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Cognitive Biases

The Illusion of Validity

The illusion of validity is confidence in a prediction that persists despite weak evidence or a poor record of accuracy. A coherent impression of a particular case can feel convincing even when we know that judgments of this kind have usually been unreliable.

THE IDEA

The Illusion of Validity

Daniel Kahneman recalls evaluating officer candidates during his military service:

Many decades ago I spent what seemed like a great deal of time under a scorching sun, watching groups of sweaty soldiers as they solved a problem. I was doing my national service in the Israeli Army at the time. I had completed an undergraduate degree in psychology, and after a year as an infantry officer was assigned to the army’s Psychology Branch, where one of my occasional duties was to help evaluate candidates for officer training. We used methods that had been developed by the British Army in World War II.

One test, called the “leaderless group challenge,” was conducted on an obstacle field. Eight candidates, strangers to each other, with all insignia of rank removed and only numbered tags to identify them, were instructed to lift a long log from the ground and haul it to a wall about six feet high. The entire group had to get to the other side of the wall without the log touching either the ground or the wall, and without anyone touching the wall. If any of these things happened, they had to declare it and start again.

There was more than one way to solve the problem. A common solution was for the team to send several men to the other side by crawling over the pole as it was held at an angle, like a giant fishing rod, by other members of the group. Or else some soldiers would climb onto someone’s shoulders and jump across. The last man would then have to jump up at the pole, held up at an angle by the rest of the group, shinny his way along its length as the others kept him and the pole suspended in the air, and leap safely to the other side. Failure was common at this point, which required them to start all over again.

As a colleague and I monitored the exercise, we made note of who took charge, who tried to lead but was rebuffed, how cooperative each soldier was in contributing to the group effort. We saw who seemed to be stubborn, submissive, arrogant, patient, hot-tempered, persistent, or a quitter. We sometimes saw competitive spite when someone whose idea had been rejected by the group no longer worked very hard. And we saw reactions to crisis: who berated a comrade whose mistake had caused the whole group to fail, who stepped forward to lead when the exhausted team had to start over. Under the stress of the event, we felt, each man’s true nature revealed itself. Our impression of each candidate’s character was as direct and compelling as the color of the sky.

After watching the candidates make several attempts, we had to summarize our impressions of soldiers’ leadership abilities and determine, with a numerical score, who should be eligible for officer training. We spent some time discussing each case and reviewing our impressions. The task was not difficult, because we felt we had already seen each soldier’s leadership skills. Some of the men had looked like strong leaders, others had seemed like wimps or arrogant fools, others mediocre but not hopeless. Quite a few looked so weak that we ruled them out as candidates for officer rank. When our multiple observations of each candidate converged on a coherent story, we were completely confident in our evaluations and felt that what we had seen pointed directly to the future. The soldier who took over when the group was in trouble and led the team over the wall was a leader at that moment. The obvious best guess about how he would do in training, or in combat, was that he would be as effective then as he had been at the wall. Any other prediction seemed inconsistent with the evidence before our eyes.

Because our impressions of how well each soldier had performed were generally coherent and clear, our formal predictions were just as definite. A single score usually came to mind and we rarely experienced doubts or formed conflicting impressions. We were quite willing to declare, “This one will never make it,” “That fellow is mediocre, but he should do okay,” or “He will be a star.” We felt no need to question our forecasts, moderate them, or equivocate. If challenged, however, we were prepared to admit, “But of course anything could happen.” We were willing to make that admission because, despite our definite impressions about individual candidates, we knew with certainty that our forecasts were largely useless.

The evidence that we could not forecast success accurately was overwhelming. Every few months we had a feedback session in which we learned how the cadets were doing at the officer-training school and could compare our assessments against the opinions of commanders who had been monitoring them for some time. The story was always the same: our ability to predict performance at the school was negligible. Our forecasts were better than blind guesses, but not by much.

We were downcast for a while after receiving the discouraging news. But this was the army. Useful or not, there was a routine to be followed and orders to be obeyed. Another batch of candidates arrived the next day. We took them to the obstacle field, we faced them with the wall, they lifted the log, and within a few minutes we saw their true natures revealed, as clearly as before. The dismal truth about the quality of our predictions had no effect whatsoever on how we evaluated candidates and very little effect on the confidence we felt in our judgments and predictions about individuals.

What happened was remarkable. The global evidence of our previous failure should have shaken our confidence in our judgments of the candidates, but it did not. It should also have caused us to moderate our predictions, but it did not. We knew as a general fact that our predictions were little better than random guesses, but we continued to feel and act as if each of our specific predictions was valid. I was reminded of the Müller-Lyer illusion, in which we know the lines are of equal length yet still see them as being different. I was so struck by the analogy that I coined a term for our experience: the illusion of validity.


This experience illustrates the illusion of validity: the tendency to overestimate the reliability and accuracy of our judgments, especially when we can construct a coherent narrative from the information at hand. The illusion of validity arises from the way System 1 operates. In this account, it readily reaches conclusions from limited evidence without assessing how much the evidence warrants. WYSIATI (What You See Is All There Is) describes the tendency to build a judgment from the evidence at hand without adequately considering what is missing. The ease with which a plausible story comes together produces a sense of confidence that is felt as a direct, almost perceptual, experience. Subjective confidence can therefore reflect a story’s coherence without tracking the quality or quantity of its evidence. Poor evidence can make a very good story, and for some of our most important beliefs we have no evidence at all except that people we love and trust hold those beliefs.

The illusion is fueled by the representativeness heuristic: we evaluate a person or situation based on how closely it matches a mental stereotype, ignoring statistical considerations such as base rates or regression to the mean. After observing one hour of behavior in an artificial setting, the evaluators felt they could forecast leadership in training and combat. They made extreme predictions without adjusting them toward average performance to reflect the weakness of the evidence. Kahneman compares this with Nisbett and Borgida’s studies: people can accept a statistical finding yet fail to apply it to an individual case.

Selective memory and self-serving explanations can sustain such confidence: a success confirms skill, while a failure is attributed to circumstances. Delayed or ambiguous feedback can make this pattern harder to detect. In the Army example, however, even clear feedback about poor overall accuracy did little to alter the compelling impression of each new candidate.

Kahneman and Amos Tversky studied the illusion in the 1970s. Later research on overconfidence and prediction provides related examples. Barber and Odean (2002) demonstrated in their paper “Trading Is Hazardous to Your Wealth” that frequent individual trading was associated with poorer investment performance, including the effect of trading costs. Overconfidence is one proposed explanation; the return difference alone does not establish what each investor believed. Philip Tetlock’s study of expert political judgment (2005) examined forecast accuracy and confidence against benchmarks, including simple statistical models. Performance varied, but expertise and a persuasive explanation did not reliably ensure accurate forecasts. Recording predictions made it possible to compare apparent authority with results.

The same problem can arise in other decisions. In investing, confidence in an untested pattern may encourage costly trading. In business, leaders often make strategic decisions based on compelling narratives rather than on base rates and probabilistic analysis, overestimating their ability to foresee success. In everyday life, we rely heavily on first impressions and anecdotal evidence when hiring, forming relationships, or making personal decisions, placing far more weight on a coherent story than it deserves.

To check this confidence, consider base rates and a range of possible outcomes. Actively search for disconfirming evidence—ask what would prove your prediction wrong and seek that information out. Maintaining a prediction diary, where you record confidence levels alongside outcomes over time, helps calibrate your sense of knowing and reveals the gap between felt confidence and actual accuracy. Compare judgments with statistical models or decision aids whose performance has been tested on relevant cases. A formula can provide a useful benchmark, but its accuracy also needs checking.

The illusion of validity rarely travels alone. It is closely related to hindsight bias—the feeling that past events were more predictable than they really were (“The mistake appears obvious, but it is just hindsight”)—and to outcome bias, where a decision is judged by its result rather than its quality (“This was a stupid decision even though it worked out well”). When a firm’s stock falls, the tendency is to conclude that its management must be bad, an inference that confuses a coherent story with evidence. These biases concern different errors in judging evidence and outcomes. For the illusion of validity, the practical question is whether confidence is supported by a record of accurate predictions in comparable cases.

When to use it

  • Analyzing why a business strategy succeeded, avoiding hindsight bias.

  • Evaluating a manager's performance based on outcomes alone.

  • Making predictions in financial markets where confidence can be misleading.

  • Learning from historical events by considering alternative scenarios.

  • Hiring: Compare an interviewer’s strong impression with structured criteria and later job performance to test whether confidence predicts useful results.

  • Diagnosis: Check whether a compelling initial explanation accounts for the evidence and relevant alternatives.

  • Investment research: Separate an appealing company story from evidence that has predicted results in comparable cases.

  • College admissions: Check whether confidence prompted by an essay or interview is supported by the institution’s record of predicting student outcomes.

  • Financial planning: Recognizing the illusion of validity can help investors avoid overtrading and reliance on short-term predictions.

  • Project management: When estimating timelines and costs, awareness of this bias encourages using historical data and probabilistic forecasts instead of overconfident best-case scenarios.

  • Hiring and promotions: Interviewers often feel confident in their gut instincts; understanding this bias can prompt structured interviews and objective criteria.

  • Professional judgment: Compare a decision aid with existing practice before relying on it to improve predictions.

FROM THEORY TO EVERYDAY LIFE

In practice

01

Hindsight Bias Example

“The mistake appears obvious, but it is just hindsight. You could not have known in advance.”

02

Narrative Fallacy Example

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

03

Outcome Bias and Halo Effect Example

“She has no evidence for saying that the firm is badly managed. All she knows is that its stock has gone down. This is an outcome bias, part hindsight and part halo effect.”

04

Outcome Bias Example

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

05

The Leaderless Group Challenge

Daniel Kahneman recounts his experience in the Israeli Army evaluating officer candidates. Despite knowing from extensive feedback that their predictions of future success were barely better than random chance, he and his colleagues remained highly confident in their assessments of individual candidates based on their behavior during a one-hour obstacle course exercise. Their confidence in the specific case persisted even when they acknowledged the general rule of their predictive helplessness.

06

Nisbett and Borgida's Helping Behavior Study

In Nisbett and Borgida’s study, learning that many participants failed to help during a staged emergency did little to alter students’ predictions about particular people seen in interviews. Kahneman uses the comparison to show how general statistical information can fail to change a judgment about an individual.

07

Stock Market Trading

A day trader feels certain that a pattern in prices and news predicts short-term movements. Comparing a written forecast record with a benchmark could test that belief. Barber and Odean’s findings on frequent trading and returns make this a relevant concern, without proving the cause of this particular trader’s confidence.

08

Expert Political Forecasts

A pundit offers a confident forecast supported by a compelling account of events. Tetlock’s approach suggests recording the forecast, its probability, and its outcome, then comparing a series of forecasts with a benchmark. A persuasive explanation alone does not establish accuracy.

✳

A MOMENT TO REFLECT

Put it to work.

  1. Recall a time you were overly confident in a judgment based on a coherent story. What evidence were you ignoring?

  2. How can you test the validity of your beliefs when you have little evidence?

  3. In what situations might confidence be useful even if it is based on flimsy evidence?

  4. Think about a time you made a very confident prediction about someone's success (e.g., in a job interview, an audition, or a first date) based on a very small sample of behavior. How good was your actual track record in those situations?

  5. Kahneman states that 'subjective confidence in a judgment is not a reasoned evaluation of the probability that this judgment is correct.' How can you distinguish between feeling confident about a story and knowing a prediction is likely to be accurate?

  6. In a field whose experts you respect, what evidence would distinguish well-founded confidence from a persuasive explanation?

  7. Could you record a set of predictions and confidence levels before the outcomes are known? What would count as a fair benchmark?

  8. In your professional field, what are common situations where people display the illusion of validity? How might you use base rates or algorithms to improve decision-making?

  9. When a prediction fails, do you revise your view of the method or treat the case as an exception? How would you decide which response is justified?

Connected ideas

Another lens can bring the same problem into focus.

Often confused with

References

  1. Thinking, Fast and Slow — Daniel Kahneman (2011)
  2. Attribution and the Psychology of Prediction — Richard Nisbett and Eugene Borgida (1975)
  3. Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors — Brad M. Barber and Terrance Odean (2002)
  4. Boys Will Be Boys: Gender, Overconfidence, and Common Stock Investment — Brad M. Barber and Terrance Odean (2006)
  5. All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors — Brad M. Barber and Terrance Odean (2008)
  6. Just How Much Do Individual Investors Lose by Trading? — Brad M. Barber, Yi-Tsung Lee, Yu-Jane Liu, and Terrance Odean (2009)
  7. Expert Political Judgment: How Good is It? How Can We Know? — Philip E. Tetlock (2005)

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Source texts

  • Thinking, Fast and Slow (Daniel Kahneman)
  • Thinking, Fast and Slow (Daniel Kahneman)
  • Thinking, Fast and Slow (Daniel Kahneman)
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