Thinking, Fast and Slow

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. In the economy of action, effort is a cost, and the acquisition of skill is driven by the balance of benefits and costs. Laziness is built deep into our nature.

Any task that requires you to keep several ideas in mind at the same time has the same hurried character. Unless you have the good fortune of a capacious working memory, you may be forced to work uncomfortably hard.

Many people are overconfident, prone to place too much faith in their intuitions. They apparently find cognitive effort at least mildly unpleasant and avoid it as much as possible.

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.

Her findings suggest that living in a culture that surrounds us with reminders of money may shape our behavior and our attitudes in ways that we do not know about and of which we may not be proud. Some cultures provide frequent reminders of respect, others constantly remind their members of God, and some societies prime obedience by large images of the Dear Leader.

Priming phenomena arise in System 1, and you have no conscious access to them.

“His System 1 constructed a story, and his System 2 believed it. It happens to all of us.” “I made myself smile and I’m actually feeling better!”

A reliable way to make people believe in falsehoods is frequent repetition, because familiarity is not easily distinguished from truth.

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. Put your ideas in verse if you can; they will be more likely to be taken as truth.

If you quote a source, choose one with a name that is easy to pronounce.

Cognitive strain, whatever its source, mobilizes System 2, which is more likely to reject the intuitive answer suggested by System 1.

Mood evidently affects the operation of System 1: when we are uncomfortable and unhappy, we lose touch with our intuition.

“We must be inclined to believe it because it has been repeated so often, but let’s think it through again.”

“I’m in a very good mood today, and my System 2 is weaker than usual. I should be extra careful.”

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. Indeed, there is evidence that people are more likely to be influenced by empty persuasive messages, such as commercials, when they are tired and depleted.

The sequence in which we observe characteristics of a person is often determined by chance. Sequence matters, however, because the halo effect increases the weight of first impressions, sometimes to the point that subsequent information is mostly wasted.

“She knows nothing about this person’s management skills. All she is going by is the halo effect from a good presentation.”

In both cases, satisfaction in the particular domain dominates happiness reports. Any emotionally significant question that alters a person’s mood will have the same effect. WYSIATI. The present state of mind looms very large when people evaluate their happiness

Self-criticism is one of the functions of System 2. 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. An active, coherence-seeking System 1 suggests solutions to an undemanding System 2.

Characteristics of System 1 generates impressions, feelings, and inclinations; when endorsed by System 2 these become beliefs, attitudes, and intentions operates automatically and quickly, with little or no effort, and no sense of voluntary control can be programmed by System 2 to mobilize attention when a particular pattern is detected (search) executes skilled responses and generates skilled intuitions, after adequate training creates a coherent pattern of activated ideas in associative memory links a sense of cognitive ease to illusions of truth, pleasant feelings, and reduced vigilance distinguishes the surprising from the normal infers and invents causes and intentions neglects ambiguity and suppresses doubt is biased to believe and confirm exaggerates emotional consistency (halo effect) focuses on existing evidence and ignores absent evidence (WYSIATI) generates a limited set of basic assessments represents sets by norms and prototypes, does not integrate matches intensities across scales (e.g., size to loudness) computes more than intended (mental shotgun) sometimes substitutes an easier question for a difficult one (heuristics) is more sensitive to changes than to states (prospect theory)* overweights low probabilities* shows diminishing sensitivity to quantity (psychophysics)* responds more strongly to losses than to gains (loss aversion)* frames decision problems narrowly, in isolation from one another

If you follow your intuition, you will more often than not err by misclassifying a random event as systematic. We are far too willing to reject the belief that much of what we see in life is random.

The exaggerated faith in small samples is only one example of a more general illusion—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 conclusions is a safer sport in the world of our imagination than it is in reality.

Are less confident in a choice when they are asked to produce more arguments to support it

The conclusion is that the ease with which instances come to mind is a System 1 heuristic, which is replaced by a focus on content when System 2 is more engaged. Multiple lines of evidence converge on the conclusion 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.

Merely reminding people of a time when they had power increases their apparent trust in their own intuition.

“The CEO has had several successes in a row, so failure doesn’t come easily to her mind. The availability bias is making her overconfident.”

The importance of an idea is often judged by the fluency (and emotional charge) with which that idea comes to mind.

A question about probability or likelihood activates a mental shotgun, evoking answers to easier questions. One of the easy answers is an automatic assessment of representativeness—routine in understanding language.

Judging probability by representativeness has important virtues: the intuitive impressions that it produces are often—indeed, usually—more accurate than chance guesses would be.

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 out their cheeks (an emotionally 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.

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 WY SIATI and associative coherence tends to make us 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?” “They keep making the same mistake: predicting rare events from weak evidence. When the evidence is weak, one should stick with the base rates.”

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.

“They added a cheap gift to the expensive product, and made the whole deal less attractive. Less is more in this case.”

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.

You are more likely to learn something by finding surprises in your own behavior than by hearing surprising facts about people in general.

Our mind is strongly biased toward causal explanations and does not deal well with “mere statistics.” When our attention is called to an event, associative memory will look for its cause—more precisely, activation will automatically spread to any cause that is already stored in memory. 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.

In order to conclude that an energy drink—or any other treatment—is effective, you must compare a group of patients who receive this treatment to a “control group” that receives no treatment (or, better, receives a placebo). 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.

Regression effects are a common source of trouble in research, and experienced scientists develop a healthy fear of the trap of unwarranted causal inference.

“Perhaps his second interview was less impressive than the first because he was afraid of disappointing us, but more likely it was his first that was unusually good.”

Intuitive predictions need to be corrected because they are not regressive and therefore are biased.

“Our intuitive prediction is very favorable, but it is probably too high. Let’s take into account the strength of our evidence and regress the prediction toward the mean.”

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.

Hindsight bias has pernicious effects on the evaluations of decision makers. It leads observers to assess the quality of a decision not by whether the process was sound but by whether its outcome was good or bad.

“He’s learning too much from this success story, which is too tidy. He has fallen for a narrative fallacy.”

“Let’s not fall for the outcome bias. This was a stupid decision even though it worked out well.”

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 confidence could be more informative).

Short-term trends can be forecast, and behavior and achievements can be predicted with fair accuracy from previous behaviors and achievements.

Behavior both on the test and in the real world is determined by many factors that are specific to the particular situation.

The line that separates the possibly predictable future from the unpredictable distant future is yet to be drawn.

“She has a coherent story that explains all she knows, and the coherence makes her feel good.”

“She is a hedgehog. She has a theory that explains everything, and it gives her the illusion that she understands the world.”

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 features in making their predictions. Complexity may work in the odd case, but more often than not it reduces validity.

Another reason for the inferiority of expert judgment is that humans are incorrigibly inconsistent in making summary judgments of complex information. When asked to evaluate the same information twice, they frequently give different answers.

The widespread inconsistency is probably due to the extreme context dependency of System 1. We know from studies of priming that unnoticed stimuli in our environment have a substantial influence on our thoughts and actions. These influences fluctuate from moment to moment. The brief pleasure of a cool breeze on a hot day may make you slightly more positive and optimistic about whatever you are evaluating at the time.

“Whenever we can replace human judgment by a formula, we should at least consider it.”

“He thinks his judgments are complex and subtle, but a simple combination of scores could probably do better.”

“Let’s decide in advance what weight to give to the data we have on the candidates’ past performance. Otherwise we will give too much weight to our impression from the interviews.”

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.

In a less regular, or low-validity, environment, the heuristics of judgment are invoked. System 1 is often able to produce quick answers to difficult questions by substitution, creating coherence where there is none. The question that is answered is not the one that was intended, but the answer is produced quickly and may be sufficiently plausible to pass the lax and lenient review of System 2.

“Does he really believe that the environment of start-ups is sufficiently regular to justify an intuition that goes against the base rates?”

“Did he really have an opportunity to learn? How quick and how clear was the feedback he received on his judgments?”

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

“He’s taking an inside view. He should forget about his own case and look for what happened in other cases.”

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.

Organizations may be better able to tame optimism and individuals than individuals are. The best idea for doing so was contributed by Gary Klein, my “adversarial collaborator” who generally defends intuitive decision making against claims of bias and is typically hostile to algorithms. He labels his proposal the premortem.

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.

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.

“He was very happy with a $20,000 bonus three years ago, but his salary has gone up by 20% since, so he will need a higher bonus to get the same utility.” “Both candidates are willing to accept the salary we’re offering, but they won’t be equally satisfied because their reference points are different. She currently has a much higher salary.”

There are three cognitive features at the heart 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 referred to as an “adaptation level.”

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.

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.

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.

“He suffers from extreme loss aversion, which makes him turn down very favorable opportunities.”

“He weighs losses about twice as much as gains, which is normal.”

No endowment effect is expected when owners view their goods as carriers of value for future exchanges, a widespread attitude in routine commerce and in financial markets.

“He just hates the idea of selling his house for less money than he paid for it. Loss aversion is at work.”

“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.”

Gottman estimated that a stable relationship requires that good interactions outnumber bad interactions by at least 5 to 1.

“This reform will not pass. Those who stand to lose will fight harder than those who stand to gain.”

“They would find it easier to renegotiate the agreement if they realized the pie was actually expanding. They’re not allocating losses; they are allocating gains.”

“My clients don’t resent the price hike because they know my costs have gone up, too. They accept my right to stay profitable.”

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 overweighted—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.

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.

Suppose that you currently use an insect spray that costs you $10 per bottle and it results in 15 inhalation poisonings and 15 child poisonings for every 10,000 bottles of insect spray that are used. You learn of a more expensive insecticide that reduces each of the risks to 5 for every 10,000 bottles. How much would you be willing to pay for it? The parents were willing to pay an additional $2.38, on average, to reduce the risks by two-thirds from 15 per 10,000 bottles to 5. They were willing to pay $8.09, more than three times as much, to eliminate it completely.

The fourfold pattern. The name has stuck. The scenarios are illustrated below. Figure 13 The top row in each cell shows an illustrative prospect. The second row characterizes the focal emotion that the prospect evokes. The third row indicates how most people behave when offered a choice between a gamble and a sure gain (or loss) that corresponds to its expected value (for example, between “95% chance to win $10,000” and “$9,500 with certainty”). Choices are said to be risk averse if the sure thing is preferred, risk seeking if the gamble is preferred. The fourth row describes the expected attitudes of a defendant and a plaintiff as they discuss a settlement of a civil suit. The

“We never let our vacations hang on a last-minute deal. We’re willing to pay a lot for certainty.”

“They will not cut their losses so long as there is a chance of breaking even. This is risk-seeking in the losses.”

A rich and vivid representation of the outcome, whether or not it is emotional, reduces the role of probability in the evaluation of an uncertain prospect. This hypothesis suggests a prediction, in which I have reasonably high confidence: adding irrelevant but vivid details to a monetary outcome also disrupts calculation.

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 100,000 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 more vivid description produces a higher decision weight for the same probability. The power of format creates opportunities for manipulation, which people with an axe to grind know how to exploit.

The probability of a rare event will (often, not always) be overestimated, because of the confirmatory bias of memory. Thinking about that event, you try to make it true in your mind. A rare event will be overweighted if it specifically attracts attention. Separate attention is effectively guaranteed when prospects are described explicitly (“99% chance to win $1,000, and 1% chance to win nothing”). 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 probabilities, 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.

“We shouldn’t focus on a single scenario, or we will overestimate its probability. Let’s set up specific alternatives and make the probabilities add up to 100%.”

“They want people to be worried by the risk. That’s why they describe it as 1 death per 1,000. They’re counting on denominator neglect.”

“I would like all of them to accept their risks.” In the context of that conversation, it was natural for the CEO to adopt a broad frame that encompassed all 25 bets. Like Sam facing 100 coin tosses, he could count on statistical aggregation to mitigate the overall risk.

“I decided to evaluate my portfolio only once a quarter. I am too loss averse to make sensible decisions in the face of daily price fluctuations.”

“Each of our executives is loss averse in his or her domain. That’s perfectly natural, but the result is that the organization is not taking enough risk.”

Finance research has documented a massive preference for selling winners rather than losers—a bias that has been given an opaque label: the disposition effect. The disposition effect is an instance of narrow framing.

Another argument against selling winners is the well-documented market anomaly that stocks that recently gained in value are likely to go on gaining at least for a short while.

The presence of sunk costs, the manager’s incentives are misaligned with the objectives of the firm and its shareholders, a familiar type of what is known as the agency problem. Boards of directors are well aware of these conflicts and often replace a CEO who is encumbered by prior decisions and reluctant to cut losses. The members of the board do not necessarily believe that the new CEO is more competent than the one she replaces. They do know that she does not carry the same mental accounts and is therefore better able to ignore the sunk costs of past investments in evaluating current opportunities.

The sunk-cost fallacy keeps people for too long in poor jobs, unhappy marriages, and unpromising research projects.

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. This has been verified in the context of gambling: people expect to be happier if they gamble and win than if they refrain from gambling and get the same amount.

My personal hindsight-avoiding policy is to be either very thorough or completely casual when making a decision with long-term consequences.

“We are hanging on to that stock just to avoid closing our mental account at a loss. It’s the disposition effect.”

“We discovered an excellent dish at that restaurant and we never try anything else, to avoid regret.”

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 a vested interest in what you choose. Salespeople quickly learn that manipulation of the context in which customers see a good can profoundly influence preferences.

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.

“The BTU units meant nothing to me until I saw how much air-conditioning units vary. Joint evaluation was essential.”

“It is often the case that when you broaden the frame, you reach more reasonable decisions.”

“When you see cases in isolation, you are likely to be guided by an emotional reaction of System 1.”

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.

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.

“They will feel better about what happened if they manage to frame the outcome in terms of how much money they kept rather than how much they lost.”

“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!”

The statistical analysis revealed two findings, which illustrate a pattern we have observed in other experiments: Peak-end rule: The global retrospective rating was well predicted by the average of the level of pain reported at the worst moment of the experience and at its end. Duration neglect: The duration of the procedure had no effect whatsoever on the ratings of total pain.

An inconsistency is built into the design of our minds. We have strong preferences about the duration of our experiences of pain and pleasure. 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 pleasure and short pains.

“You are thinking of your failed marriage entirely from the perspective of the remembering self. A divorce is like a symphony with a screeching sound at the end—the fact that it ended badly does not mean it was all bad.” “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.”

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.

People choose by memory when they decide whether or not to repeat an experience.

I am my remembering self, and the experiencing self, who does my living, is like a stranger to me.

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.

To get pleasure from eating, for example, you must notice that you are doing it.

Not surprisingly, a headache will make a person miserable, and the second best predictor of the feelings of a day is whether a person did or did not have contacts with friends or relatives. It is only a slight exaggeration to say that happiness is the experience of spending time with people you love and who love you.

“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?”

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.

The focusing illusion can cause people to be wrong about their present state of well-being as well as about the happiness of others, and about their own happiness in the future.

The mistake that people make in the focusing illusion involves attention to selected moments and neglect of what happens at other times. The mind is good with stories, 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 not a good day to ask him about his job satisfaction!”

“She looks quite cheerful most of the time, but when she is asked she says she is very unhappy. The question must make her think of her recent divorce.”

What can be done about biases? How can we improve judgments and decisions, both our own and those of the institutions that we serve and that serve us? The short answer is that little can be achieved without a considerable investment of effort. 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 reframed …” And I have made much more progress in recognizing the errors of others than my own. The way to block errors that originate in System 1 is simple in principle: recognize the signs that you are in a cognitive minefield, slow down, and ask for reinforcement from System 2.

Labels such as “anchoring effects,” “narrow framing,” or “excessive coherence” bring together in memory everything we know about a bias, its causes, its effects, and what can be done about it. There is a direct link from more precise gossip at the watercooler to better decisions.