Tag Archives: Overconfidence

Overconfidence Looks Good

Overconfidence is a Social Signaling Bias:

We test three different theories about observed relative overconfidence. The first theory notes that simple statistical comparisons are compatible with a Bayesian model of updating from a common prior and truthful statements. … Data on 1,016 individuals’ relative ability judgments about two cognitive tests rejects the Bayesian model. The second theory suggests that self-image concerns asymmetrically affect the choice to get new information about one’s abilities. … We test an important specific prediction of these models: individuals with a higher belief will be less likely to search for further information about their skill. … Our data also reject this prediction. The third theory is that overconfidence is induced by the desire to send positive signals to others about one’s own skill; this suggests either a bias in judgment, strategic lying, or both. We provide evidence that personality traits strongly affect relative ability judgments in a pattern that is consistent with this third theory. Our results together suggest that overconfidence in statements is most likely to be induced by social concerns than by either of the other two factors.

This of course means that you should expect to risk looking less impressive to others if you correct for your overconfidence.

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How To Survey Confidence

In a 3-point elicitation procedure, an expert is asked for a lower limit, upper limit, and best guess, the two limits creating an interval of some assigned confidence level (e.g., 80%). In our 4-step interval elicitation procedure, experts were also asked for a realistic lower limit, upper limit, and best guess, but no confidence level was assigned; the fourth step was to rate their anticipated confidence in the interval produced. … We … found average overconfidence of 11.9%, 95% CI [3.5, 20.3] (a hit rate of 68.1% for 80% intervals)—a substantial decrease in overconfidence compared with previous studies.

More here.

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Forensic Delusions

A groundbreaking report by the National Academy of Sciences (NAS) last year recognized that much of forensic science is not rooted in solid science. Many forensic disciplines — such as hair microscopy, bite-mark comparisons, fingerprint analysis, firearm testing and tool-mark analysis — were developed solely to solve crimes.  They evolved mainly in the context of individual cases, which often had significant variation in resources and expertise. They have not been subjected to rigorous experimental scrutiny, and there are no standards or oversight in the United States or elsewhere to ensure that validated, reliable forensic methods are used consistently. With the exception of DNA analysis, no forensic method has been proved to reliably and accurately demonstrate a connection between evidence and a specific source. …

We advocate the creation of an office of forensic science improvement and support (OFSIS) within the US Department of Commerce to spur independent research, develop standards and ensure compliance. … [Some] within the forensic-science and law-enforcement fields … argue that an OFSIS is not necessary and that laboratory accreditation is sufficient. … They argue that an OFSIS would cost too much … and that it could create chaos in the US justice system by reopening countless old cases. … Political and criminal-justice ends — rather than research imperatives — have taken forensic science off course. … See www.just-science.org.

More here.  The primary social pressure on law court practices is for courts to give the appearance of punishing guilty folks.  Observers have much less info on who is actually guilty.  So the main pressure on legal standards is that officially-accepted evidence seem to the public, juries, and judges to indicate guilt, not that it actually indicate guilt.  We expect the law to be overconfident about its evidence.

Requiring that legal evidence standards stand up to independent experimental scrutiny would create a more accurate legal system, but at the expense of reducing the apparent rate at which the guilty are punished.  So I expect, sadly, this proposal to be rejected.

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The Confidence Heuristic

In Moore’s experiment, volunteers were given cash for correctly guessing the weight of people from their photographs. In each of the eight rounds of the study, the guessers bought advice from one of four other volunteers. The guessers could see in advance how confident each of these advisers was (see table), but not which weights they had opted for.

From the start, the more confident advisers found more buyers for their advice, and this caused the advisers to give answers that were more and more precise as the game progressed. This escalation in precision disappeared when guessers simply had to choose whether or not to buy the advice of a single adviser. In the later rounds, guessers tended to avoid advisers who had been wrong previously, but this effect was more than outweighed by the bias towards confidence. …

Moore said that following the advice of the most confident person often makes sense, as there is evidence that precision and expertise do tend to go hand in hand. For example, people give a narrower range of answers when asked about subjects with which they are more familiar.

There are times, however, when this link breaks down. With complex but politicised subjects such as global warming, for example, scientific experts who stress uncertainties lose out to activists or lobbyists with a more emphatic message.

That is from New Scientist back in June.  So the key hard question is: when does confidence credibly signal expertise, and when it is just empty cheap talk?  Hat tip to Toby Ord.

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Shy And Badly Dressed

Gladwell:

The psychologist Ellen Langer once had subjects engage in a betting game against either a self-assured, well-dressed opponent or a shy and badly dressed opponent (in Langer’s delightful phrasing, the “dapper” or the “schnook” condition), and she found that her subjects bet far more aggressively when they played against the schnook. They looked at their awkward opponent and thought, I’m better than he is. Yet the game was pure chance: all the players did was draw cards at random from a deck, and see who had the high hand. This is called the “illusion of control”: confidence spills over from areas where it may be warranted (“I’m savvier than that schnook”) to areas where it isn’t warranted at all (“and that means I’m going to draw higher cards”).

I was once a shy badly dressed person who didn’t understand why people kept underestimating him.  Now I know.

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Obama’s Opportunity Cost

The US public has long felt guilty about historical racism, and so they felt great about electing a black president, and giving him some space to do what he wants. That and Bush-hatred seemed to give progressives a rare opportunity to achieve many things they’ve always wanted.

This opportunity now seems substantially squandered.  Obama has spent much of his political capital on changes far from professed progressive priorities.  He spent lots on fiscal stimulus and nationalizing the auto industry, and seems to have too little left for big medical and financial reform.  Tyler and I have long said Obama can’t do near as much as supporters seemed to think, and we’ve been puzzled to hear this prospect dismissed out of hand .

For Obama and his new-to-power advisers, this failure may come from overconfidence, but his old-hand-operative advisers should have known better.  So either their stern warnings were ignored, or they betrayed him by not making stern warnings.  Since much of Obama’s political capital was spent by longtime congressional Democrats choosing the detailed pork of stimulus and related bills, they might be blamed.  If they said “Support us to pick this pork now, and we’ll help you get health care reform later,” they were basically taking him to the cleaners.

For progressives, the lost opportunity here is not just bills not passed, or the public checking off “elect a minority president” from their to-do-list.  Another cost is a more conservative public opinion. Psychology experiments explain: Continue reading "Obama’s Opportunity Cost" »

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Write Your Hypothetical Apostasy

Let's say you have been promoting some view (on some complex or fraught topic – e.g. politics, religion; or any "cause" or "-ism") for some time.  When somebody criticizes this view, you spring to its defense.  You find that you can easily refute most objections, and this increases your confidence.  The view might originally have represented your best understanding of the topic.  Subsequently you have gained more evidence, experience, and insight; yet the original view is never seriously reconsidered.  You tell yourself that you remain objective and open-minded, but in fact your brain has stopped looking and listening for alternatives.

Here is a debiasing technique one might try: writing a hypothetical apostasy.  Remind yourself before you start that unless you later choose to do so, you will never have to show this text to anyone.

Imagine, if you will, that the world's destruction is at stake and the only way to save it is for you to write a one-pager that convinces a jury that your old cherished view is mistaken or at least seriously incomplete.  The more inadequate the jury thinks your old cherished view is, the greater the chances that the world is saved.  The catch is that the jury consists of earlier stages of yourself (such as yourself such as you were one year ago).  Moreover, the jury believes that you have been bribed to write your apostasy; so any assurances of the form "trust me, I am older and know better" will be ineffective.  Your only hope of saving the world is by writing an apostasy that will make the jury recognize how flawed/partial/shallow/juvenile/crude/irresponsible/incomplete and generally inadequate your old cherished view is.

(If anybody tries this, feel free to comment below on whether you found the exersise fruitful or not – but no need to state which specific view you were considering or how it changed.)

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No Overconfidence?

New data question the claim that people tend to overestimate their abilities:

A large body of literature purports to find that people are generally overconfident. In particular, a better-than-average effect in which a majority of people claim to be superior to the average person has been noted for a wide range of skills, from driving, to spoken expression, to the ability to get along with others, to test taking on simple tests. The literature generally accepts that this better-than-average effect is indicative of inflated self- assessments. However, [we] recently … show that the better-than-average data … does not indicate … people have made some kind of error in their self-evaluations.  Because of this reason, almost none of the existing experimental literature on relative overconfidence can actually claim to have found overconfidence. … In this paper, we report on an experiment designed to provide a proper test of overconfidence. … As in much previous experimental work, we find a better-than-average effect among our subjects. … We find evidence that subjects are uncertain of their own types. Our experiment can be viewed as a test of the null hypothesis that people are behaving rationally (and are not overconfident). We cannot reject that hypothesis.
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Entrepreneurs Are Not Overconfident

Not too long ago, the well-known economist Robert Hall presented this paper (co-authored with Susan E. Woodward) at my place of work.  Here is the abstract:

In the standard venture capital contract, entrepreneurs have a large fraction of equity ownership in the companies they found and are paid a sub-market salary by the investors who provide the money to develop the idea.  The big rewards come only to those whose companies go public or are acquired on favorable terms, forcing entrepreneurs to bear a substantial burden of idiosyncratic risk.  We study this burden in the case of high-tech companies funded by venture capital.  Over the past 20 years, the typical venture-backed entrepreneur earned an average of $4.4 million from companies that succeeded in attracting venture funding.  Entrepreneurs with a coefficient of relative risk aversion of two and with less than $0.7 million would be better off in a salaried position than in a startup, despite the prospect of an average personal payoff of $4.4 million and the possibility of payoffs over $1 billion.  We conclude that startups attract entrepreneurs with lower risk aversion, higher initial assets, preferences for entrepreneurship over employment, and optimistic beliefs about the payoffs from their products.

During the seminar it occurred to me that these results, assuming they are correct, are evidence of an absence of overconfidence, at least among the kinds of people who leave good jobs to form high-tech startups.  The reason is that if potential entrepreneurs were massively overconfident, one would expect to see lots of entry of startups based on weak ideas, which would lead to an expected payoff so low that forming a startup would be a losing proposition for the potential entrepreneur unless he/she started out extremely wealthy and/or had very low risk-aversion.  But what the authors actually find is that forming a startup with an average-quality idea* is a break-even proposition for a potential entrepreneur with quite modest wealth and with a more-or-less standard degree of risk-aversion.

After the talk, I asked Professor Hall if he agreed with this interpretation (he seemed to), and if he would object to my posting about it on OB (he didn't).  But I will make him aware of this post, and invite him to comment if he would like, and correct any mistakes that I might have made.

*The authors have no way to distinguish the quality of an idea, so there is an implicit assumption that the marginal quality of the idea is equal to the average quality of all ideas that actually get implemented.
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Luck Pessimism

While we tend to be optimistic about our abilities, we are pessimistic about our luck:

We analyze the answers of a sample of 1,540 individuals to the following question "Imagine that a coin will be flipped 10 times. Each time, if heads, you win 10C. How many times do you think that you will win?" The average answer is surprisingly about 3.9 which is below the average 5, and we interpret this as a pessimistic bias. We find that women are more "pessimistic" than men, as are old people relative to young.

Added:  Benja Fallenstein notes "if there is no [personal] gain associated to the coin tossing, the average [guess] is 4.9, and 90% answer 5.

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