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SK2
Imagine an experiment where we randomize subjects into two groups. All subjects are given a 20-question quiz that asks them to provide a confidence interval on the temperatures in various cities around the world on various dates in the past year. However, the cities and dates for group 1 are chosen at random, whereas the cities and dates for group 2 are chosen because they were record highs or lows.
This will result in two radically different estimates of overconfidence. The fact that the result of a calibration test depends heavily on the questions being asked should suggest that the methodology is problematic.
What this comes down to is: how do you estimate the probability that a question has an unexpected answer? See this quiz: maybe the quizzer is trying to trick you, maybe he’s trying to reverse-trick you, or maybe he just chose his questions at random. It’s a meaningless exercise because you’re being asked to estimate values from an unknown distribution. The only rational thing to do is guess at random.
People taking a calibration test should first see the answers to a sample of the data set they will be tested on.
I have seen a problem with selection bias in calibration tests, where trick questions are overrepresented. For example, in this PDF article, the authors ask subjects to provide a 90% confidence interval estimating the number of employees IBM has. They find that fewer than 90% of subjects select a suitable range, which they conclude results from overconfidence. However, IBM has almost 400,000 employees, which is atypically high (more than 4x Microsoft). The results of this study have just as much to do with the question asked as with the overconfidence of the subjects.
Similarly, trivia questions are frequently (though not always) designed to have interesting/unintuitive answers, making them problematic for a calibration quiz where people are expecting straightforward questions. I don’t know that to be the case for the AcceleratingFuture quizzes, but it is an issue in general.
Another reason converts are more zealous than people who grew up with a religion is that conversion is a voluntary act, whereas being born into a religious family is not. Converting to a religion late in life is a radical move, one that generally requires a certain amount of zeal and motivation to begin with, so converts are pre-selected to be zealous.
Regarding the “Repent” example: as conformists, human beings are more likely to make particular decisions (like wear a “Repent” sign) if they believe others would do the same. So instead of framing this study as showing that “sign-wearing volunteers overestimate the probability others would volunteer”, one could flip the implied causality and say “people who think others would volunteer are more likely to volunteer themselves”, a much more banal claim. One could test the effect by re-running the experiment on self-identified nonconformists, or using behaviors for which conformity is not believed to play a big role. I predict the False Consensus Effect discovered in those settings would be much weaker.
The blue/red ball analogy is good food for thought, but there are way too many differences between it and the “Repent” study for the numerical similarity to be considered anything more than a coincidence. Our approximations of other people’s behavior are much more elaborate than making a naive inference based on a sample of one.
I wonder how long-lasting this “quota” effect is. The study only looked at the immediate effects of moral behavior, not the more important long-term effects.
To make an analogy with physical exercise, maybe flexing your moral muscles exhausts your ability to be moral for the rest of the day, but when you wake up tomorrow your moral strength will be not only restored but actually strengthened. Most forms of exertion I can think of (e.g. learning, writing, working) work like this, so I wouldn’t be surprised if the same held for doing good deeds.
I think this disagreement comes down to the definition of “bias”, which Wikipedia defines as “a tendency or preference towards a particular perspective, ideology or result, when the tendency interferes with the ability to be impartial, unprejudiced, or objective.” If a bias helps you make fewer errors, I would argue it’s not a bias.
Maybe it is clearer if we speak of behaviors rather than biases. A given behavior (e.g. tendency to perceive what you were expecting to perceive) may make you more biased in certain contexts, and more rational in others. It might be advantageous to keep this behavior if it helps you more than it hurts you, but to the extent that you can identify the situations where the behavior causes errors, you should try to correct it.
Great audio clip, BTW.