later, and it was a long, painful but very
interesting experience. I don’t think it was related to this meeting.
* I suspect that for people who actively dislike the government or insurance companies, the effect
would still hold, though it might be mitigated to some degree—something worth testing in the
future.
* Think about all the cases in which people ask for advice about how to behave in embarrassing
situations—not for themselves but for a “friend.”
* When I was a teenager, a magnesium flare exploded next to me. I suffered massive third-degree
burns and underwent many operations and treatments over the subsequent years. For more
details, see my previous books.
* Perhaps the most telling evidence for the pharma industry’s influence is the fact that my insider for
this interview insisted that I keep his name confidential to avoid being blacklisted by pharma.
* This was the first time that I was paid a lot by the hour, and I was intrigued by how I started to
view many decisions in terms of “work hours.” I figured that for one hour of work I could buy a
really fancy dinner and that for a few more I could buy a new bicycle. I suspect that this is an
interesting way to think about what we should and should not purchase, and one day I might
look into this.
*
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* The market for fake goods, of course, ranges far beyond Chinatown and New York. After gathering
momentum for more than forty years, the phenomenon is now a formidable affair.
Counterfeiting is illegal almost everywhere on our planet, though the severity of the punishment
varies from country to country, as does people’s view of the morality of buying counterfeits.
(See Frederick Balfour, “Fakes!” BusinessWeek, February 7, 2005.)
* The rumor about this shipment quickly traveled around Duke, and I became popular among the
fashion-minded crowd.
* You might wonder if receiving counterfeits as gifts would have the same effect as choosing a
counterfeit product for ourselves. We wondered the same thing and tested this question in
another experiment. It turned out that it doesn’t matter whether we acquire a counterfeit product
by our own choice or not; once we have a fake product, we are more likely to cheat.
* You might wonder if people are aware of the downstream consequences of counterfeits. We tested
this too and found that they are unaware of these effects.
* We used this type of SAT-like question instead of our standard matrices because we expected that
such questions would lead more naturally to the feeling of “I knew it all along” and to selfdeception.
* The story was written up by Kubrick’s assistant, Anthony Frewin, in Stop Smiling magazine, and it
was the basis of the film Colour Me Kubrick, starring John Malkovich as Conway.
* I have nothing against the Ford Taurus, which I am sure is a fine automobile; it just wasn’t as
exciting a car as I’d imagined myself driving.
* I suspect that there is a connection between dishonesty and traveling in general. Perhaps it’s
because when traveling the rules are less clear, or maybe it has to do with being away from
one’s usual setting.
* The smart thing would have been to lead the students through the oath at the start of every lecture,
and maybe this is what I will do next time.
* I suspect that companies that adapt the ideology of maximizing shareholder value above all else
can use this motto to justify a broad range of misbehaviors, from financial to legal to
environmental cheating. The fact that the compensation of the executives is linked to the stock
price probably only increases their commitment to “shareholder value.”
* Another fuzzy rule is the quaint-sounding “principle of prudence,” according to which accountants
should not make things appear rosier than they actually are.
* Are dentists doing this on purpose, and do the patients know that they are being punished for their
loyalty? Most likely it is not intentional, but whether conscious or not, the problem remains.
* Based on these results, we could speculate that people who work for ideological organizations such
as political groups and not-for-profits might actually feel more comfortable bending moral rules
—because they are doing it for a good cause and to help others.