Thinking, Fast and Slow

by Daniel Kahneman

Gilbert proposed that understanding a statement must begin with an attempt to believe it: you must first know what the idea would mean if it were true. Only then can you decide whether or not to unbelieve it. The

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.

The operations of associative memory contribute to a general confirmation bias.

Contrary to the rules of philosophers of science, who advise testing hypotheses by trying to refute them, people (and scientists, quite often) seek data that are likely to be compatible with the beliefs they currently hold.

If you like the president’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.

The halo effect is also an example of suppressed ambiguity: like the word bank, the adjective stubborn is ambiguous and will be interpreted in a way that makes it coherent with the context.

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.

to tame the halo effect conforms to a general principle: decorrelate error!

The Wisdom of Crowds, this is the kind of task in which individuals do very poorly, but pools of individual judgments do remarkably well.

the errors that individuals make are independent of the errors made by others, and (in the absence of a systematic bias) they tend to average to zero.

the magic of error reduction works well only when the observations are independent and their errors uncorrelated.

A simple rule can help: before an issue is discussed, all members of the committee should be asked to write a very brief summary of their position.

The standard practice of open discussion gives too much weight to the opinions of those who speak early and assertively, causing others to line up behind them.

the remarkable asymmetry between the ways our mind treats information that is currently available and information we do not have.

System 1 excels at constructing the best possible story that incorporates ideas currently activated, but it does not (cannot) allow for information it does not have.

When information is scarce, which is a common occurrence, System 1 operates as a machine for jumping to conclusions.

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?”

Jumping to conclusions on the basis of limited evidence is so important to an understanding of intuitive thinking, and comes up so often in this book, that I will use a cumbersome abbreviation for it: WYSIATI, which stands for what you see is all there is.

Furthermore, participants who saw one-sided evidence were more confident of their judgments than those who saw both sides.

Indeed, you will often find that knowing little makes it easier to fit everything you know into a coherent pattern.

Much of the time, the coherent story we put together is close enough to reality to support reasonable action. However, I will also invoke WYSIATI to help explain a long and diverse list of biases of judgment and choice, including the following among many others:

Overconfidence:

Framing effects:

Base-rate neglect:

This is an example of what I will call a judgment heuristic in the following chapters. Voters are attempting to form an impression of how good a candidate will be in office, and they fall back on a simpler assessment that is made quickly and automatically and is available when System 2 must make its decision.

Evidently, the relative importance of System 1 in determining voting choices is not the same for all people.

Here we encounter a new aptitude of System 1. An underlying scale of intensity allows matching across diverse dimensions.

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.

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 word comes from the same root as eureka.

people actually judge something else and believe they have judged probability. System 1 often makes this move when faced with difficult target questions, if the answer to a related and easier heuristic question comes readily to mind.

Another capability of System 1, intensity matching, is available to solve that problem. Recall that both feelings and contribution dollars are intensity scales.

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.

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.

System 1 is highly adept in one form of thinking—it automatically and effortlessly identifies causal connections between events, sometimes even when the connection is spurious.

the differences between dense and rural counties do not really count as facts: they are what scientists call artifacts, observations that are produced entirely by some aspect of the method of research—in this case, by differences in sample size.

Even now, you must exert some mental effort to see that the following two statements mean exactly the same thing: Large samples are more precise than small samples. Small samples yield extreme results more often than large samples do.

even sophisticated researchers have poor intuitions and a wobbly understanding of sampling effects.

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.

“intuitions about random sampling appear to satisfy the law of small numbers, which asserts that the law of large numbers applies to small numbers as well.” We

researchers regard their “statistical intuitions with proper suspicion and replace impression formation by computation whenever possible.”

“people are not adequately sensitive to sample size.”

System 1 is not prone to doubt. It suppresses ambiguity and spontaneously constructs stories that are as coherent as possible.

we are prone to exaggerate the consistency and coherence of what we see.

produce a representation of reality that makes too much sense.

Our predilection for causal thinking exposes us to serious mistakes in evaluating the randomness of truly random events.

We are pattern seekers, believers in a coherent world, in which regularities (such as a sequence of six girls) appear not by accident but as a result of mechanical causality or of someone’s intention.

The hot hand is entirely in the eye of the beholders, who are consistently too quick to perceive order and causality in randomness. The hot hand is a massive and widespread cognitive illusion.

Many facts of the world are due to chance, including accidents of sampling. Causal explanations of chance events are inevitably wrong.

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 quantity before estimating that quantity.