Part 1
Two Systems
1
The Characters of the Story
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 gorilla study illustrates two important facts about our minds: we can be blind to the obcious, and we are also blind to our blindness.
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.
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.
2
Attention and effort
As you become skilled in a task, its demand for energy diminishes.
A general "law of least effort" applies to cognitive as well as physical exertion. The law asserts that if there are several ways of achieving the same goal, people will eventually gravitate to the least demanding course of action.
3
The Lazy Controller
Self-control and deliberate thought apparently draw on the same limited budget of effort.
In a state of flow, however, maintaining focused attention on these absorbing activities requires no exertion of self-control, thereby freeing resources to be directed to the task at hand.
It is now a well-established proposition that both self-control and cognitive effort are forms of mental work. Several psychological studies have shown that people who are simultaneously challenged by a demanding cognitive task and by a temptation are more likely to yield to the temptation.
System 1 has more influence on behavior when System 2 is busy, and it has a sweet tooth.
The conclusion is straightforward: self-control requires attention and effort. Another way of saying this is that controlling thoughts and behaviors is one of the tasks that System 2 performs.
Baumeister's group has repeatedly found that an effort of will or self-control is tiring; if you have had to force yourself to do something, you are less willing or less able to exert self-control when the next challenge comes around.
The evidence is persuasive: activities that impose high demands on System 2 require self-control, and the exertion of self-control is depleting and unpleasant...After exerting self-control in one task, you do not feel like making an effort in another, although you could do it if you really had to.
When you are actively involved in difficult cognitive reasoning or engaged in a task that requires self-control, your blood glucose level drops. The effect is analogous to a runner who draws down glucose stored in her muscles during a sprint. The bold implication of this idea is that the effects of ego depletion could be undone by ingesting glucose, and Baumeister and his colleagues have confirmed this hypothesis in several experiments.
Intelligence is not only the ability to reason; it is also the ability to find relevant material in memory and to deploy attention when needed. Memory function is an attribute of System 1. However, everyone has the option of slowing down to conduct an active search of memory for all possibly relevant facts - just as they could slow down to check the intuitive answer in the bat-and-ball problem. The extent of deliberate checking and search is a characteristic of System 2, which varies among individuals.
These students can solve much more difficult problems when they are not tempted to accept a superficially plausible answer that comes readily to mind. The ease with which they are satisfied enough to stop thinking is rather troubling.
4
The Associative Machine
This complex constellation of responses occurred quickly, automatically, and effortlessly. You did not will it and you could not stop it. It was an operation of System 1. The events that took place as a result of your seeing the words happened by a process called associativie activation: ideas that have been evoked trigger many other ideas, in a spreading cascasde of activitiy in your brain.
If you have recently seen or heard the word EAT, you are temporarily more likely to complete the word fragment SO_P as SOUP than as SOAP. The opposite would happen, of course, if you had just seen WASH. We call this a priming effect and say that the idea of EAT primes the idea of SOUP, and that WASH primes SOAP.
Again, there was no awareness, just a habitual connection between an attitude of rejection or acceptance and its common physical expression. You can see why the common admonition to "act calm and kind regardless of how you feel" is very good advice: you are likely to be rewarded by actually feeling calm and kind.
The general theme of these findings is that the idea of money primes individualism: a reluctance to be involved with others, to depend on others, or to accept demands from others.
If you had been exposed to a screen saver of floating dollar bills, you too would likely have picked up fewer pencils to help a clumsy stranger. You do not believe that these results apply to you because they correspond to nothing in your subjective experience. But your subjective experience consists largely of the story that your System 2 tells itself about what is going on. Priming phenomena arise in System 1, and you have no conscious access to them.
System 1 provides the impressions that often turn into your beliefs, and is the source of the impulses that often become your choices and your actions.
5
Cognitive Ease
The impression of familiarity is produced by System 1, and System 2 relies on that impression for a true/false judgment.
A reliable way to make people believe in falsehoods is frequent repetition, because familiarity is not easily distinguished from truth.
But it was psychologists who discovered that you do not have to repeat the entire statement of a fact or idea to make it appear true. People who were repeatedly exposed to the phrase "the body temperature of a chicken" were more likely to accept as true the statement that "the body temperature of a chicken is 144° (or any other arbitrary number). The familiarity of one phrase in the statement sufficed to make the whole statement feel familiar, and therefore true.
The general principle is that anything you can do to reduce cognitive strain will help, so you should first maximize legibility. Compare these two statements:
Adolf Hitler was born in 1892
Adolf Hitler was born in 1887.
Both are false (Hitler was born in 1889), but experiments have shown that the first is more likely to be believed.
If you care about being thought credible and intelligent, do not use complex language where simpler language will do.
In an article titled "Consequences of Erudite Vernacular Utilized Irrespective of Necessity: Problems with Using Long Words Needlessly," he showed that couching familiar ideas in pretentious language is taken as a sign of poor intelligence and low credibility.
In addition to making your message simple, try to make it memorable...
Woes unite foes.
Little strokes will tumble great oaks.
A fault confessed is half redressed.
Woes unite enemies.
Little strokes will tumble great trees.
A fault admitted is half redressed.
...The aphorisms were judged more insightful when they rhymed than when they did not.
Cognitive strain, whatever its source, mobilizes System 2, which is more likely to reject the intuitive answer suggested by System 1.
It appears to be a feature of System 1 that cognitive ease is associated with good feelings.
The mere exposure effect does not depend on the conscious experience of familiarity. In fact, the effect does not depend on consciousness at all: it occurs even when the repeated words or pictures are shown so quickly that the observers never become aware of having seen them. They still end up liking the words or pictures that were presented more frequently.
The link between positive emotion and cognitive ease in System 1 has a long evolutionary history.
Mood evidently affects the operation of System 1: when we are uncomfortable and unhappy, we lose touch with our intuition.
A happy mood loosens the control of System 2 over performance: when in a good mood, people become more intuitive and more creative but also less vigilant and more prone to logical errors.
Cognitive ease and smiling occur together, but do the good feelings actually lead to intuitions of coherence? Yes, they do.
6
Norms, Surprises, And Causes
When something does not fit into the current context of activated ideas cement, the system detects an abnormality, as you just experienced. You had no particular idea of what was coming after ideas, but you knew when the word cement came that it was abnormal in that sentence. Studies of brain responses have shown that violations of normality are detected with astonishing speed and subtlety.
System 1, which understands language, has access to norms of categories, which specify the range of plausible values as well as the most typical cases.
Read this sentence:
After spending a day exploring beautiful sights in the crowded streets of New York, Jane discovered that her wallet was missing.
When people who had read this brief story (along with many others) were given a surprise recall test, the word pickpocket was more strongly associated with the story than the word sights, even though the latter was actually in the sentence while the former was not.
7
A Machine for Jumping to Conclusions
In a later test of memory, the depleted participants ended up thinking that many of the false sentences were true. The moral is significant: when System 2 is otherwise engaged, we will believe almost anything. System 1 is gullible and biased to believe, System 2 is in charge of doubting and unbelieving, but System 2 is sometimes busy, and often lazy. Indee, there is evidence that people are more likely to be influenced by empty persuasive messages, such as commercials, when they are tired and depleted.
If you like the predisent's politics, you probably like his voice and his appearance as well. The tendency to like (or dislike) everything about a person - including things you have not observed - is known as the halo effect.
You meet a woman named Joan at a party and find her personable and easy to talk to. Now her name comes up as someone who could be asked to contribute to a charity. What do you know about Joan's generosity? The correct answer is that you know virtually nothing, because there is little reason to believe that people who are agreeable in social situations are also generous contributors to charities. But you like Joan and you will retrieve the feeling of liking her when you think of her. You also like generosity and generous people. By association, you are now predisposed to believe that Joan is generous. And now that you believe she is generous, you probably like Joan even better than you did earlier, because you have added generosity to her pleasant attributes.
What do you think of Alan and Ben?
Alan: intelligent - industrious - impulsive - critical - stubborn - envious
Ben: envious - stubborn - critical - impulsive - industrious - intelligent
If you are like most of us, you viewed Alan much more favorably than Ben. The initial traits in the list change the very meaning of the traits that appear later. The stubbornness of an intelligent person is seen as likely to be justified and may actually evoke respect, but intelligence in an envious and stubborn person makes him more dangerous.
When information is scarce, which is a common occurrence, System 1 operates as a machine for jumping to conclusions. Consider the following: "Will Mindik be a good leader? She is intelligent and strong..." An answer quickly came to your mind, and it was yes. You picked the best answer based on the very limited information available, but you jumped the gun. What if the next two adjectives were corrupt and cruel?
Take note of what you did not do as you briefly thought of Mindik as a leader. You did not start by asking, "What would I need to know before I formed an opinion about the quality of someone's leadership?" System 1 got to work on its own from the first adjective: intelligent is good, intelligent and strong is very good. This is the best story that can be constructed from two adjectives, and System 1 delivered it with great cognitive ease. The story will be revised if new information comes in (such as Mindik is corrupt), but there is no waiting and no subjective discomfort. And there also remains a bias favoring the first impression.
Furthermore, participants who saw one-sided evidence were more confident of their judgments than those who saw both sides. This is just what you would expect if the confidence that people experience is determined by the coherence of the story they manage to construct from available information. It is the consistency of the information that matters for a good story, not its completeness. Indeed, you will often find that knowing little makes it easier to fit everything you know into a coherent pattern.
However, I will also invoke WYSIATI (What You See is All There is) to help explain a long and diverse list of biases of judgment and choice, including the following among many others:
• Overconfidence: As the WYSIATI rule implies, neither the quantity nor the quality of the evidence counts for much in subjective confidence. The confidence that individuals have in their beliefs depends mostly on the quality of the story they can tell about what they see, evin if they see little. We often fail to allow for the possibility that evidence that should be critical to our judgment is missing - what we see is all there is.
• Framing effects: Different ways of presenting the same information often evoke different emotions. The statement that "the odds of survival one month after surgery are 90%" is more reassuring than the equivalent statement that "mortality within one month of surgery is 10%." Similarly, cold cuts described as "90% fat-free" are more attractive than when they are described as "10% fat."
"They didn't want more information that might spoil their story. WYSIATI."
8
How Judgments Happen
System 1 has been shaped by evolution to provide a continuous assessment of the main problems that an organism must solve to survive: How are things going? Is there a threat or a major opportunity? Is everything normal? Should I approach or avoid? The questions are perhaps less urgent for a human in a city environment than for a gazelle on the savannah, but we have inherited the neural mechanisms that evolved to provide ongoing assessments of threat level, and they have not been turned off. Situations are constantly evaluated as good or bad, requiring escape or permitting approach. Good mood and cognitive ease are the human equivalents of assessments of safety and familiarity.
Todorov has found that people judge competence by combining the two dimensions of strength and trustworthiness. The faces that exude competence combine a strong chin with a slight confident-appearing smile. There is no evidence that these facial features actually predict how well politicians will perform in office. But studies of the brain's response to winning and losing candidates show that wea are biologically predisposed to reject candidates who lack the attributes we value - in this research, losers evoked stronger indications of (negative) emotional response.
Because System 1 represents categories by a prototype or a set of typical exemplars, it deals well with averages but poorly with sums.
What are the correct responses for the following sentences?
Some roads are snakes.
Some jobs are snakes.
Some jobs are jails.
All three sentences are literally false. However, you probably noticed that the second sentence is more obviously flase than the other two - the reaction times collected in the experiment confirmed a substantial difference. The reason for the difference is that the two difficult sentences can be metaphorically true. Here again, the intention to perform one computation evoked another. And here again, the correct answer prevailed in the conflice, but the conflict with the irrelevant answer disrupted performance.
9
Answering An Easier Question
The normal state of your mind is that you have intuitive feelings and opinions about almost everything that comes your way. You like or dislike people long before you know much about them; you trust or distrust strangers without knowing why; you feel that an enterprise is bound to succeed without analyzing it. Whether you state them or not, you often have answers to questions that you do not completely understand, relying on evidence that you can neither explain nor defend.
I propose a simple account of how we generate intuitive opinions on complex matters. If a satisfactory answer to a hard question is not found quickly, System 1 will find a related question that is easier and will answer it. I call the operation of answering one question in place of another substitution. I also adopt the following terms:
The target question is the assessment you intend to produce.
The heuristic question is the simpler question that you answer instead.
The technical definition of heuristic is a simple procedure that helps find adequate, though often imperfect, answers to difficult questions. The word comes from the same root as eureka.
The mental shotgun makes it easy to generate quick answers to difficult questions without imposing much hard work on your lazy System 2. The right-hand counterpart of each of the left-hand questions is very likely to be evoked and very easily answered. Your feelings about dolphins and financial crooks, your current mood, your impressions of the political skill of the primary candidate, or the current standing of the president will readily come to mind. The heuristic questions provide an off-the-shelf answer to each of the difficult target questions.
Another capability of System 1, intensity matching, is available to solve that problem. Recall that both feelings and contribution dollars are intensity scales. I can feel more or less strongly about dolphins and there is a contribution that matches the intensity of my feelings. The dollar amount that will come to my mind is the matching amount.
On some occasions, substitution will occur and a heuristic answer will be endorsed by System 2. Of course, System 2 has the opportunity to reject this intuitive answer, or to modify it by incorporating other information. However, a lazy System 2 often follows the path of least effort and endorses a heuristic answer without much scrutiny of whether it is truly appropriate. You will not be stumped, you will not have to work very hard, and you may not even notice that you did not answer the question you were asked. Furthermore, you may not realize that the target question was difficult, because an intuitive answer to it came readily to mind.
You were not confused about the question, but you were influenced by the answer to a question that you were not asked...
The survey that the young participants completed included the following two questions:
How happy are you these days?
How many dates did you have last month?
Would the students who reported many dates say that they were happier than those with fewer dates? Surprisingly, no: the correlation between the answers was about zero.
Another group of students saw the same two questions, but in reverse order:
How many dates did you have last month?
How happy are you these days?
The results this time were completely different. In this sequence, the correlation between the number of dates and reported happiness was about as high as correlations between psychological measures can get. What happened?...The students who had many dates were reminded of a happy aspect of their life, while those who had none were reminded of loneliness and rejection.
WYSIATI. The present state of mind looms very large when people evaluate their happiness.
The dominance of conclustions over arguments is most pronounced where emotions are involved. The psychologist Paul Slovic has proposed an affect heuristic in which people let their likes and dislikes determine their beliefs about the world.
Your emotional attitude to such things as irradiated food, red meat, nuclear power, tattoos, or motorcycles drives your beliefs about their benefits and their risks. If you dislike any of these things, you probably believe that its risks are high and its benefits negligible.
In the context of attitudes, however, System 2 is more of an apologist for the emotions of System 1 than a critic of those emotions - an endorser rather than an enforcer. Its search for information and arguments is mostly constrained to information that is consistent with existing beliefs, not with an intention to examine them.
"Do we still remember the question we are trying to answer? Or have we substituted an easier one?"
Part 2
Heuristics and Biases
10
The Law of Small Numbers
The bottom line: yes, you did know that the results of large samples are more precise, but you may now realize that you did not know it very well.
If you are the researcher, this outcome is costly to you because you have wasted time and effort, and failed to confirm a hypothesis that was in fact true. Using a sufficiently large sample is the only way to reduce the risk. Researchers who pick too small a sample leave themselves at the mercy of sampling luck.
The author pointed out that psychologists commonly choose samples so small that they exposed themselves to a 50% risk of failing to confirm their true hypotheses! No researcher in his right mind would accept such a risk. A plausible explanation was that psychologists' decisions about sample size reflected prevalent intuitive misconceptions of the extent of sampling variation.
But do you discriminate sufficiently between "I read in The New York Times..." and "I heard at the watercooler..."? Can your System 1 distinguish degrees of belief? The principle of WYSIATI suggests that it cannot.
As I described earlier, System 1 is not prone to doubt. It suppresses ambiguity and spontaneously constructs stories that are as coherent as possible. Unless the message is immediately negated, the associations that it evokes will spread as if the message were true.
The strong bias toward believing that small samples closely resemble the population from which they are drawn is also part of a larger story: we are prone to exaggerate the consistency and coherence of what we see.
We do not expect to see regularity produced by a random process, and when we detect what appears to be a rule, we quickly reject the idea that the process is truly random. Random processes produce many sequences that convince people that the process is not random after all.
A careful statistical analysis revealed that the distribution of hits was typical of a random process - and typical as well in evoking a strong impression that it was not random. "To the untrained eye," Feller remarks, "randomness appears as regularity or tendency to cluster."
We are far too willing to reject the belief that much of what we see in life is random.
Unfortunately, the causal analysis is pointless because the facts are wrong. If the statisticians who reported to the Gates Foundation had asked about the characteristics of the worst school, they would have found that bad schools also tend to be smaller than average. The truth is that small schools are not better on average; they are simply more variable.
...the law of small numbers is part of two larger stories about the workings of the mind.
• The exaggerated faith in small samples is only one example of a more general illustion - we pay more attention to the content of messages than to information about their reliability, and as a result end up with a view of the world around us that is simpler and more coherent than the data justify. Jumping to conclustions is a safer sport in the world of our imagination than it is in reality.
• Statistics produce many observations that appear to beg for causal explanations but do not lend themselves to such explanations. Many facts of the world are due to chance, including accidents of sampling. Causal explanations of chance events are inevitably wrong.
11
Anchors
The phenomenon we were studying is so common and so important in the everyday world that you should know its name: it is an anchoring effect. It occurs when people consider a particular value for an unknown quantitiy before estimating that quantity. What happens is one of the most reliable and robust results of experimental psychology: the estimates stay close to the number that people considered - hence the image of an anchor. If you are asked whether Gandhi was more than 114 years old when he died you will end up with a much higher estimate of his age at death than you would if the anchoring question referred to death at 35. If you consider how much you should pay for a house, you will be influenced by the asking price. The same house will appear more valuable if its listing price is high than if it is low, even if you are determined to resist the influence of this number; and so on - the list of anchoring effects is endless. Any number that you are asked to consider as a possible solution to an estimation problem will induce an anchoring effect.
Two different mechanisms produce anchoring effects - one for each system. There is a form of anchoring that occurs in a deliberate process of adjustment, an operation of System 2. And there is anchoring that occurs by a priming effect, an automatic manifestation of System 1.
Insufficient adjustment is a failure of a weak or lazy System 2.
Is the height of the tallest redwood more or less than 1,200 feet?
What is your best guess about the height of the tallest redwood?
The "high anchor" in this experiment was 1,200 feet. For other participants, the first question rerferred to a "low anchor" of 180 feet. The difference between the two anchors was 1,020 feet.
As expected, the two groups produced very different mean estimates: 844 and 282 feet.
When no anchor was mentioned, the visitors at the Exploratorium - generally an environmentally sensitive crowd - said they were willing to pay $64, on average. When the anchoring amount was only $5, contributions averaged $20. When the anchor was a rather extravagant $400, the willingness to pay rose to an average of $143.
However, a key finding of anchoring research is that anchors that are obviously random can be just as effective as potentially informative anchors.
The conclusion is clear: anchors do not have their effects because people believe they are informative.
German judges with an average of more than fifteen years of experience on the bench first read a description of a woman who had been caught shoplifting, then rolled a pair of dice that were loaded so every roll resulted in either a 3 or a 9. As soon as the dice came to a stop, the judges were asked whether they would sentence the woman to a term in prison greater or lesser, in months, than the number showing on the dice. Finally, the judges were instructed to specify the exact prison sentence they would give to the shoplifter. On average, those who had rolled a 9 said they would sentence her to 8 months; those who rolled a 3 said they would sentence her to 5 months; the anchoring effect was 50%.
My advice to students when I taught negotiations was that if you think the other sid has made an outrageous proposal, you should not come back with an equally outrageous counteroffer, creating a gap that will be difficult to bridge in further negotiations. Instead you should make a scene, storm out or threaten to do so, and make it clear - to yourself as well as to the other side - that you will not continue the negotiation with that number on the table.
Finally, try your hand at working out the effect of anchoring on a problem of public policy: the size of damages in personal injury cases. These awards are sometimes very large. Businesses that are frequent targets of such lawsuits, such as hospitals and chemical companies, have lobbied to set a cap on the awards. Before you read this chapter you might have thought that capping awards is certainly good for potential defendants, but now you should not be so sure. COnsider the effect of capping awards at $1 million. This rule would eliminate all larger awards, but the anchor would also pull up the size of many awards that would otherwise be much smaller. It would almost certainly benefit serious offenders and large firms much more than small ones.
The main moral of priming research is that our thoughts and our behavior are influenced, much more than we know or want, by the environment of the moment.
However, you should assume that any number that is on the table has had an anchoring effect on you, and if the stakes are high you should mobilize yourself (your System 2) to combat the effect.
12
The Science of Availability
The availability heuristic, like other heuristics of judgment, substitutes one question for another: you wish to estimate the size of a category or the frequency of an event, but you report an impression of the ease with which instances come to mind.
You will occasionally do more than your share, but it is useful to know that you are likely to have that feeling even when each member of the team feels the same way.
Which will count more - the amount retrieved or the ease and fluency of the retrieval?
The contest yielded a clear-cut winner: people who had just listed twelve instances reated themselves as less assertive than people who had listed only six. Furthermore, participants who had been asked to list twelve cases in which they had not behaved assertively ended up thinking of themselves as quite assertive!
For example, people:
• believe that they use their bicycles less often after recalling many rather than few instances
• are less confident in a choice when they are asked to produce more arguments to support it
• are less confident that an event was avoidable after listing more ways it could have been avoided
• are less impressed by a car after listing many of its advantages
The subjects have an experience of diminishing fluency as they produce instances. They evidently have expectations about the rate at which fluency decreases, and those expectations are wrong: the difficulty of coming up with new instances increases more rapidly than they expect. It is the unexpectedly low fluency that causes people who were asked for twelve instances to describe themselves as unassertive. When the surprise is eliminated, low fluency no longer influences the judgment. The process appears to consist of a sophisticated set of inferences. Is the automatic System 1 capable of it?
The students with a family history of heart disease showed the opposite pattern - they felt safer when they retrieved many instances of safe behavior and felt greater danger when they retrieved many instances of risky behavior. They were also more likely to feel that their future behavior would be affected by the experience of evaluating their risk.
Multiple lines of evidence converge on the conclustion that people who let themselves be guided by System 1 are more strongly susceptible to availability biases than others who are in a state of higher vigilance.
13
Availability, Emotion, and Risk
The lesson is clear: estimates of causes of death are warped by media coverage. The coverage is itself biased toward novelty and poignancy. The media do not just shape what the public is interested in, but also are shaped by it.
The world in our heads is not a precise replica of reality; our expectations about the frequency of events are distorted by the prevalence and emotional intensity of the messages to which we are exposed.
As mentioned earlier, Slovic eventually developed the notion of an affect heuristic, in which people make judgments and decisions by consulting their emotions: Do I like it? Do I hate it? How strongly do I feel about it? In many domains of life, Slovic said, people form opinions and make choices that directly express their feelings and their basic tendency to approach or avoid, often without knowing that they are doing so. The affect heuristic is an instance of substitution, in which the answer to an easy question (How do I feel about it?) serves as an answer to a much harder question (What do I think about it?).
His view is that the existing system of regulation in the United States displays a very poor setting of priorities, which reflects reaction to public pressures more than careful objective analysis.
Lawmakers and regulators may be overly responsive to the irrational concerns of citizens, both because of political sensitivity and because they are prone to the same cognitive biases as other citizens.
An availability cascade is a self-sustaining chain of events, which may start from media reports of a relatively minor event and lead up to public panic and large-scale government action. On some occasions, a media story about a risk catches the attention of a segment of the public, which becomes aroused and worried. This emotional reaction becomes a story in itself, prompting additional coverage in the media, which in turn produces greater concern and involvement. The cycle is sometimes sped along deliberately by "availability entrepreneurs," individuals or organizations who work to ensure a continuous flow of worrying news. The danger is increasingly exaggerated as the media compete for attention-grabbing headlines. Scientists and others who try to dampen the increasing fear and revulsion attract little attention, most of it hostile: anyone who claims that the danger is overstated is suspected of association with a "heinous cover-up." The issue becomes politically important because it is on everyone's mind, and the response of the political system is guided by the intensity of public sentiment. The availability cascade has now reset priorities. Other risks, and other ways that resources could be applied for the public good, all have faded into the background.
The Alar tale illustrates a basic limitation in the ability of our mind to deal with small risks: we either ignore them altogether or give them far too much weight - nothing in between.
As Slovic has argued, the amount of concern is not adequately sensitive to the probability of harm; you are imagining the numerator - the tragic story you saw on the news - and not thinking about the denominator, which includes many safe cases. Sunstein has coined the phrase "probability neglect" to describe the pattern. The combination of probability neglect with the social mechanisms of availability cascades inevitably leads to gross exaggeration of minor threats, sometimes with important consequences.
Where do i come down in the debate between my friends? Availability cascades are real and they undoubtedly distort priorities in the allocation of public resources. Cass Sunstein would seek mechanisms that insulate decision makers from public pressures, letting the allocation of resources be determined by impartial experts who have a broad view of all risks and of the resources available to reduce them. Paul Slovic trusts the experts much less and the public somewhat more than Sunstein does, and he points out that insulating the experts from the emotions of the public produces policies that the public will reject - an impossible situation in a democracy. Both are eminently sensible, and I agree with both.
I share Sunstein's discomfort with the influence of irrational fear and availability cascades on public policy in the domain of risk. However, I also share Slovic's belief that widespread fear, evin if they are unreasonable, should not be ignored by policy makers. Rational or not, fear is painful and debilitating, and policy makers must endeavor to protect the public from fear, not only from real dangers.
14
Tom W's Specialty
To decide whether a marble is more likely to be red or green, you need to know how many omarbles of each color there are in the urn. The proportion of marbles of a particular kind is called a base rate.
Using base-rate information is the obvious move when no other information is provided.
The task of ranking the nine careers is complex and certainly requires the discipline and sequential oranization of which only System 2 is capable. However, the hints planted in the description (corny puns and others) were intended to activate an association with a stereotype, an automatic activity of System 1.
Here is an example: you see a person reading The New York Times on the New York subway. Which of the following is a better bet about the reading stranger?
She has a PhD.
She does not have a college degree.
Representativeness would tell you to bet on the PhD, but his is not necessarily wise. You should seriously consider the second alternative, because many more nongraduates than PhDs ride in New York subways.
Half the students were told to puff out their cheeks during the task, while the others were told to frown. Frowning, as we have seen, generally increases the vigilance of System 2 and reduces both overconfidence and the reliance on intuition. The students who puffed on their cheeks (an emotionaly neutral expression) replicated the original results: they relied exclusively on representativeness and ignored the base rates. As the authors had predicted, however, the frowners did show some sensitivity to the base rates. This is an instructive finding.
The second sin of representativeness is insensitivity to the quality of evidence. Recall the rule of System 1: WYSIATI. In the Tom W example, what activates your associative machinery is a description of Tom, which may or may not be an accurate portrayal. The statement that Tom W "has little feel and little sympathy for people" was probably enough to convince you (and most other readers) that he is very unlikely to be a student of social science or social work. But you were explicitly told that the description should not be trusted!
You surely understand in principle that worthless information should not be treated differently from a complete lack of information, but WYSIATI makes it very difficult to apply that principle. Unless you decide immediately to reject evidence (for example, by determining that you received it from a liar), your System 1 will automatically process the information available as if it were true.
The mathematical details are not relevant in this book. There are two ideas to keep in mind about Bayesian reasoning and how we tend to mess it up. The first is that base rates matter, even in the presence of evidence about the case at hand. This is often not intuitively obvious. The second is that intuitive impressions of the diagnosticity of evidence are often exaggerated. The combination of WYSIATI and associative coherence tends to make up believe in the stories we spin for ourselves. The essential keys to disciplined Bayesian reasoning can be simply summarized:
• Anchor your judgment of the probability of an outcome on a plausible base rate.
• Question the diagnosticity of your evidence.
"This start-up looks as if it could not fail, but the base rate of success in the industry is extremely low. How do we know this case is different?"
15
Linda: Less is More
The twist comes in the judgments of likelihood, because there is a logical relation between the two scenarios. Think in terms of Venn diagrams. The set of feminist bank tellers is wholly included in the set of bank tellers, as every feminist bank teller is a bank teller. Therefore the probability that Linda is a feminist bank teller must be lower than the probability of her being a bank teller. When you specify a possible event in greater detail you can only lower its probability. The problem therefore sets up a conflict between the intuition of representativeness and the logic of probability.
Our initial experiment was between-subjects. Each participant saw a set of seven outcomes that included only one of the critical items ("bank teller" or "feminist bank teller"). Some ranked the outcomes by resemblance, others by likelihood. As in the case of Tom W, the average rankings by resemblance and by likelihood were identical; "feminist bank teller" ranked higher than "bank teller" in both.
I quickly called Amos in great excitement to tell him what we had found: we had pitted logic against representativeness, and representativeness had won!
As expected, probability judgments were higher for the richer and more detailed scenario, contrary to logic. This is a trap for forecasters and their clients: adding detail to scenarios makes them more persuasive, but less likely to come true.
To appreciate the role of plausibility, consider the following questions:
Which alternative is more probable?
Mark has hair.
Mark has blond hair.
and
Which alternative is more probable?
Jane is a teacher.
Jane is a teacher and walks to work.
The two questions have the same logical structure as the Linda problem, but they cause no fallacy, because the more detailed outcome is only more detailed - it is not more plausible, or more coherent, or a better story.
You can see that Set A contains all the dishes of Set B, and seven additional intact dishes, and it must be valued more. Indeed, the participants in Hsee's joint evaluation experiment were willing to pay a little more for Set A than for Set B: $32 versus $30.
The results reversed in single evaluation, where Set B was priced much higher than Set A: $33 versus $23. We know why this happened. Sets (including dinnerware sets!) are represented by norms and prototypes. You can sense immediately that the average value of the dishes is much lower for Set A than for Set B, because no one wants to pay for broken dishes. If the average dominates the evaluation, it is not surprising that Set B is valued more. Hsee called the resulting pattern less is more. By removing 16 items from Set A (7 of them intact), its value is improved.
Bjorn Borg was the dominant tennis player of the day when the study was conducted. These were the outcomes:
A. Bor will win the match.
B. Borg will lose the first set.
C. Borg will lose the first set but win the match.
D. Borg will win the first set but lose the match.
The critical items are B and C. B is the more inclusive event and its probability must be higher than that of an event it includes. Contrary to logic, but not to representativeness or plausibility, 72% assigned B a lower probability than C - another instance of less is more in a direct comparison.
We told participants about a regular six-sided die with four green faces and two red faces, which would be rolled 20 times. They were shown three sequences of greens (G) and reds (R), and were asked to choose one. They would (hypothetically) win $25 if their chosen sequence showed up. The sequences were:
1. RGRRR
2. GRGRRR
3. GRRRRR
Because the die has twice as many green as red faces, the first sequence is quite unrepresentative - like Linda being a bank teller. The second sequence, which contains six tosses, is a better fit to what we would expet from this die, because it includes two G's. However, this sequence was constructed by adding a G to the beginning of the first sequence, so it can only be less likely than the first...Almost tow-thirds of respondents preferred to bet on sequence 2 rather than on sequence 1.
If their next vacation had depended on it, and if they had been given indefinite time and told to follow logic and not to answer until they were sure of their answer, I believe that most of our subjects would have avoided the conjunction fallacy. However, their vacation did not depend on a correct answer; they spent very little time on it, and were content to answer as if they had only been "asked for their opinion." The laziness of System 2 is an important fact of life, and the observation that representativeness can block the application of an obvious logical rule is also of some interest.
People who see the dinnerware set that includes broken dishes put a very low price on it; their behavior reflects a rule of intuition. Others who see both sets at once apply the logical rule that more dishes can only add value.
"They added a cheap gift to the expensive product, and made the whole deal less attractive. Less is more in this case."
"In most situations, a direct comparison makes people more careful and more logical. But not always. Sometimes intuition beats logic even when the correct answer stares you in the face."
16
Causes Trump Statistics
The cab example illustrates two types of base reates. Statistical base rates are facts about a population to which a case belongs, but they are not relevant to the individual case. Causal base rates change your view of how the individual case came to be. The two types of base-rate information are treated differently:
• Statistical base rates are generally underweighted, and sometimes neglected altogether, when specific information about the case at hand is available.
• Causal base rates are treated as information about the individual case and are easily combined with other case-specific information.
The social norm against stereotyping, including the opposition to profiling, has been highly beneficial in creating a more civilized and more equal society. It is useful to remember, however, that neglecting valid stereotypes inevitably results in suboptimal judgments. Resistance to stereotyping is a laudable moral position, but the simplistic idea that the resistance is costless is wrong. The costs are worth paying to achieve a better society, but denying that the costs exist, while satisfying to the soul and politically correct, is not scientifically defensible. Reliance on the affect heuristic is common in politically charged arguments. The positions we favor have no cost and those we oppose have no benefits. We should be able to do better.
The experiment shows that individuals feel relieved of responsibility when they know that others have heard the same request for help.
Subjects' unwillingness to deduce the particular from the general was matched only by their willingness to infer the general from the particular.
The test of learning psychology is whether your understanding of situations you encounter has changed, not whether you have learned a new fact.
You are more likely to learn something by finding surprises in your own behavior than by hearing surprising facts about people in general.
17
Regression to the Mean
I was telling them about an important principle of skill training: rewards for improved performance work better than punishment of mistakes. This proposition is supported by much evidence from research on pigeons, rats, humans, and other animals.
This is why the pattern is called regression to the mean. The more extreme the original score, the more regression we expect, because an extremely good score suggests a very lucky day.
The point to remember is that the change from the first to the second jump does not need a causal explanation. It is mathematically inevitable consequence of the fact that luck played a role in the outcome of the first jump. Not a very satisfactory story - we would all prefer a causal account - but that is all there is.
The correlation coefficient between two measures, which varies between 0 and 1, is a measure of the relative weight of the factors they share.
• The correlation between the size of objects measured with precision in English or in metric units is 1. Any factor that influences one measure also influences the other; 100% of determinants are shared.
• The correlation between family income and the last four digits of their phone number is 0.
The general rule is straightforward but has surprising consequences: whenever the correlation between two scores is imperfect, there will be regression to the mean.
Highly intelligent women tend to marry men who are less intelligent than they are.
Some may think of highly iintelligent women wanting to avoid the competition of equally intelligent men, or being forced to compromise in their choice of spouse because intelligent men do not want to compete with intelligent women. More far-fetched explanations will come up at a good party. Now consider this statement:
The correlation between the intelligence scores of spouses is less than perfect.
The statement is obviously true and not interesting at all. Who would expect the correlation to be perfect? There is nothing to explain. But the statement you found interesting and the statement you found trivial are algebraically equivalent. If the correlation between the intelligence of spouses is less than perfect (and if men and women generally do not differ in intelligence), then it is a mathematical inevitability that highly intelligent women will be married to husbands who are on average less intelligent than they are (and vice versa, of course).
Causal explanations will be evoked when regression is detected, but they will be wrong because the truth is that regression to the mean has an explanation but does not have a cause.
The control group is expected to improve by regression alone, and the aim of the experiment is to determine whether the treated patients improve more than regression can explain.
18
Taming Intuitive Predictions
As was the case with Julie, the prediction of the future is not distinguished from an evaluation of current evidence - prediction matches evaluation. This is perhaps the best evidence we have for the role of substitution. People are asked for a prediction but they substitute an evaluation of the evidence, without noticing that the question they answer is not the one they were asked. This process is guaranteed to generate predictions that are systematically biased; they completely ignore regression to the mean.
Recall that the correlation between two measures - in the present case reading age and GPA - is equal to the proportion of shared factors among their determinants. What is your best guess about that proportion? My most optimistic guess is about 30%. Assuming this estimate, we have all we need to produce an unbiased prediction. Here are the directions for how to get there in four simple steps:
1. Start with an estimate of average GPA.
2. Determine the GPA that matches your impression of the evidence.
3. Estimate the correlation between reading precocity and GPA.
4. If the correlation is .30, move 30% of the distance from the average to the matching GPA.
Step 1 gets you the baseline, the GPA you would have predicted if you were told nothing about Julie beyond the fact that she is a graduating senior....Step 2 is your intuitive prediction, which matches your evaluation of the evidence. Step 3 moves your from the baseline toward your intuition, but the distance you are allowed to move depends on your estimate of the correlation. You end up, at step 4, with a prediction that is influenced by your intuition but is far more moderate.
Furthermore, you should know that correcting your intuitions may complicate your life. A characteristic of unbiased predictions is that they permit the prediction of rare of extreme events only when the information is very good. If you expect your predictions to be of modest validity, you will never guess an outcome that is either rare or far from the mean. If your predictions are unbiased, you will never have the satisfying experience of correctly calling an extreme case.
If you choose to delude yourself by accepting extreme predictions, however, you will do well to remain aware of your self-indulgence.
Part 3
Overconfidence
19
The Illusion of Understanding
In The Black Swan, Taleb introduced the notion of a narrative fallacy to describe how flawed stories of the past shape our view of the world and our expectations for the future.
Taleb suggests that we humans constantly fool ourselves by constructing flimsy accounts of the past and believing they are true.
The halo effect helps keep explanatory narratives simple and coherent by exaggerating the consistency of evaluations: good people do only good things and bad people are all bad. The statement "Hitler loved dogs and little children" is shocking no matter how many times you hear it, because any trace of kindness in someone so evil violates the expectations set up by the halo effect.
Paradoxically, it is easier to construct a coherent story when you know little, when there are fewer pieces to fit into the puzzle. Our comforting conviction that the world makes sense rests on a secure foundation: our almost unlimited ability to ignore our ignorance.
A general limitation of the human mind is its imperfect ability to reconstruct past states of knowledge, or beliefs that have changed. Once you adopt a new view of the world (or of any part of it), you immediately lose much of your ability to recall what you used to believe before your mind changed.
Consider a low-risk surgical intervention in which an unpredictable accident occured that caused the patient's death. The jury will be prone to believe, after the fact, that the operation was actually risky and that the doctor who ordered it should have known better. This outcome bias makes it almost impossible to evaluate a decision properly - in terms of the beliefs that were reasonable when the decision was made.
As malpractice litigation became more common, physicians changed their procedures in multiple ways: ordered more tests, referred more cases to specialists, applied conventional treatments even when they were unlikely to help. These actions protected the physicians more than they benefited the patients, creating the potential for conflicts of interest. Increased accountability is a mixed blessing.
The sense-making machinery of System 1 makes us see the world as more tidy, simple, predictable, and coherent than it really is.
The basic message of Built to Last and other similar books is that good managerial practices can be identified and that good practices will be rewarded by good results. Both messages are overstated. The comparison of firms that have been more or less successful is to a significant extent a comparison between firms that have been more or less lucky. Knowing the importance of luck, you should be particularly suspicious when highly consistent patterns emerge from the comparison of successful and lesss successful firms. In the presence of randomness, regular patterns can only be mirages.
A study of Fortune's "Most Admired Companies" finds that over a twenty-year period, the firms with the worst ratings went on to earn much higher stock returns than the most admired firms.
20
The Illusion of Validity
System 1 is designed to jump to conclusions from little evidence - and it is not designed to know the size of its jumps. Because of WYSIATI, only the evidence at hand counts. Because of confidence by coherence, the subjective confidence we have in our opinions reflects the coherence of the story that System 1 and System 2 have constructed. The amount of evidence and its quality do not count for much, because poor evidence can make a very good story.
It is wise to take admissions of uncertainty seriously, but declarations of high confidence mainly tell you that an individual has constructed a coherent story in his mind, not necessarily that the story is true.
To determine whether those ideas were well founded, Odean compared the returns of the stock the investor had sold and the stock he had bought in its place, over the course of one year after the transaction. The results were unequivocally bad. On average, the shares that individual traders sold did better than those they bought, by a very substantial margin: 3.2 percentage points per year, above and beyond the significant costs of executing the two trades.
It is important to remember that this is a statement about averages: some individuals did much better, others did much worse. However, it is clear that for the large majority of individual investors, taking a shower and doing nothing would have been a better policy than implementing the ideas that came to their minds.
The logic is simple: if individual differences in any one year are due entirely to luck, the ranking of investors and funds will vary erratically and the year-to-year correlation will be zero. Where there is skill, however, the rankings will be more stable.
Mutual funds are run by highly experienced and hardworking professionals who buy and sell stocks to achieve the best possible results for their clients. Nevertheless, the evidence from more than fifty years of research is conclusive: for a large majority of fund managers, the selection of stocks is more like rolling dice than like playing poker. Typically at least two out of every three mututal funds do not achieve their own benchmark in any given year.
More important, the year-to-year correlation between the outcomes of mutual funds is very small, barely higher than zero.
The illusion of skill is not only an individual aberration; it is deeply ingrained in the culture of the industry. Facts that challenge such basic assumptions - and thereby threaten people's livelihood and self-esteem - are simply not absorbed. The mind does not digest them. This is particularly true of statistical studies of performance, which provide base-rate information that people generally ignore when it clashes with their personal impressions from experience.
We know that people can maintain an unshakable faith in any proposition, however absurd, when they are sustained by a community of like-minded believers.
Everything makes sense in hindsight, a fact that financial pundits exploit every mevening as they offer convincing accounts of the day's events. And we cannot suppress the powerful intuition that what makes sense in hindsight today was predictable yesterday. The illusion that we understand the past fosters overconfidence in our ability to predict the future.
In other words, people who spend their time, and earn their living, studying a particular topic produce poorer predictions than dart-throwing monkeys who would have distributed their choices evenly over the options. Even in the region they knew best, experts were not significantly better than nonspecialists.
Those who know more forecast very slightly better than those who know less. But those with the most knowledge are often less reliable. The reason is that the person who acquires more knowledge develops an enhanced illusion of her skill and becomes unrealistically overconfident.
The main point of this chapter is not that people who attempt to predict the future make many errors; that goes without saying. The first lesson is that errors of prediction are inevitable because the world is unpredictable. The second is that high subjective confidence is not to be trusted as an indicator of accuracy (low confiedence could be more informative).
"The question is not whether these experts are well trained. It is whether their world is predictable."
21
Intuitions Vs. Formulas
In a typical study, trained counselors predicted the grades of freshmen at the end of the school year. The counselors interviewed each student for forty-five minutes. They also had access to high school grades, several aptitude tests, and a four-page personal statement. The statistical algorithm used only a fraction of this information: high school grades and one aptitude test. Nevertheless, the formula was more accurate than 11 of the 14 counselors.
Why are experts inferior to algorithms? One reason, which Meehl suspected, is that experts try to be clever, think outside the box, and consider complex combinations of feautres in making their predictions. Complexity may work in the oddd case, but more often than not it reduces validity. Simple combinations of feautres are better.
They feel that they can overrule the formula becuase they have additional information about the case, but they are wrong more often than not.
In contrast, Meehl and other proponents of algorithms have argued strongly that it is unethical to rely on intuitive judgments for important decisions if an algorithm is available that will make fewer mistakes. Their rational argument is compelling, but it runs against a stubborn psychological reality: for most people, the cause of a mistake matters. The story of a child dying because an algorithm made a mistake is more poignant than the story of the same tagedy occuring as a result of human error, and the difference in emotional intensity is readily translated into a moral preference.
The big surprise to me was that the intuitive judgment that the interviewers summoned up in the "close your eyes" exercise also did very well, indeed just as well as the sum of the six specific ratings. I learned from this finding a lesson that I have never forgotten: intuition adds value even in the justly derided selection interview, but only after a disciplined collection of objective information and disciplined scoring of separate traits.
A more general lesson that I learned from this episode was do not simply trust intuitive judgment - your own or that of others - but do not dismiss it, either.
Suppose that you need to hire a sales representative for your firm. If you are serious about hiring the best possible person for the job, this is what you should do. FIrst, select a few traits that are prerequisites for success in this position (technical proficiency, engaging personality, reliability, and so on). Don't overdo it - six dimensions is a good number. The traits you choose should be as independent as possible from each other, and you should feel that you can assess them reliably by asking a few factual questions. Next, make a list of those questions for each trait and think about how you will score it, say on a 1-5 scale. You should have an idea of what you will call "very weak" or "very strong."...To avoid halo effects, you must collect the information on one trait at a time, scoring each before you move on to the next one. Do not skip around. To evaluate each candidate, add up the six scores. Because you are in charge of the final decision, you should not do a "close your eyes." Firmly resolve that you will hire the candidate whose final score is the highest, even if there is another one whom ou like better - try to resist your wish to invent broken legs to change the ranking. A vast amount of research offers a promise: you are much more likely to find the best candidate if you use this procedure than if you do what people normally do in such situations, which is to go into the interview unprepared and to make choices by an overall intuitive judgment such as "I looked into his eyes and liked what I saw."
22
Expert Intuition: When Can We Trust It?
"The situation has provided a cue; this cue has given the expert access to information stored in memory, and the information provides the answer. Intuition is nothing more and nothing less than recognition."
This strong statement reduces the apparent magic of intuition to the everyday experience of memory. We marvel at the story of the firefighter because the firefighter knows the danger intuitively, "without knowing how he knows."
The moral of Simon's remark is that the mystery of knowing without knowing is not a distinctive feature of intuition; it is the norm of mental life.
The acquisitioin of expertise in complex tasks such as high-level chess, professional basketball, or firefighting is intricate and slow because expertise in a domain is not a single skill but rather a large collection of miniskills.
Klein and I eventually agreed on an important principle: the confidence that people have in their intuitions is not a reliable guide to their validity. In other words, do not trust anyone - including yourself - to tell you how much you should trust their judgment.
If subjective confidence is not to be trusted, how can we evaluate the probable validity of an intuitive judgment? When do judgments reflect true expertise? When do they display an illusion of validity? The answer comes from the two basic conditions for acquiring a skill:
• an environment that is sufficiently regular to be predictable
• an opportunity to learn these regularities through prolonged practice
When both these conditions are satisfied, intuitions are likely to be skilled.
Statistical algorithms greatly outdo humans in noisy environments for two reasons: they are more likely than human judges to detect weakly valid cues and much more likely to maintain a modest level of accuracy by using such cues consistently.
It is wrong to blame anyone for failing to forecast accurately in an unpredictable world. However, it seems fair to blame professionals for believing they can succeed in an impossible task. Claims for correct intuitions in an unpredictable situation are self-delusional at best, sometimes worse.
Remember this rule: intuition cannot be trusted in the absence of stable regularities in the environment.
Whether professionals have a chance to develop intuitive expertise depends essentially on the quality and speed of feedback, as well as on sufficient opportunity to practice.
If the environment is sufficiently regular and if the judge has had a chance to learn its regularities, the associative machinery will recognize situations and generate quick and accurate predictions and decisions. You can trust someone's intuitions if these conditions are met.
But this is what always happens when a project ends reasonably well: once you understand the main conclusion, it seems it was always obvious.
"She is very confident in her decision, but subjective confidence is a poor index of the accuracy of a judgment."
23
The Outside View
There are many ways for any plan to fail, and although most of them are too improbable to be anticipated, the likelihood that something will go wrong in a big project is high.
This is a common pattern: people who have information about an individual case rarely feel the need to know the statistics of the class to which the case belongs.
Amos and I coined the term planning fallacy to describe plans and forecasts that
• are unrealistically close to best-case scenarios
• could be improved by consulting the statistics of similar cases
In such cases, the greatest responsibility for avoiding the planning fallacy lies with the decision makers who approve the plan. If they do not recognize the need for an outside view, they commit a planning fallacy.
The forecasting method that Flyvbjerg applies is similar to the practices recommended for overcoming base-rate neglect:
1. Identify an appropriate reference class (kitchen renovations, large railway projects, etc.).
2. Obtain the statistics of the reference class (in terms of cost per mile of railway, or of the percentage by which expenditures exceeded budget). Use the statistics to generate a baseline prediction.
3. Use specific information about the case to adjust the baseline prediction, if there are particular reasons to expect the optimistic bias to be more or less pronounced in this project than in others of the same type.
"She is the victim of a planning fallacy. She's assuming a best-case scenario, but there are too many different ways for the plan to fail, and she cannot foresee them all."
"We are making and additional investment because we do not want to admit failure. This is an instance of the sunk-cost fallacy."
24
The Engine of Capitalism
Of course, the blessings of optimism are offered only to individuals who are only mildly biased and who are able to "accentuate the positive" without losing track of reality.
This reasoning leads to a hypothesis: the people who have the greatest influence on the lives of others are likely to be optimistic and overconfident, and to take more risks than they realize.
I have had several occasions to ask founders and participants in innovative start-ups a question: To what extent will the outcome of your effort depend on what you do in your firm? This is evidently an easy question; the answer comes quickly and in my small sample it has never been less than 80%. Even when they are notsure they will succeed, these bold bpeople think their fate is almost entirely in their own hands. They are surely wrong: the outcome of a start-up depends as much on the achievements of its competitors and on changes in the market as on its own efforts. However, WYSIATI plays its part, and entrepreneurs naturally focus on what they know best - their plans and actions and the most immediate threats and opportunities, such as the availability of funding. They know less about their competitors and therefore find it natural to imagine a future in which the competition plays little part.
An unbiased appreciation of uncertainty is a cornerstone of rationality - but it is not what people and organizations want. Extreme uncertainty is paralyzing under dangerous circumstances, and the admission that one is merely guessing is especially unacceptable when the stakes are high. Acting on pretended knowledge is often the preferred solution.
The effects of high optimism on decision making are, at best, a mixed blessing, but the contribution of optimism to good implementation is certainly positive. The main benefit of optimism is resilience in the face of setbacks.
However, overconfidence is a direct consequence of features of System 1 that can be tamed - but not vanquished. The main obstacle is that subjective confidence is determined by the coherence of the story one has constructed, not by the quality and amount of the information that supports it.
He labels his proposal the premortem. The procedure is simple: when the organization has almost come to an important decision but has not formally committed itself, Klein proposes gathering for a brief session a group of individuals who are knowledgeable about the decision. The premise of the session is a short speech: "Imagine that we are a year into the future. We implemented the plan as it now exists. The outcome was a disaster. Please take 5 to 10 minutes to write a brief history of that disaster."
The premortem has two main advantages: it overcomes the groupthink that affects many teams once a decision appears to have been made, and it unleashes the imagination of knowledgeable individuals in a much-needed direction.
The main virtue of the premortem is that it legitimizes doubts. Furthermore, it encourages even supporters of the decision to search for possible threats that they had not considered earlier.
Part 4
Choices
25
Bernoulli's Errors
The field had a theory, expected utility theory, which was the foundation of the rational-agent model and is to this day the most important theory in the social sciences. Expected utility theory was not intended as a psychological model; it was a logic of choice, based on elementary rules (axioms) of rationality. Consider this example:
If you prefer an apple to a banana,
then
you also prefer a 10% chance to win an apple to a 10% chance to win a banana.
Five years after we began our study of gambles, we finally completed an essay that we titled "Prospect Theory: An Analysis of Decision under Risk." Our theory was closely modeled on utility theory but departed from it in fundemental ways. Most important, our model was purely descriptive, and its goal was to document and explain systematic violations of the axioms of rationality in choices between gambles.
He argued that a gift of 10 ducats has the same utility to someone who already has 100 ducats as a gift of 20 ducats to someone whose current wealth is 200 ducats. Bernoulli was right, of course: we normally speak of changes of income in terms of percentages, as when we say "she got a 30% raise." The idea is that a 30% raise may evoke a fairly similar psychological response for the rich and for the poor, which an increase of $100 will not do.
For example, the expected value of:
80% chance to win $100 and 20% chance to win $10 is $82 (0.8 x 100 + 0.2 x 10).
Now ask yourself this question: Which would you prefer to receive as a gift, this gamble or $80 for sure? Almost everyone prefers the sure thing. If people valued uncertain prospects by their expected value, they would prefer the gamble, because $82 is more than $80. Bernoulli pointed out that people do not in fact evaluate gambles in this way.
In fact a risk-averse decision maker will choose a sure thing that is less than expected value, in effect paying a premium to avoid the uncertainty.
The same sound will be experienced as very loud or quite faint, depending on whether it was preceded by a whisper or by a roar. To predict the subjective experience of loudness, it is not enough to know its absolute energy; you also need to know the reference sound to which it is automatically compared.
I call it theory-induced blindness: once you have accepted a theory and used it as a tool in your thinking, it is extraordinarily difficult to notice its flaws. If you come upon an observation that does not seem to fit the model, you assume that there must be a perfectly good explanation that you are somehow missing.
26
Prospect Theory
You just like winning and dislike losing - and you almost certainly dislike losing more than you like winning.
...there are three cognitive features at the hear t of prospect theory. They play an essential role in the evaluation of financial outcomes and are common to many automatic processes of perception, judgment, and emotion. They should be seen as operating characteristics of System 1.
• Evaluation is relative to a neutral reference point, which is sometimes refferred to as an "adaptation level." You can easily set up a compelling demonstration of this principle. Place three bowls of water in front of you. Put ice water into the left-hand bowl and warm water into the right-hand bowl. The water in the middle bowl should be at room temperature. Immerse your hands in the cold and warm water for about a minute, then dip both in the middle bowl. You will experience the same temperature as heat in one hand and cold in the other. For financial outcomes, the usual reference point is the status quo, but it can also be the outcome that you expect, or perhaps the outcome to which you feel entitled, for example, the raise or bonus that your colleagues receive. Outcomes that are better than the reference points are gains. Below the reference point they are losses.
• A principle of diminishing sensitivity applies to both sensory dimensions and the evaluation of changes of wealth. Turning on a weak light has a large effect in a dark room. The same increment of light may be undetectable in a brightly illuminated room. Similarly, the subjective difference between $900 and $1,000 is much smaller than the difference between $100 and $200.
• The third principle is loss aversion. When directly compared or weighted against each other, losses loom larger than gains. This asymmetry between the power of positive and negative expectations or experiences has an evolutionary history. Organisms that treat threats as more urgent than opportunities have a better chance to survive and reproduce.
The slope of the function changes abruptly at the reference point: the response to losses is stronger than the response to corresponding gains. This is loss aversion.
For most people, the fear of losing $100 is more intense than the hope of gaining $150. We concluded from many such observations that "losses loom larger than gains" and that people are loss averse.
You can measure the extent of your aversion to losses by asking yourself a question: What is the smallest gain that I need to balance an equal chance to lose $100? For many people the answer is about $200, twice as much as the loss. The "loss aversion ratio" has been estimated in several experiments and is usually in the range of 1.5 to 2.5. This is an average, of course; some people are much more loss averse than others.
In this chapter I have made two claims, which some readers may view as contradictory:
• In mixed gambles, where both a gain and a loss are possible, loss aversion causes extremely risk-averse choices.
• In bad choices, where a sure loss is compared to a larger loss that is merely probable, diminishing sensitivity causes risk seeking.
There is no contradiction. In the mixed case, the possible loss looms twice as large as the possible gain, as you can see by comparing the slopes of the value function for losses and gains. In the bad case, the bending of the value curve (diminishing sensitivity) causes risk seeking. The pain of losing $900 is more than 90% of the pain of losing $1,000. These two insights are the essence of prospect theory.
"He weighs losses about twice as much as gains, which is normal."
27
The Endowment Effect
The representation of indefference curves implicitly assumes that your utility at any given moment is determined entirely by your present situation, that the past is irrelevant, and that your evaluation of a possible job does not depend on the terms of your current job. These assumptions are completely unrealistic in this case and in many others.
The standard theory represented in the figure assumes that preferences are stable over time. Positions A and B are equally attractive for both twins and they will need little or no incentive to switch. In sharp contrast, prospect theory asserts that both twins will definitely prefer to remain as they are. This preference for the status quo is a consequence of loss aversion.
Let us focus on Albert. He was initially in position 1 on the graph, and from that reference point he found these two alternatives equally attractive:
Go to A: a raise of $10,000
OR
Go to B: 12 extra days of vacation
Taking position A changes Albert's reference point, and when he considers switching to B, his choice has a new structure:
Stay at A: no gain and no loss
OR
Move to B: 12 extra days of vacation and a $10,000 salary cut
You just had the subjective experience of loss aversion.
This example highlights two aspects of choice that the standard model of indifference curves does not predict. First, tastes are not fixed; they vary with the reference point. Second, the disadvantages of a change loom larger than its advantages, inducing a bias that favors the status quo.
Conventional indifference maps and Bernoulli's representation of outcomes as states of wealth share a mistaken assumption: that your utility for a state of affairs depends only on that state and is not affected by your history. Correcting that mistake has been one of the achievements of behavioral economics.
There is no loss aversion on either side of routine commercial exchanges.
What distinguishes these market transactions from Professor R's reluctance to sell his wine, or the reluctance of Super Bowl ticket holders to sell even at a very high price? The distinctive feature is that both the shoes the merchant sells you and the money you spend from your budget for shoes are held "for exchange." They are intended to be traded for other goods. Other goods, such as wine and Super Bowl tickets, are held "for use," to be consumed or otherwise enjoyed.
The fundamental ideas of prospect theory are that reference points exist, and that losses loom larger than corresponding gains.
Veteran traders have apparently learned to ask the correct question, which is "How much do I want to have that mug, compared with other things I could have instead?" This is the question that Econs ask, and with this question there is no endowment effect, because the asymmetry between the pleasure of getting and the pain of giving up is irrelevant.
Being poor, in prospect theory, is living below one's reference point. There are goods that the poor need and cannot afford, so they are always "in the losses." Small amounts of money that they receive are therefore perceived as a reduced loss, not as a gain. The money helps one climb a little toward the reference point, but the poor always remain on the steep limb of the value function.
"These negotiations are going nowhere because both sides find it difficult to make concessions, even when they can get something in return. Losses loom larger than gains."
28
Bad events
The brains of humans and other animals contain a mechanism that is designed to give priority to bad news. By shaving a few hundredths of a second from the time needed to detect a predator, this circuit improves the animal's odds of living long enough to reproduce. The automatic operations of System 1 reflect this evolutionary history.
The sensitivity to threats extends to the processing of statements of opinions with which we strongly disagree.
Other scholars, in a paper titled "Bad Is Stronger Than Good," summarized the evidence as follows: "Bad emotions, bad parents, and bad feedback have more impact than good ones, and bad information is processed more thoroughly than good. The self is more motivated to avoid bad self-definitions than to pursue good ones. Bad impressions and bad stereotypes are quicker to form and more resistant to disconfirmation than good ones."
29
The Fourfold Pattern
The conclusion is straightforward: the decision weights that people assign to outcomes are not identical to the probabilities of these outcomes, contrary to the expectation principle. Improbable outcomes are over-weighted - this is the possibility effect. Outcomes that are almost certain are underweighted relative to actual certainty. The expectation principle, by which values are weighted by their probability, is poor psychology.
You can see that the decision weights are identical to the corresponding probabilities at the extremes: both equal to 0 when the outcome is impossible, and both equal to 100 when the outcome is a sure thing. However, decision weights depart sharply from probabilities near these points. At the low end, we find the possibility effect: unlikely events are considerably overweighted. For example, the decision weight that corresponds to a 2% chance is 8.1. If people conformed to the axioms of rational choice, the decision weight would be 2 - so the rare event is overweighted by a factor of 4. The certainty effect at the other end of the probability scale is even more striking. A 2% risk of not winning the prize reduces the utility of the gamble by 13%, from 100 to 87.1.
When you pay attention to a threat, you worry - and the decision weights reflect how much you worry. Because of the possibility effect, the worry is not proportional to the probability of the threat. Reducing or mitigating the risk is not adequate; to eliminate the worry the probability must be brought down to zero.
"They know the risk of a gas explosion is minuscule, but they want it mitigated. It's a possibility effect, and they want peace of mind."
30
Rare Events
My experience illustrates how terrorism works and why it is so effective: it induces an availability cascade. An extremely vivid image of death and damage, constantly reinforced by media attention and frequent conversations, becomes highly accessible, especially if it is associated with a specific situation such as the sight of a bus. The emotional arousal is associative, automatic, and uncontrolled, and it produces an impulse for protective action. System 2 may "know" that the probability is low, but this knowledge does not eliminate the self-generated discomfort and the wish to avoid it. System 1 cannot be turned off.
Our mind has a useful capability to focus spontaneously on whatever is odd, different, or unusual.
The idea of denominator neglect helps explain why different ways of communicating risks vary so much in their effects. You read that "a vaccine that protects children from a fatal disease carries a 0.001% risk of permanent disability." The risk appears small. Now consider another description of the same risk: "One of 10,000 vaccinated children will be permanently disabled." The second statement does something to your mind that the first does not: it calls up the image of an individual child who is permanently disabled by a vaccine; the 99,999 safely vaccinated children have faded into the background. As predicted by denominator neglect, low-probability events are much more heavily weighted when described in terms of relative frequencies (how many) than when stated in more abstract terms of "chances," "risk," or "probability" (how likely). As we have seen, System 1 is much better at dealing with individuals than categories.
The same statistics were described in two ways:
Patients similar to Mr. Jones are estimated to have a 10% probability of committing an act of violence against others during the first several months after discharge.
Of every 100 patients similar to Mr. Jones, 10 are estimated to commit an act of violence against others during the first several months after discharge.
The professionals who saw the frequency format were almost twice as likely to deny the discharge (41%, compared to 21% in the probability format). The more vivid description produces a higher decision weight for the same probability.
Obsessive concerns (the bus in Jerusalem), vivid images (the roses), concrete representations (1 of 1,000), and explicit reminders (as in choice from description) all contribute to overweighting. And when there is no overweighting, there will be neglect. When it comes to rare events, our mind is not designed to get things quite right. For the residents of a planet that may be exposed to events no one has yet experienced, this is not good news.
"Tsunamis are very rare even in Japan, but the image is so vivid and compelling that tourists are bound to overestimate their probability."
31
Risk Policies
As in many other choices that involve moderate or high probabilities, people tend to be risk averse in the domain of gains and risk seeking in the domain of losses.
The example also show that it is costly to be risk averse for gains and risk seeking for losses. These attitudes make you willing to pay a premium to obtain a sure gain rather than face a gamble, and also willing to pay a premium (in expected value) to avoid a sure loss.
There were two ways of construing decisions (i) and (ii).
• narrow framing: a sequence of two simple decisions, considered separately
• broad framing: a single comprehensive decision, with four options
Broad framing was obviously superior in this case. Indeed, it will be superior (or at least not inferior) in every case in which several decisions are to be contemplated together. Imagine a longer list of 5 simple (binary) decisions to be considered simultaneously. The broad (comprehensive) frame consists of a single choice with 32 options. Narrow framing will yield a sequence of 5 simple choices. The sequence of 5 choices will be one of the 32 options of the broad frame. Will it be the best? Perhaps, but not very likely. A rational agent will of course engage in broad framing, but Humans are by nature narrow framers.
However, the aggregation of favorable gambles rapidly reduces the probability of losing, and the impact of loss aversion on his preferences diminishes accordingly.
32
Keeping Score
The decision to invest additional resources in a losing account, when better investments are available, is known as the sunk-cost fallacy, a costly mistake that is observed in decisions large and small. Driving into the blizzard because one paid for tickets is a sunk-cost error.
The sunk-cost fallacy keeps people for too long in poor jobs, unhappy marriages, and unpromising research projects. I have often observed young scientists struggling to salvage a doomed project when they would be better advised to drop it and start a new one.
To appreciate the link of regret to normality, consider the following scenario:
Mr. Brown almost never picks up hitchhikers. Yesterday he gave a man a ride and was robbed.
Mr. Smith frequently picks up hitchhikers. Yesterday he gave a man a ride and was robbed.
Who of the two will experience greater regret over the episode?
The results are not surprising: 88% of respondents said Mr. Brown, 12% said Mr. Smith.
Regret is not the same as blame. Other participants were asked this question about the same incident:
Who will be criticized most severely by others?
The results: Mr. Brown 23%, Mr. Smith 77%.
Regret and blame are both evoked by a comparison to a norm, but the relevant norms are different. The emotions experienced by Mr. Brown and Mr. Smith are dominated by what they usually do about hitchhikers.
This short expample illustrates a broad story: people expect to have stronger emotional reactions (including regret) to an outcome that is produced by action than to the same outcome when it is produced by inaction.
In a compelling demonstration of the power of default options, participants played a computer simulation of blackjack. Some players were asked "Do you wish to hit?" while others were asked "Do you wish to stand?" Regardless of the question, saying yes was associated with much more regret than saying no if the outcome was bad!
My personal hindsight-avoiding policy is to be either very thorough or completely casual when making a decision with long-term consequences. Hindsight is worse when you think a little, just enough to tell yourself later, "I almost made a better choice."
"We are hanging on to that stock just to avoid closing our mental account at a loss. It's the disposition effect."
33
Reversals
We normally experience life in the between-subjects mode, in which contrasting alternatives that might change your mind are absent, and of course WYSIATI.
Judgments and preferences are coherent within categories but potentially incoherent when the objects that are evaluated belong to different categories. For an example, answer the following three questions:
Which do you like more, apples or peaches?
Which do you like more, steak or stew?
Which do you like more, apples or steak?
The first and the second questions refer to items that belong to the same category, and you know immediately which you like more. Furthermore, you would have recovered the same ranking from single evaluation ("How much do you like apples?" and "How much do you like peaches?") because apples and peaches both evoke fruit. There will be no preference reversal because different fruits are compared to the same norm and implicitly compared to each other in single as well as in joint evaluation. In contrast to the within-category questions, there is no stable answer for the comparison of apples and steak. Unlike apples and peaches, apples and steak are not natural substitutes and they do not fill the same need. You sometimes want steak and sometimes an apple, but you rarely say that either one will do just as well as the other.
In experiments, the dolphins attracted somewhat larger contributions in single evaluation than did the farmworkers...Next, consider the two causes in joint evaluation. Which of the two, dolphins or farmworkers, deserves a larger dollar contribution? Joint evaluation highlights a feature that was not noticeable in single evaluation but is recognized as decisive when detected: farmers are human, dolphins are not. You knew that, of course, but it was not relevant to the judgment that you made in single evaluation. The fact that dolphins are not human did not arise because all the issues that were activated in your memory shared that feature. The fact that farmworkers are human did not come to mind because all public-health issues involve humans. The narrow framing of single evaluation allowed dolphins to have a higher intensity score, leading to a high rate of contributions by intensity matching. Joint evaluation changes the representation of the issues: the "human vs. animal" feature becomes salient only when the two are seen together. In joint evaluation people show a solid preference for the farmworkers and a willingness to contribute substantially more to their welfare than to the protection of a likable non-human species.
As we have seen, rationality is generally served by broader and more comprehensive frames, and joint evaluation is obviously broader than single evaluation. Of course, you should be wary of joint evaluation when someone who controls what you see has vested interest in what you choose. Sales-people quickly learn that manipulation of the context in which customers see a good can profoundly influence preferences. Except for such cases of deliberate manipulation, there is a presumption that the comparative judgment, which necessarily involves System 2, is more likely to be stable than single evaluations, which often reflect the intensity of emotional responses of System 1. We would expect that any institution that wishes to elicit thoughtful judgments would seek to provide the judges with a broad context for the assessments of individual cases.
"When you see cases in isolation, you are likely to be guided by an emotional reaction of System 1."
34
Frames and Reality
We should not be surprised: losses evokes stronger negative feelings than costs. Choices are not reality-bound because System 1 is not reality-bound.
Physician participants were given statistics about the outcomes of two treatments for lung cancer: surgery and radiation. The five-year survival rates clearly favor surgery, but in the short term surgery is riskier than radiation. Half the participants read statistics about survival rates, the others received the same information in terms of mortality rates. The two descriptions of the short-term outcomes of surgery were:
The one-month survival rate is 90%.
There is 10% mortality in the first month.
You already know the results: surgery was much more popular in the former frame (84% of physicians chose it) than in the latter (where 50% favored radiation). The logical equivalence of the two descriptions is transparent, and a reality-bound decision maker would make the same choice regardless of which version she saw. But System 1, as we have gotten to know it, is rarely indifferent to emotional words: mortality is bad, survival is good, and 90% survival sounds encouraging whereas 10% mortality is frightening.
Reframing is effortful and System 2 is normally lazy. Unless there is an obvious reason to do otherwise, most of us passively accept decision problems as they are framed and therefore rarely have an opportunity to discover the extent to which our preferences are frame-bound rather than reality-bound.
Imagine that the United States is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. Assume that the exact scientific estimates of the consequences of the programs are as follows:
If program A is adopted, 200 people will be saved.
If program B is adopted, there is a one-third probability that 600 people will be saved and a two-thirds probability that no people will be saved.
A substantial majority of respondents choose program A: they prefer the certain option over the gamble...The outcomes of the programs are framed differently in a second version:
If program A' is adopted, 400 people will die.
If program B' is adopted, there is a one-third probability that nobody will die and a two-thirds probability that 600 people will die.
Look closely and compare the two versions: the consequences of programs A and A' are identical; so are the consequences of programs B and B'. In the second frame, however, a large majority of people choose the gamble.
Decision makers tend to prefer the sure thing over the gamble (they are risk averse) when the outcomes are good. They tend to reject the sure thing and accept the gamble (they are risk seeking) when both outcomes are negative.
In this context, as well, the framing experiment reveals that risk-averse and risk-seeking preferences are not reality-bound. Preferences between the same objective outcomes reverse with different formulations.
We can recognize System 1 at work. It delivers an immediate response to any question about rich and poor: when in doubt, favor the poor.
The evidence comes from a comparison of the rate of organ donation in European countries, which reveals startling differences between neighboring and culturally similar countries. An article published in 2003 noted that the rate of organ donation was close to 100% in Austria but only 12% in Germany, 86% in Sweden but only 4% in Denmark.
These enormous differences are a framing effect, which is caused by the format of the critical question. The high-donation countries have an opt-out form, where individuals who wish not to donate must check an appropriate box. Unless they take this simple action, they are considered willing donors. The low-contribution countries have an opt-in form: you must check a box to become a donor. That is all. The best single predictor whether or not people will donate their organs is the designation of the default option that will be adopted without having to check a box.
Skeptics about rationality are not surprised. They are trained to be sensitive to the power of inconseequential factors as determinants of preference - my hope is that readers of this book have acquired this sensitivity.
"They ask you to check the box to opt out of their mailing list. Their list would shrink if they asked you to check a box to opt in!"
Part 5
Two Selves
35
Two Selves
Jeremy Bentham opened his Introduction to the Principles of Morals and Legislation with the famous sentence "Nature has placed mankind under the governance of two sovereign masters, pain and pleasure. It is for them alone to point out what we ought to do, as well as to determine what we shall do."
We now have an embarrassment of riches: two measures of experienced utility - the hedonimeter total and the retrospective assessment - that are systematically different. The hedonimeter totals are computed by an observer from an individual's report of the experience of moments. We call these judgments duration-weighted, because the computation of the "area under the curve" assigns equal weights to all moments: two minutes of pain at level 9 is twice as bad as one minute at the same level of pain. However, the findings of this experiment and others show that the retrospective assessments are insensitive to duration and weight two singular moments, the peak and the end, much more than others. So which should matter? What should the physician do? The choice has implications for medical practice. We noted that:
• If the objective is to reduce patients' memory of pain, lowering the peak intensity of pain could be more important than minimizing the duration of the procedure. By the same reasoning, gradual relief may be preferable to abrupt relief if patients retain a better memory when the pain at the end of the procedure is relatively mild.
• If the objective is to reduce the amount of pain actually experienced, conducting the procedure switftly may be appropriate even if doing so increases the peak pain intensity and leaves patients with an awful memory.
A comment I heard from a member of the audience after a lecture illustrates the fifficulty of distinguishing memories from experiences. He told of listening raptly to a long symphony on a disc that was scratched near the end, producing a shocking sound, and he reported that the bad ending "ruined the whole experience." But the experience was not actually ruined, only the memory of it. The experiencing self had had an experience that was almost entirely good, and the bad end could not undo it, because it had already happened. My questioner had assigned the entire episode a failing grade because it had ended very badly, but that grade effectively ignored 40 minutes of musical bliss. Does the actual experience count for nothing?
COnfusing experience with memory of it is a compelling cognitive illusion - and it is the substitution that makes us believe a past experience can be ruined. The experiencing self does not have a voice. The remembering self is sometimes wrong, but it is the one that keeps score and governs what we learn from living, and it is the one that makes decisions.
Their decision was governed by a simple rule of intuitive choice: pick the option you like the most, or dislike the least. Rules of memory determined how much they disliked the two options, which in turn determined their choice.
In the cold-hand experiment, the error reflects two principles of memory: duration neglect and the peak-end rule. The mechanisms are different but the outcome is the same: a decision that is not correctly attuned to the experience.
The cold-hand study showed that we cannot fully trust our preferences to reflect our interests, even if they are based on personal experience, and even if the memory of that experience was laid down within the last quarter of an hour!
We want pain to be brief and pleasure to last. But our memory, a function of System 1, has evolved to represent the most intense moment of an episode of pain or pleasure (the peak) and the feelings when the episode was at its end. A memory that neglects duration will not serve our preference for long pleaure and short pains.
"This is a bad case of duration neglect. You are giving the good and the bad part of your experience equal weight, although the good part lasted ten times as long as the other."
36
Life As a Story
A story is about significant events and memorable moments, not about time passing. Duration neglect is normal in a story, and the ending often defines its character. The same core features appear in the rules of narratives and in the memories of colonoscopies, vacations, and films. This is how the remembering self works: it composes stories and keeps them for future reference.
Caring for people often takes the form of concern for the quality of their stories, not for their feelings.
As expected from this idea, Diener and his students also found a less-is-more effect, a strong indication that an average (prototype) has been substituted for a sum. Adding 5 "slightly happy" years to a very happy life caused a substantial drop in evaluations of the total happiness of that life.
In intuitive evaluation of entire lives as well as brief episodes, peaks and ends matter but duration does not.
The pains of labor and the benefits of vacations always come up as objections to the idea of duration neglect: we all share the intuition that it is much worse for labor to last 24 than 6 hours, and that 6 days at a good resort is better than 3. Duration appears to matter in these situations, but this is only because the quality of the end changes with the length of the episode. The mother is more depleted and helpless after 24 hours than after 6, and the vacationer is more refreshed and rested after 6 days than after 3. What truly matters when we intuitively assess such episodes is the progressive deterioration or improvement of the ongoing experience, and how the person feels at the end.
As in the cold-hand experiment, right or wrong, people choose by memory when they decide whether or not to repeat an experience.
A thought experiment about your next vacation will allow you to observe your attitude to your experiencing self.
At the end of the vacation, all pictures and videos will be destroyed.
Furthermore, you will swallow a potion that will wipe out all your memories of the vacation.
How would this prospect affect your vacation plans? How much would you be willing to pay for it, relative to a normally memorable vacation?
For another thought experiment, imagine you face a painful operation during which you will remain conscious. You are told you will scream in pain and beg the surgeon to stop. However, you are promised an amnesia-inducing drug that will completely wipe out any memory of the episode. How do you feel about such a prospect? Here again, my informal observation is that most people are remarkably indifferent to the pains of their experiencing self.
Odd as it may seem, I am my remembering self, and the experiencing self, who does my living, is like a stranger to me.
"He is desperately trying to protect the narrative of a life of integrity, which is endangered by the latest episode."
37
Experienced Well-Being
A U-index can also be computed for activities. For example, we can measure the proportion of time that people spend in a negative emotional state while commuting, working, or interacting with their parents, spouses, or children. For 1,000 American women in a Midwestern city, the U-index was 29% for the morning commute, 27% for work, 24% for child care, 18% for housework, 12% for socializing, 12% for TV watching, and 5% for sex. The U-index was higher by about 6% on weekdays than it was on weekends, mostly because on weekends people spend less time in activities they dislike and do not suffer the tension and stress associated with work. The biggest surprise was the emotional experience of the time spent with one's children, which for American women was slightly less enjoyable than doing housework.
An individual's mood at any moment depends on her temperament and overall happiness, but emotional well-being aslo fluctuates considerably over the day and the week.
Attention is key. Our emotional state is largely determined by what we attend to, and we are normally focused on our current activity and immediate environment.
It is only a slight exaggeration to say that happiness is the experience of spending time with people you love and who love you.
An analysis of more than 450,000 responses to the Gallup-Healthways Well-Bing Index, a daily survey of 1,000 Americans, provides a surprisingly definite answer to the most frequently asked question in well-bing research: Can money buy happiness? The conclusion is that being poor makes one miserable, and that being rich may enhance one's life satisfaction, but does not (on average) improve experienced well-being.
Severe poverty amplifies the experienced effects of other misfortunes in life...A headache increases the proportion reporting sadness and worry from 19% to 38% for individuals in the top two-thirds of the income distribution. The corresponding numbers for the poorest tenth are 38% and 70% - a higher baseline level and a much larger increase. Significant differences between the very poor and others are also found for the effects of divorce and loneliness.
The satiation level beyond which experienced well-being no longer increases was a household income of about $75,000 in high-cost areas (it could be less in areas where the cost of living is lower). The average increase of experienced well-being associated with incomes beyond that level was precisely zero. This is surprising because higher income undoubtedly permits the purchase of many pleasures, including vacations in interesting places and opera tickets, as well as an improved living environment.
"The easiest way to increase happiness is to control your use of time. Can you find more time to do the things you enjoy doing?"
38
Thinking About Life
The graph shows the level of satisfaction reported by people around the time they got married. The graph reliably evokes nervous laughter from audiences, and the nervousness is easy to understand: after all, people who decide to get married do so either because they expect it will make them happier or because they hope that making a tie permanent will maintain the present state of bliss.
Even people who are happy to be reminded of their marriage when asked a question about their life are not necessarily happier the rest of the time. Unless they think happy thoughts about their marriage during much of their day, it will not directly influence their happiness. Even newlyweds who are lucky enough to enjoy a state of happy preoccupation with their love will eventually return to earth, and their experienced well-being will again depend, as it does for the rest of us, on the environment and activities of the present moment.
Experienced well-being is on average unaffected by marriage, not because marriage makes no difference to happiness but beause it changes some aspect of life for the better and others for the worse.
One reason for the low correlations between individuals' circumstances and their satisfaction with life is that both experienced happiness and life satisfaction are largely determined by the genetics of temperament. A disposition for well-being is as heritable as height or intelligence, as demonstrated by studies of twins separated at birth. People who appear equally fortunate vary greatly in how happy they are.
The effect of income on life satisfaction was larger for those who had listed being well-off financially as an essential goal: .57 point on a 5-point scale. The corresponding differnece for those who had indicated that money was not important only .12. The people who wanted money and got it were significantly more satisfied than average; those who wanted money and didn't get it were significantly more dissatisfied.
In part because of these findings I have changed my mind about the definition of well-being. The goals that people set for themselves are so imprtant to what they do and how they feel about it that an exclusive focus on experienced well-being is not tenable. We cannot hold a concept of well-being that ignores what people want. On the other hand, it is also true that a concept of well-being that ignores how people feel as they live and focuses only on how they feel when they think about their life is also untenable. We must accept the complexities of a hybrid view, in which the well-being of both selves is considered.
Any aspect of life to which attention is directed will loom large in a global evaluation. This is the essence of the focusing illusion, which can be described in a single sentence:
Nothing in life is as important as you think it is when you are thinking about it.
Adaptation to a new situation, whether good or bad, consists in large part of thinking less and less about it. In that sense, most long-term circumstances of life, including paraplegia and marriage, are part-time states that one inhabits only when one attends to them.
Compare two commitments that will change some aspects of your life: buying a comfortable new car and joining a group that meets weekly, perhaps a poker or book club. Both experiences will be novel and exciting at the start. The crucial difference is taht you will eventually pay little attention to the car as you drive it, but you will always attend to the social interaction to which you committed yourself. By WYSIATI, you are likely to exaggerate the long-term benefits of the car, but you are not likely to make the same mistake for a social gathering or for inherently attention-demanding activities such as playing tennis or learning to play the cello. The focusing illusion creates a bias in favor of goods and experiences that are initially exciting, even if they will eventually lose their appeal. Time is neglected, causing experiences that will retain their attention value in the long term to be appreciated less than they deserve to be.
The mind is good with sotries, but it does not appear to be well designed for the processing of time.
"His car broke down on the way to work this morning and he's in a foul mood. This is nota good day to ask him about his job satisfaction!"
Conclusions
The neglect of duration combined with the peak-end rule causes a bias that favors a short period of intense joy over a long period of moderate happiness. The mirror image of the same bias makes us fear a short period of intense but tolerable suffering more than we fear a much longer period of moderate pain.
A theory of well-being that ignores what people want cannot be sustained. On the other hand, a theory that ignores what actually happens in people's lives and focuses exclusively on what they think about their life is not tenable either. The remembering self and the experiencing self must both be considered, because their interests do not always coincide. Philosophers could struggle with these questions for a long time.
The only test of rationality is not whether a person's beliefs and preferences are reasonable, but whether they are internally consistent. A rational person an believe in ghosts so long as all her other beliefs are consistent with the existence of ghosts. A rational person can prefer being hated over being loved, so long as his preferences are consistent. Rationality is logical coherence - reasonable or not.
It also presented a set of solutions to the dilemma of how to help people make good decisions without curtailing their freedom. Thaler and Sunstein advocate a position of libertarian paternalism, in which the state and other institutions are allowed to nudge people to make decisions that serve their own long-term interests. The designation of joing a pension plan as the default option is an example of a nudge. It is difficult to argue that anyone's freedom is diminished by being automatically enrolled in the plan, when they merely have to check a box to opt out. As we saw earlier, the framing of the individual's decision - Thaler and Sunstein call it choice architecture - has a huge effect on the outcome.
As i know from experience, System 1 is not readily educable. Except for some effects that i attribute mostly to age, my intuitive thinking is just as prone to overconfidence, extreme predictions, and the planning fallacy as it was before I made a study of these issues. I have improved only in my ability to recognize situations in which errors are likely: "This number will be an anchor...," "The decision could change if the problem is reframes..." And I have made much more progress in recognizing the errors of others than my own.