Course introduction, philosophy, and structure Your two brains

1. Find a recent (within 1 year) example of bad “framing” in the news (provide a link). That is, find a title or sentence in any news source that you think could be improved by changing the reference point to switch from gain to loss “frame” or vice versa, and rewrite it in a way that you think would be a better. Explain why you think your new “frame” is better. Your new “frame” should not change the objective information provided or add new information, nor should it drastically change the original speaker’s intended message. Hints: 1) Make sure you know what “frame” means for this class… a bad frame is not simply about poor wording! 2) The best examples of sentences to reframe contain numerical information

600-word limit

No fluff rule: Your goal is to show your understanding. Please do NOT write an intro, background, or conclusion. Also do NOT define terms and avoid quoting directly from readings or slides. DO make sure to do the readings thoroughly (the optional ones for that topic may help). Knowledge cannot be faked.

There rarely exist right answers to these questions. That’s what makes the prompts interesting, useful, and fun (we hope). Good write-ups will always reflect a solid understanding of the material but more importantly you should be able to apply the concepts to the prompt. This means that you should not provide definitions and examples from the reading, but instead figure out what concepts are relevant and how they apply to this business situation. The following are a few tangible, specific tips based on years of grading write-ups. I offer them to you in roughly decreasing order of how frustrating their violations are to a grader. 1.Don’t regurgitate the reading. You never need to waste space including definitions from the reading. Write as if your audience not only has read the assigned materials but also knows them well. When necessary, cite a concept as briefly as possible. The fact that you’ve done the reading should be revealed to us by your thinking, NOT by some quotation. 2.Start quickly and end abruptly. For these short write-ups, introductions, background, and conclusions are almost entirely unnecessary. Even worse, they take away space that is much better used in other ways. We don’t expect these things to read like English compositions. Nor are we strangers to why you’re writing in the first place. Jump right in. 3.Choose specific over abstract. Precision is good. It’s good for communication, and it’s good for sharpening thinking. When you feel yourself getting fuzzy, think to yourself: I need an example. We love examples. Make it real. 4.Be realistic. There is nothing more irritating than a cute suggestion (for example, of how an organization might mitigate a particular bias) that works theoretically but is utterly infeasible in the real world. Perhaps the best criterion is to ask yourself if you’d be willing to sit in a manager’s office advocating his or her use of your recommendation. 5.Less is more. Believe it or not, a common mistake is to include too many ideas — not because too many ideas itself is bad, but because these ideas, as intriguing, tantalizing, and, yes, right as they might be, are often too poorly developed. Don’t make this mistake! We’re not impressed with laundry lists. It’s much better to write about a few things really well. Oh, and have fun! This is an opportunity to be creative (the risk-reward tradeoff for creativity is very attractive). A student who is thoughtful and having fun when writing these is generally going to do pretty well. And get more out of it. Thanks!

Stripped down to its essentials, business is about one thing:
making decisions. We’re always deciding something – from the
small and the daily ( which emails to answer, what meetings to
have ) to the macro and the strategic ( what product to launch
and when ) to the intensely personal ( what job to take, whom
to hire, whom to marry ). But what does it take to make a
“good” decision? Is it about going by facts and percentages – or
about following your gut instinct? Does time produce better
decisions, or does pressure make you decide not only faster but
also more wisely? And finally, is better decision making some-
thing that you can learn? We asked 11 decisive leaders, inside
and outside of business, to answer these and other, related
questions. Does their advice help? You decide.

Ed Koch
Partner
Robinson Silverman Pearce Aronsohn & Berman LLP

New York, New York

To make good decisions, you need confidence in your judg-
ment. We all make bad decisions, but the important thing is
not to worry too much about them. Otherwise, you’ll never do
a thing. I was mayor of New York City for 12 years. I had a $28
billion budget. Each decision I made affected seven and a half
million people. The stakes were high. I had to show confidence
– in particular, confidence in my decision-making ability –
because a lot of people had put their trust in me. The worst
decision I ever made was to run for governor of New York State
in 1982. I did it on a lark, and it was stupid. Thank god the peo-
ple of New York had enough sense to understand that I didn’t
have my heart in that race – and to vote against me. They did
the right thing, and I was happier because of it.

As a judge, I have to decide on the credibility of two people
standing before me. I don’t know who is telling the truth, but I
know that one of them is lying. That’s when making decisions
gets sticky. Sure, the law helps me make such decisions. But
there have been many times when I’ve had a hell of a time
deciding. Even so, I never base my courtroom decisions on gut
instinct. I go by the evidence – or the lack of evidence – and by
the applicable law.

Ed Koch was mayor of New York City from 1978 to 1989.
Today he writes a weekly column for the New York Daily News,

has his own radio talk show, and is the judge on the television
program “The People’s Court.”

Pamela Lopker
Chairman and President
QAD Inc.
Carpinteria, California

I make bad decisions all the time. But I’ve been successful
because I’ve developed a process for identifying and changing
those decisions quickly. I approach every decision with an eye
to the long-term outcome. That’s a hard method to adopt in a
fast-paced business environment. But it’s the only way to create
sustainable value on either a professional or a personal level.
The quick-fix method that I see so many companies rely on is
just that – a quick fix. There’s a big difference between invest-
ing heavily in marketing the product that you have today – with
no sense of what it takes to survive tomorrow – and investing
heavily in R&D today so that you can have tomorrow’s product.

Even in my personal life, I looked at decisions from the per-
spective of what’s going to be better for me over the long term.
When I was in college, I needed to decide on a career path.
While most of my peers were concerned with following their
passion, with doing what they “loved” to do, I was looking for a
career that would support me financially over the long run.
Sometimes making important decisions is just a matter of ask-
ing some basic questions: What are my skills? Where is a cer-
tain industry going? What should I be doing now to get to
where I want to be later? Because I was always strong in math
and in analytical thinking, I figured that I would do statistical
or actuarial work. Then I realized that statistics wasn’t a boom-
ing industry. Computer science seemed like a better long-term
bet, so I changed my major.

As a leader, I try not to make decisions for others. Sure, being a
dictator is often the fastest way to get things done. But it’s not a
process that allows an organization to sustain growth. I want the
people in my organization to learn the lessons that come with
making decisions: that everything is a compromise, that noth-
ing is ever completely logical, but that you can deal with things
through a logical decision-making process.

Pamela Lopker has been called America’s “richest self-made

1© All rights reserved. Fast Company, LLC • Visit: http://www.fastcompany.com/learning

FC :L E A R N I N G

Decisions, Decisions
Unit of One

BY ANNA MUOIO
First appeared: FC18, p.93

woman.” QAD, a $172 million enterprise resource-planning
software company, is one of the 30 largest public companies to
be led by a female CEO. Its clients include Avon Products,
PepsiCo, Ford, and Johnson & Johnson.

W. Brian Arthur
Citibank Professor
Santa Fe Institute
Santa Fe, New Mexico

I received my PhD in operations research, which is a highly sci-
entific, mathematical way of strategizing and of making deci-
sions. I once thought that I could make any decision, whether
professional or personal, by using decision trees, game theory,
and optimization. Over time, I’ve changed my mind. For the
day-to-day work of running a business – scheduling a fleet of oil
tankers, choosing where to open a new factory – scientific deci-
sion theory works pretty well. But for just about every other
kind of decision, it doesn’t work at all.

For the big decisions in life, you need to reach a deeper region
of consciousness. Making decisions then becomes not so much
about “deciding” as about letting an inner wisdom emerge.
We’ve been bamboozled into believing that cognition is ration-
al – that our mind is a gigantic computer, or a blackboard on
which we can reach a decision by calculating pluses and
minuses. Recent research on cognition shows that our minds
rarely make strictly logical deductions. Instead, we rely on pat-
terns – and on feelings associated with those patterns.

So for those big decisions – Should I marry this person? Should
I follow that career? Should I sell my company? When should
we go public? – let patterns develop in your mind. Let clues and
evidence emerge from your environment. This approach to
decision making requires time, patience, and another key
ingredient: courage. It takes courage to listen to your inner wis-
dom. But once you hear that wisdom, making a decision
becomes fairly easy.

W. Brian Arthur’s work on the economics of increasing returns
and their role in technology-based industries has won him
international recognition in the scientific and business com-
munities. He is a pioneer of the new science of complexity and
the author of The Economy as an Evolving Complex System II
( Addison-Wesley, 1997 ).

Chung-Jen Tan
Senior Manager, Application Systems
IBM’s Thomas J. Watson Research Center
Yorktown Heights, New York

I’ve learned a lot about decision making by watching how a
machine plays chess. In 1996, Deep Blue played Garry

Kasparov, the world chess champion. Deep Blue won the first
game but lost the match. That experience taught us what we
needed to do to be ready for the rematch in 1997.

A human uses a combination of knowledge, strategy, and intu-
ition to make chess decisions. A machine relies on brute com-
putational power and on an ability to examine a tremendous
amount of data. On average, the human mind can manage
three or four positions per second. Deep Blue can evaluate 200
million alternatives per second. So the machine has a huge
advantage. But Deep Blue also had weaknesses, and they cen-
tered on its inability to be flexible. Our challenge was to equip
Deep Blue to make decisions like a human grandmaster.

We built in several programming tools that allowed us to adjust
some of the decision parameters dynamically and to change
strategies in between games. Joel Benjamin, the U.S. chess
champion, played chess with Deep Blue for nine months – test-
ing and tunneling the system – and we programmed some of his
knowledge into the computer.

An interesting thing happened when Deep Blue met Kasparov
for the rematch. While we had refined Deep Blue so that it
could make decisions and play more like a human, Kasparov
had refined his strategy so that he could play better against
standard computer-chess programs. In game six, Deep Blue
surprised Kasparov by sacrificing a knight to gain strategic
advantage. Kasparov, who hadn’t planned for such a decision,
realized how inflexible his own strategy had become. We
showed that a machine can reach a level of play comparable
with that of a grandmaster .

Chung-Jen Tan manages IBM’s Deep Blue computer-chess
project. Since 1984, Tan has worked on the architecture devel-
opment and machine design of highly parallel, scalable sys-
tems for solving large, complex problems.

Deborah Triant
CEO and President
Check Point Software Technologies Inc.
Redwood City, California

Making and implementing decisions boils down to a key ingre-
dient: listening.

I often wonder why schools emphasize debating. Why not have
listening classes as well? Debating is easy; listening with an
open mind is not. The worst thing that you as a leader can do
in the decision-making process is to voice your opinion before
anyone else can. No matter how open and honest your people
are, stating your opinion first will short-change the discussion
process and taint what you hear later. I’ve learned this the hard
way.

FC :L E A R N I N G

2© All rights reserved. Fast Company, LLC

There are two classes of decisions. The first is the easy kind. For
instance, how do you choose which features to include in the
next release of your product? It’s a pretty straightforward
process: Survey your customers, identify the information you
need, and formulate a decision by using rational, objective
measurements. The second class is the tough kind. Fo r
instance: Should you hire this person? Should you go after this
key market? Should you switch jobs? Should you have a kid?
These are bet-your-life decisions for which there’s no obvious
right or wrong answer – and no way of gathering objective infor-
mation.

To tackle decisions of either class, I first kick into a talkative
mode. I ask everybody I know to give me an opinion. I get dif-
ferent perspectives – and I listen to them. I also listen to that
thing called intuition. Some people warn against that
approach. But there’s a kind of processing that happens in a far
deeper place than logical processing does. Intuition offers a
way to integrate and synthesize, to weigh and balance informa-
tion. If I have to make a big decision, I listen to what others
think. But ultimately, I listen to my intuition. I postpone a deci-
sion until I wake up one morning and know where my gut is
going.

Deborah Triant was president and CEO of Sitka Corp., a sub-
sidiary of Sun Microsystems, before she joined Adobe Systems
as president of marketing in 1993. In 1995, she left Adobe to
head Check Point, a network-security and traffic-management
software company.

Roger Rainbow
VP, Global Business Environment
Shell International Ltd.
London, England

Nothing can paralyze a decision-making process more than
uncertainty can. The big decisions that have failed at Shell did-
n’t fail because of our operations or because of project man-
agement; they failed because we misunderstood the external
world. That’s why, when we’re on the verge of a big decision,
we do scenario planning. A scenario is valuable because it’s a
plausible, coherent story that we can use to articulate why we
want to do something and which issues to factor into the deci-
sion-making process.

Everyone has two things in mind when approaching a big deci-
sion. The first thing is a scenario – a view of how the world will
turn out. The second thing is an objective or a strategy. A good
decision-making process marries those two things.

Decisions fall into three categories. With the first category, you
know a lot. Take a plant that’s been operating for 20 years. You

know what makes it succeed or fail, and the decisions you take
regarding it tend to be fairly straightforward. They may be hard
to implement, but they’re simple to make.

With the second category, you know something but not every-
thing. This is where scenario planning helps. For instance, if
we’re trying to decide whether to invest in an oil field in Russia,
we talk about which factors are uncertain and why. What has
to happen in order for this investment to succeed? What could
go wrong? What would the consequences be? Are any of those
consequences absolutely catastrophic? If so, how can we guard
against them?

With the third category, you know virtually nothing, and you’re
starting from scratch. This is where intuition comes into play –
and where you make truly creative decisions: You’re deciding
on things that haven’t been done before.

Each category of decisions requires different skills and process-
es. Understand which kind of decision you’re facing, and use
scenarios to narrow the range of uncertainty.

Roger Rainbow ( roger.r.rainbow@si.shell.com ) joined Shell
in 1970. His team provides analyses of the business environ-
ment by preparing long-term scenarios that consider econom-
ic, social, technological, and environmental issues, as well as
the long-term supply and demand of energy sources.

Chris Newell
Executive Director, the Lotus Institute
Lotus Development Corp.
Cambridge, Massachusetts

The crux of making good decisions isn’t doing things right – it’s
making sure that you focus on the right things. As citizens of
the Information Age, we’re overwhelmed with data, reports,
facts – much of it noise that we need to filter out before we can
figure out what’s relevant to a decision. So I’ve learned to hone
my discrimination skills. But if you’re exploring something that
has no precedent – an idea, a product, a service – you can’t rely
solely on data to guide you. You have to rely on people too. I’ve
developed a personal advisory council that I consult before
tackling a big decision, a group of people who are anchored by
similar values – though not necessarily by similar perspectives.

Sometimes making the “wrong” decision is the right thing to
do. Last year, I decided to overrun my budget – to continue
investing in LearningSpace, a product that Lotus was unsure
about investing in. I knew it was the right thing to do, even
though I couldn’t get the company to agree. When news of my
decision surfaced on the radar of some key people, I got ham-
mered. At times, I even doubted my own decision. A year later,
LearningSpace has become one of Lotus’s most important

3© All rights reserved. Fast Company, LLC

FC :L E A R N I N G

strategic products.

I made one mistake: I didn’t communicate all of the implica-
tions of going over budget. Otherwise, I wouldn’t change a
thing about what I did.

Chris Newell founded the Lotus Institute in 1994. Its mission
is to explore ways in which groupware technology intersects
with cultural issues. It has developed two applications:
TeamRoom, which supports virtual teaming; and
L e a r ningSpace, which supports collaborative, di s t r i b u t i v e
learning.

Buz Mertes
VP, Loss Management and Policy Servicing
GE Capital Mortgage Insurance Corp.
Raleigh, North Carolina

By transforming the art of decision making into a science, you
can save time, money, and frustration. My team handles tough
decisions every day. It has to decide whether we can “cure” a
loan for someone who has stopped making payments on it or
whether we have to recommend foreclosure because of real
financial trouble.

For a long time, we couldn’t figure out what allowed some of
our reps to make better decisions than others did. We pulled six
of our best reps off their jobs and analyzed their decision-mak-
ing processes for 10 months. We found that these reps had rad-
ically different styles. Our challenge was to figure out the criti-
cal processes that drove their decisions and then to make sure
that those decisions were driven by factual, up-to-date informa-
tion. We had a goal: to become more consistent in our decision
making and to improve our customers’ perception of us. We
ended up creating a software program, called Loss Mitigation
Optimizer, to aid us in that process.

Turning decision making into a science saved us time and
money. Before we implemented this technology, we were cur-
ing fewer than 30% of our cases. Now we cure more than 50%
of them. The decision-making process itself takes 30% to 50%
less time per deal. Our savings jumped dramatically – by about
$8,000 per case. In the project’s first 18 months, these addi-
tional savings came to $15 million in net income. Some peo-
ple think that decisions of this type can’t be driven by data. Our
results show otherwise.

Buz Mertes joined GE in 1984. Since 1996, Mertes has spon-
sored a series of projects that have increased the company’s net
income by more than $20 million.

Jerry Seeman
Senior Director of Officiating
National Football League

New York, New York

As a referee, I found that the pressure was the same whether I
was officiating a preseason game or a Super Bowl. Being on the
field is like being in a fishbowl: Everyone – players, coaches,
fans, the media – is waiting for your decision. A successful call
depends on three things: You must be in position, you must
have a deep knowledge of the game, and you must have intense
concentration. Remember, no matter what the reaction to your
decision may be, you answer to only one thing: your con-
science. Above all, when making a decision, you have to keep
your cool.

One of the biggest errors that I see officials fall into is making
calls too quickly. Each decision has two phases: You read and
analyze the play, and then you make the call. But when things
happen in a split second, it can be tempting to throw a penalty
flag before you know what happened. That’s why I tell all of my
officials to work in “cruise control.” The fans may go crazy, the
players and coaches may get excited, but there should be seven
people on the field who work every game the same way from
beginning to end – and who exude a quiet confidence.

Once you make a decision, you’d better be able to communi-
cate it. I remember having to make a call on a bizarre play in
a playoff game between Houston and Cleveland. After an
attempted onside kick, the kicking team illegally touched the
ball, which then went out of bounds. The rules dictate that the
kicking team should kick again. That team again tried an
onside kick, and again it illegally touched the ball – but this
time, it recovered the ball. I called that the receiving team
would gain control of the ball on the spot where it was illegal-
ly touched. This was a complicated play: The NFL probably
hasn’t seen another of its kind in the past 15 years. At first, the
fans didn’t understand my decision. But I explained to them
what the proper ruling was, and they accepted it. I was confi-
dent about my knowledge of the game. And I didn’t lose my
cool.

Jerry Seeman, one of the most celebrated referees in football
history, became an NFL line judge in 1975. He was appointed
referee in 1979. His responsibilities now cover the league’s
supervisory staff, as well as regional game observers, collegiate
scouts, and all game officials.

Max Bazerman
J. Jay Gerber Distinguished Professor of Dispute Resolution
and Organizations
Kellogg Graduate School of Management
Evanston, Illinois

When making a decision, don’t listen to your intuition.
Intuition will lead you astray; it’s drastically overrated. The
desire to follow intuition reflects the mythology of people who

4© All rights reserved. Fast Company, LLC

FC :L E A R N I N G

don’t want to think rationally and systematically. They tell sto-
ries about how their intuition guided them through a decision,
but they don’t understand how or why. Often, when you hear
about intuition, what you’re really hearing is a justification of
luck. Intuition might be fine for the small decisions in life – like
what kind of ice cream to buy. But when you get to the biggies,
you need a more systematic thought process.

One of the biggest challenges I face is teaching people how to
change their decision-making behavior. Everyone makes mis-
takes and bad decisions. I try to show people that their mistakes
are predictable.

Here’s an interesting thought experiment: You’ve got to decide
between two things – two executives to hire for a key position,
two acquisition targets, two houses that you’re thinking about
buying.

You go through a systematic process of identifying all of the fac-
tors and weighing them for each alternative. You do a little
arithmetic, and your analysis says to pick A over B. But your
intuition says to pick B over A. So what do you do?

Most people will go on their intuition – which raises the ques-
tion, Why did you do all that work in the first place? One of
these two options is wrong. So postpone your decision until you
can determine why your intuition is out of sync with the sys-
tematic analysis. That’s the purpose of systematic analysis: to
inform your intuition, to make you consider all of the options,
and to help you make a wise decision.

Max Bazerman ( mbazerman@hbs.edu ) studies decision mak-
ing, negotiation, and environmental issues. He is the author of
Judgment in Managerial Decision Making ( John Wiley &
Sons, 1986 ) and Why Smart People Make Dumb Money
Moves ( forthcoming from Wiley, April 1999 ). Bazerman is a
visiting professor of business admi nistration at Harvard
Business School.

Howard Raiffa
Professor Emeritus
Harvard Business School
Boston, Massachusetts

One of the biggest pitfalls in decision making is not creating
enough alternatives. You can make a decision in order to solve
a problem – or you can make a decision in order to exploit an
opportunity. To make this point, I use the case study of a busi-
nessman named Bill. His dilemma: to sell or not to sell his
business. Bill and his partner had struggled for years to build a
soundproofing business in Brooklyn, and finally the company
was doing well. But Bill was bored; at age 57, he wanted a
change. The solution, he thought, was to sell out to his partner,

move to California, and start a new business. He framed his
problem around how much he should sell his part of the busi-
ness for – $400,000 ( a price that his partner could afford ) or
something higher.

At my suggestion, Bill went through a rigorous process of
reframing his decision. He realized that what he wanted was to
spend more time outdoors, to be challenged intellectually, and
to minimize stress. In the end, Bill decided to move to
California and to establish a branch of the soundproofing
business there. That way, he could change his life and also be
challenged – but without taking on an enormous amount of
risk. The business did well: Eight years later, he sold out to his
partner for $1.7 million.

Howard Raiffa is a pioneer in the development of decision
analysis, negotiation analysis, and game theory. He is coauthor,
with John S. Hammond and Ralph L. Keeney, of Smart
Choices: A Practical Guide to Making Better Decisions (
Harvard Business School Press, 1998 ).

5© All rights reserved. Fast Company, LLC

FC :L E A R N I N G

Introduction

Every author, I suppose, has in mind a setting in which readers of his or her work could benefit

from having read it. Mine is the proverbial office watercooler, where opinions are shared and
gossip is exchanged. I hope to enrich the vocabulary that people use when they talk about the
judgments and choices of others, the company’s new policies, or a colleague’s investment
decisions. Why be concerned with gossip? Because it is much easier, as well as far more
enjoyable, to identify and label the mistakes of others than to recognize our own. Questioning what
we believe and want is difficult at the best of times, and especially difficult when we most need to
do it, but we can benefit from the informed opinions of others. Many of us spontaneously anticipate
how friends and colleagues will evaluate our choices; the quality and content of these anticipated
judgments therefore matters. The expectation of intelligent gossip is a powerful motive for serious
self-criticism, more powerful than New Year resolutions to improve one’s decision making at
work and at home.

To be a good diagnostician, a physician needs to acquire a large set of labels for diseases, each
of which binds an idea of the illness and its symptoms, possible antecedents and causes, possible
developments and consequences, and possible interventions to cure or mitigate the illness.
Learning medicine consists in part of learning the language of medicine. A deeper understanding of
judgments and choices also requires a richer vocabulary than is available in everyday language.
The hope for informed gossip is that there are distinctive patterns in the errors people make.
Systematic errors are known as biases, and they recur predictably in particular circumstances.
When the handsome and confident speaker bounds onto the stage, for example, you can anticipate
that the audience will judge his comments more favorably than he deserves. The availability of a
diagnostic label for this bias—the halo effect—makes it easier to anticipate, recognize, and
understand.

When you are asked what you are thinking about, you can normally answer. You believe you
know what goes on in your mind, which often consists of one conscious thought leading in an
orderly way to another. But that is not the only way the mind works, nor indeed is that the typical
way. Most impressions and thoughts arise in your conscious experience without your knowing how
they got there. You cannot tracryd>e how you came to the belief that there is a lamp on the desk in
front of you, or how you detected a hint of irritation in your spouse’s voice on the telephone, or
how you managed to avoid a threat on the road before you became consciously aware of it. The
mental work that produces impressions, intuitions, and many decisions goes on in silence in our
mind.

Much of the discussion in this book is about biases of intuition. However, the focus on error
does not denigrate human intelligence, any more than the attention to diseases in medical texts
denies good health. Most of us are healthy most of the time, and most of our judgments and actions
are appropriate most of the time. As we navigate our lives, we normally allow ourselves to be
guided by impressions and feelings, and the confidence we have in our intuitive beliefs and
preferences is usually justified. But not always. We are often confident even when we are wrong,
and an objective observer is more likely to detect our errors than we are.

So this is my aim for watercooler conversations: improve the ability to identify and understand
errors of judgment and choice, in others and eventually in ourselves, by providing a richer
and more precise language to discuss them. In at least some cases, an accurate diagnosis may
suggest an intervention to limit the damage that bad judgments and choices often cause.

7

Two Systems

The Characters of the Story

To observe your mind in automatic mode, glance at the image below.

Figure 1

Your experience as you look at the woman’s face seamlessly combines what we normally call
seeing and intuitive thinking. As surely and quickly as you saw that the young woman’s hair is
dark, you knew she is angry. Furthermore, what you saw extended into the future. You sensed that
this woman is about to say some very unkind words, probably in a loud and strident voice. A
premonition of what she was going to do next came to mind automatically and effortlessly. You did
not intend to assess her mood or to anticipate what she might do, and your reaction to the picture
did not have the feel of something you did. It just happened to you. It was an instance of fast
thinking.

Now look at the following problem:

17

×

24

You knew immediately that this is a multiplication problem, and probably knew that you could
solve it, with paper and pencil, if not without. You also had some vague intuitive knowledge of the
range of possible results. You would be quick to recognize that both 12,609 and 1

23

are
implausible. Without spending some time on the problem, however, you would not be certain that
the answer is not 568. A precise solution did not come to mind, and you felt that you could choose
whether or not to engage in the computation. If you have not done so yet, you should attempt the
multiplication problem now, completing at least part of it.

You experienced slow thinking as you proceeded through a sequence of steps. You first
retrieved from memory the cognitive program for multiplication that you learned in school, then
you implemented it. Carrying out the computation was a strain. You felt the burden of holding much
material in memory, as you needed to keep track of where you were and of where you were going,
while holding on to the intermediate result. The process was mental work: deliberate, effortful,
and orderly—a prototype of slow thinking. The computation was not only an event in your mind;
your body was also involved. Your muscles tensed up, your blood pressure rose, and your heart

17

rate increased. Someone looking closely at your eyes while you tackled this problem would have
seen your pupils dilate. Your pupils contracted back to normal size as soon as you ended your
work—when you found the answer (which is 408, by the way) or when you gave up.

Two Systems

Psychologists have been intensely interested for several decades in the two modagee fi Pn=”cees
of thinking evoked by the picture of the angry woman and by the multiplication problem, and have
offered many labels for them. I adopt terms originally proposed by the psychologists Keith
Stanovich and Richard West, and will refer to two systems in the mind, System 1 and System 2.

System 1 operates automatically and quickly, with little or no effort and no sense of voluntary
control.
System 2 allocates attention to the effortful mental activities that demand it, including
complex computations. The operations of System 2 are often associated with the subjective
experience of agency, choice, and concentration.

The labels of System 1 and System 2 are widely used in psychology, but I go further than most in
this book, which you can read as a psychodrama with two characters.

When we think of ourselves, we identify with System 2, the conscious, reasoning self that has
beliefs, makes choices, and decides what to think about and what to do. Although System 2
believes itself to be where the action is, the automatic System 1 is the hero of the book. I describe
System 1 as effortlessly originating impressions and feelings that are the main sources of the
explicit beliefs and deliberate choices of System 2. The automatic operations of System 1 generate
surprisingly complex patterns of ideas, but only the slower System 2 can construct thoughts in an
orderly series of steps. I also describe circumstances in which System 2 takes over, overruling the
freewheeling impulses and associations of System 1. You will be invited to think of the two
systems as agents with their individual abilities, limitations, and functions.

In rough order of complexity, here are some examples of the automatic activities that are
attributed to System 1:

Detect that one object is more distant than another.
Orient to the source of a sudden sound.
Complete the phrase “bread and…”
Make a “disgust face” when shown a horrible picture.
Detect hostility in a voice.
Answer to 2 + 2 = ?
Read words on large billboards.
Drive a car on an empty road.
Find a strong move in chess (if you are a chess master).
Understand simple sentences.
Recognize that a “meek and tidy soul with a passion for detail” resembles an occupational

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stereotype.

All these mental events belong with the angry woman—they occur automatically and require little
or no effort. The capabilities of System 1 include innate skills that we share with other animals.
We are born prepared to perceive the world around us, recognize objects, orient attention, avoid
losses, and fear spiders. Other mental activities become fast and automatic through prolonged
practice. System 1 has learned associations between ideas (the capital of France?); it has also
learned skills such as reading and understanding nuances of social situations. Some skills, such as
finding strong chess moves, are acquired only by specialized experts. Others are widely shared.
Detecting the similarity of a personality sketch to an occupatiohein occupatnal stereotype requires
broad knowledge of the language and the culture, which most of us possess. The knowledge is
stored in memory and accessed without intention and without effort.

Several of the mental actions in the list are completely involuntary. You cannot refrain from
understanding simple sentences in your own language or from orienting to a loud unexpected
sound, nor can you prevent yourself from knowing that 2 + 2 = 4 or from thinking of Paris when the
capital of France is mentioned. Other activities, such as chewing, are susceptible to voluntary
control but normally run on automatic pilot. The control of attention is shared by the two systems.
Orienting to a loud sound is normally an involuntary operation of System 1, which immediately
mobilizes the voluntary attention of System 2. You may be able to resist turning toward the source
of a loud and offensive comment at a crowded party, but even if your head does not move, your
attention is initially directed to it, at least for a while. However, attention can be moved away from
an unwanted focus, primarily by focusing intently on another target.

The highly diverse operations of System 2 have one feature in common: they require attention
and are disrupted when attention is drawn away. Here are some examples:

Brace for the starter gun in a race.
Focus attention on the clowns in the circus.
Focus on the voice of a particular person in a crowded and noisy room.
Look for a woman with white hair.
Search memory to identify a surprising sound.
Maintain a faster walking speed than is natural for you.
Monitor the appropriateness of your behavior in a social situation.
Count the occurrences of the letter a in a page of text.
Tell someone your phone number.
Park in a narrow space (for most people except garage attendants).
Compare two washing machines for overall value.
Fill out a tax form.
Check the validity of a complex logical argument.

In all these situations you must pay attention, and you will perform less well, or not at all, if you
are not ready or if your attention is directed inappropriately. System 2 has some ability to change
the way System 1 works, by programming the normally automatic functions of attention and
memory. When waiting for a relative at a busy train station, for example, you can set yourself at

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will to look for a white-haired woman or a bearded man, and thereby increase the likelihood of
detecting your relative from a distance. You can set your memory to search for capital cities that
start with N or for French existentialist novels. And when you rent a car at London’s Heathrow
Airport, the attendant will probably remind you that “we drive on the left side of the road over
here.” In all these cases, you are asked to do something that does not come naturally, and you will
find that the consistent maintenance of a set requires continuous exertion of at least some effort.

The often-used phrase “pay attention” is apt: you dispose of a limited budget of attention that
you can allocate to activities, and if you try to i>Cyou try tgo beyond your budget, you will fail. It
is the mark of effortful activities that they interfere with each other, which is why it is difficult or
impossible to conduct several at once. You could not compute the product of 17 × 24 while making
a left turn into dense traffic, and you certainly should not try. You can do several things at once, but
only if they are easy and undemanding. You are probably safe carrying on a conversation with a
passenger while driving on an empty highway, and many parents have discovered, perhaps with
some guilt, that they can read a story to a child while thinking of something else.

Everyone has some awareness of the limited capacity of attention, and our social behavior
makes allowances for these limitations. When the driver of a car is overtaking a truck on a narrow
road, for example, adult passengers quite sensibly stop talking. They know that distracting the
driver is not a good idea, and they also suspect that he is temporarily deaf and will not hear what
they say.

Intense focusing on a task can make people effectively blind, even to stimuli that normally attract
attention. The most dramatic demonstration was offered by Christopher Chabris and Daniel
Simons in their book The Invisible Gorilla. They constructed a short film of two teams passing
basketballs, one team wearing white shirts, the other wearing black. The viewers of the film are
instructed to count the number of passes made by the white team, ignoring the black players. This
task is difficult and completely absorbing. Halfway through the video, a woman wearing a gorilla
suit appears, crosses the court, thumps her chest, and moves on. The gorilla is in view for 9
seconds. Many thousands of people have seen the video, and about half of them do not notice
anything unusual. It is the counting task—and especially the instruction to ignore one of the teams
—that causes the blindness. No one who watches the video without that task would miss the
gorilla. Seeing and orienting are automatic functions of System 1, but they depend on the allocation
of some attention to the relevant stimulus. The authors note that the most remarkable observation of
their study is that people find its results very surprising. Indeed, the viewers who fail to see the
gorilla are initially sure that it was not there—they cannot imagine missing such a striking event.
The gorilla study illustrates two important facts about our minds: we can be blind to the obvious,
and we are also blind to our blindness.

Plot Synopsis

The interaction of the two systems is a recurrent theme of the book, and a brief synopsis of the plot
is in order. In the story I will tell, Systems 1 and 2 are both active whenever we are awake. System
1 runs automatically and System 2 is normally in a comfortable low-effort mode, in which only a
fraction of its capacity is engaged. System 1 continuously generates suggestions for System 2:
impressions, intuitions, intentions, and feelings. If endorsed by System 2, impressions and
intuitions turn into beliefs, and impulses turn into voluntary actions. When all goes smoothly, which
is most of the time, System 2 adopts the suggestions of System 1 with little or no modification. You
generally believe your impressions and act on your desires, and that is fine—usually.

When System 1 runs into difficulty, it calls on System 2 to support more detailed and specific

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processing that may solve the problem of the moment. System 2 is mobilized when a question
arises for which System 1 does not offer an answer, as probably happened to you when you
encountered the multiplication problem 17 × 24. You can also feel a surge of conscious attention
whenever you are surprised. System 2 is activ”>< 2 is actated when an event is detected that violates the model of the world that System 1 maintains. In that world, lamps do not jump, cats do not bark, and gorillas do not cross basketball courts. The gorilla experiment demonstrates that some attention is needed for the surprising stimulus to be detected. Surprise then activates and orients your attention: you will stare, and you will search your memory for a story that makes sense of the surprising event. System 2 is also credited with the continuous monitoring of your own behavior—the control that keeps you polite when you are angry, and alert when you are driving at night. System 2 is mobilized to increased effort when it detects an error about to be made. Remember a time when you almost blurted out an offensive remark and note how hard you worked to restore control. In summary, most of what you (your System 2) think and do originates in your System 1, but System 2 takes over when things get difficult, and it normally has the last word.

The division of labor between System 1 and System 2 is highly efficient: it minimizes effort and
optimizes performance. The arrangement works well most of the time because System 1 is
generally very good at what it does: its models of familiar situations are accurate, its short-term
predictions are usually accurate as well, and its initial reactions to challenges are swift and
generally appropriate. System 1 has biases, however, systematic errors that it is prone to make in
specified circumstances. As we shall see, it sometimes answers easier questions than the one it
was asked, and it has little understanding of logic and statistics. One further limitation of System 1
is that it cannot be turned off. If you are shown a word on the screen in a language you know, you
will read it—unless your attention is totally focused elsewhere.

Conflict

Figure 2 is a variant of a classic experiment that produces a conflict between the two systems. You
should try the exercise before reading on.

Figure 2

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You were almost certainly successful in saying the correct words in both tasks, and you surely
discovered that some parts of each task were much easier than others. When you identified upper-
and lowercase, the left-hand column was easy and the right-hand column caused you to slow down
and perhaps to stammer or stumble. When you named the position of words, the left-hand column
was difficult and the right-hand column was much easier.

These tasks engage System 2, because saying “upper/lower” or “right/left” is not what you
routinely do when looking down a column of words. One of the things you did to set yourself for
the task was to program your memory so that the relevant words (upper and lower for the first
task) were “on the tip of your tongue.” The prioritizing of the chosen words is effective and the
mild temptation to read other words was fairly easy to resist when you went through the first
column. But the second column was different, because it contained words for which you were set,
and you could not ignore them. You were mostly able to respond correctly, but overcoming the
competing response was a strain, and it slowed you down. You experienced a conflict between a
task that you intended to carry out and an automatic response that interfered with it.

Conflict between an automatic reaction and an intention to conWhetion to ctrol it is common in
our lives. We are all familiar with the experience of trying not to stare at the oddly dressed couple
at the neighboring table in a restaurant. We also know what it is like to force our attention on a
boring book, when we constantly find ourselves returning to the point at which the reading lost its
meaning. Where winters are hard, many drivers have memories of their car skidding out of control
on the ice and of the struggle to follow well-rehearsed instructions that negate what they would
naturally do: “Steer into the skid, and whatever you do, do not touch the brakes!” And every human
being has had the experience of not telling someone to go to hell. One of the tasks of System 2 is to
overcome the impulses of System 1. In other words, System 2 is in charge of self-control.

Illusions

To appreciate the autonomy of System 1, as well as the distinction between impressions and
beliefs, take a good look at figure 3.

This picture is unremarkable: two horizontal lines of different lengths, with fins appended,
pointing in different directions. The bottom line is obviously longer than the one above it. That is
what we all see, and we naturally believe what we see. If you have already encountered this
image, however, you recognize it as the famous Müller-Lyer illusion. As you can easily confirm by
measuring them with a ruler, the horizontal lines are in fact identical in length.

Figure 3

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Now that you have measured the lines, you—your System 2, the conscious being you call “I”—
have a new belief: you know that the lines are equally long. If asked about their length, you will
say what you know. But you still see the bottom line as longer. You have chosen to believe the
measurement, but you cannot prevent System 1 from doing its thing; you cannot decide to see the
lines as equal, although you know they are. To resist the illusion, there is only one thing you can
do: you must learn to mistrust your impressions of the length of lines when fins are attached to
them. To implement that rule, you must be able to recognize the illusory pattern and recall what you
know about it. If you can do this, you will never again be fooled by the Müller-Lyer illusion. But
you will still see one line as longer than the other.

Not all illusions are visual. There are illusions of thought, which we call cognitive illusions.
As a graduate student, I attended some courses on the art and science of psychotherapy. During one
of these lectures, our teacher imparted a morsel of clinical wisdom. This is what he told us: “You
will from time to time meet a patient who shares a disturbing tale of multiple mistakes in his
previous treatment. He has been seen by several clinicians, and all failed him. The patient can
lucidly describe how his therapists misunderstood him, but he has quickly perceived that you are
different. You share the same feeling, are convinced that you understand him, and will be able to
help.” At this point my teacher raised his voice as he said, “Do not even think of taking on this
patient! Throw him out of the office! He is most likely a psychopath and you will not be able to
help him.”

Many years later I learned that the teacher had warned us against psychopathic charm, and the
leading authority in the strn y in the udy of psychopathy confirmed that the teacher’s advice was
sound. The analogy to the Müller-Lyer illusion is close. What we were being taught was not how
to feel about that patient. Our teacher took it for granted that the sympathy we would feel for the
patient would not be under our control; it would arise from System 1. Furthermore, we were not
being taught to be generally suspicious of our feelings about patients. We were told that a strong
attraction to a patient with a repeated history of failed treatment is a danger sign—like the fins on
the parallel lines. It is an illusion—a cognitive illusion—and I (System 2) was taught how to
recognize it and advised not to believe it or act on it.

The question that is most often asked about cognitive illusions is whether they can be overcome.
The message of these examples is not encouraging. Because System 1 operates automatically and
cannot be turned off at will, errors of intuitive thought are often difficult to prevent. Biases cannot
always be avoided, because System 2 may have no clue to the error. Even when cues to likely
errors are available, errors can be prevented only by the enhanced monitoring and effortful activity
of System 2. As a way to live your life, however, continuous vigilance is not necessarily good, and
it is certainly impractical. Constantly questioning our own thinking would be impossibly tedious,
and System 2 is much too slow and inefficient to serve as a substitute for System 1 in making
routine decisions. The best we can do is a compromise: learn to recognize situations in which
mistakes are likely and try harder to avoid significant mistakes when the stakes are high. The
premise of this book is that it is easier to recognize other people’s mistakes than our own.

Useful Fictions

You have been invited to think of the two systems as agents within the mind, with their individual
personalities, abilities, and limitations. I will often use sentences in which the systems are the
subjects, such as, “System 2 calculates products.”

The use of such language is considered a sin in the professional circles in which I travel,
because it seems to explain the thoughts and actions of a person by the thoughts and actions of little

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people inside the person’s head. Grammatically the sentence about System 2 is similar to “The
butler steals the petty cash.” My colleagues would point out that the butler’s action actually
explains the disappearance of the cash, and they rightly question whether the sentence about
System 2 explains how products are calculated. My answer is that the brief active sentence that
attributes calculation to System 2 is intended as a description, not an explanation. It is meaningful
only because of what you already know about System 2. It is shorthand for the following: “Mental
arithmetic is a voluntary activity that requires effort, should not be performed while making a left
turn, and is associated with dilated pupils and an accelerated heart rate.”

Similarly, the statement that “highway driving under routine conditions is left to System 1”
means that steering the car around a bend is automatic and almost effortless. It also implies that an
experienced driver can drive on an empty highway while conducting a conversation. Finally,
“System 2 prevented James from reacting foolishly to the insult” means that James would have
been more aggressive in his response if his capacity for effortful control had been disrupted (for
example, if he had been drunk).

System 1 and System 2 are so central to the story I tell in this book that I must make it absolutely
clear that they are217at they a fictitious characters. Systems 1 and 2 are not systems in the standard
sense of entities with interacting aspects or parts. And there is no one part of the brain that either
of the systems would call home. You may well ask: What is the point of introducing fictitious
characters with ugly names into a serious book? The answer is that the characters are useful
because of some quirks of our minds, yours and mine. A sentence is understood more easily if it
describes what an agent (System 2) does than if it describes what something is, what properties it
has. In other words, “System 2” is a better subject for a sentence than “mental arithmetic.” The
mind—especially System 1—appears to have a special aptitude for the construction and
interpretation of stories about active agents, who have personalities, habits, and abilities. You
quickly formed a bad opinion of the thieving butler, you expect more bad behavior from him, and
you will remember him for a while. This is also my hope for the language of systems.

Why call them System 1 and System 2 rather than the more descriptive “automatic system” and
“effortful system”? The reason is simple: “Automatic system” takes longer to say than “System 1”
and therefore takes more space in your working memory. This matters, because anything that
occupies your working memory reduces your ability to think. You should treat “System 1” and
“System 2” as nicknames, like Bob and Joe, identifying characters that you will get to know over
the course of this book. The fictitious systems make it easier for me to think about judgment and
choice, and will make it easier for you to understand what I say.

Speaking of System 1 and System 2

“He had an impression, but some of his impressions are illusions.”

“This was a pure System 1 response. She reacted to the threat before she recognized it.”

“This is your System 1 talking. Slow down and let your System 2 take control.”

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