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Overcoming Bias Is the Mother of Science

Summary:
“Science is prediction.”  Not quite true, but still deeply insightful.  Especially when you remember that “Science is prediction” doesn’t mean a prediction that you whisper to yourself.  “Science is prediction” means a public prediction.  You have to shout it from the rooftops, in advance. When Einstein publicly predicted a specific anomaly in the deflection of light during a solar eclipse – and turned out to be exactly right – it was awesome.  Einstein loudly said exactly what was going to happen before it happened.  He was right.  And the world took notice. Now ponder this: As a matter of pure logic, the evidence would have been just as strong if Einstein waited for the eclipse measurements to come in, and then showed they were consistent with his theory.  But of

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“Science is prediction.”  Not quite true, but still deeply insightful.  Especially when you remember that “Science is prediction” doesn’t mean a prediction that you whisper to yourself.  “Science is prediction” means a public prediction.  You have to shout it from the rooftops, in advance.

When Einstein publicly predicted a specific anomaly in the deflection of light during a solar eclipse – and turned out to be exactly right – it was awesome.  Einstein loudly said exactly what was going to happen before it happened.  He was right.  And the world took notice.

Now ponder this: As a matter of pure logic, the evidence would have been just as strong if Einstein waited for the eclipse measurements to come in, and then showed they were consistent with his theory.  But of course the world’s reaction would have been far more tepid in this scenario.

Why?  In common-sense terms, the answer is, “It’s easy to ‘explain’ facts you already know.  Practically any smart person can do it.  As a result, we reasonably discount post hoc explanations.”

If you know a little modern psychology, though, you’ll be sorely tempted to say, “Public prediction greatly reduces the severity of confirmation bias.”  Human beings naturally tend to misinterpret the facts in favor of their own views.  But such misinterpretation is much more difficult if (a) you say exactly what’s going to happen before you see the facts, and (b) do so publicly to ensure that many of your listeners will refuse to gloss over your failed predictions.

And if you know more modern psychology, you’ll probably pile on.  “Public prediction greatly reduces the severity of not only confirmation bias, but also Biases X, Y, and Z.”  For example, public prediction also greatly reduces the severity of Social Desirability Bias.  Human beings naturally tend to say and believe things that sound good.  But sugar-coating reality is much more difficult if (a) you say exactly what’s going to happen before you see the facts, and (b) do so publicly to ensure that many of your listeners will refuse to gloss over your failed predictions.

The upshot: The adage that “Science is prediction” rests not on logic, but on psycho-logic.  Logically speaking, explaining after the fact is just as epistemically revealing as predicting before the fact.  Psychologically speaking, however, explaining after the fact is far inferior to predicting before the fact.  Why?  Because explaining after the fact is mired in intellectual corruption.  Predicting before the fact is, by comparison, squeaky clean.  Predicting before the fact is the best way to signal that you’re overcoming bias.

Otherwise you’re mired in what Tetlock calls “vague verbiage” and “self-scoring.”  You say things vague enough to be compatible with a wide range of outcomes.  And then you further water-down this forgiving metric by delegating the scoring to yourself.  An epistemic kangaroo court.

Notice, by the way, that betting combines the advantages of prediction with a recognition of its flaws.  Like predictions, bets are specific.  And even if a bet is “private,” at least one person who doubts you – your opponent – knows about it.

At the same time, the bet avoids the unfortunately binary nature of prediction.  Suppose Einstein’s light deflection prediction had failed.  That doesn’t prove he was wrong.  Perhaps something went wrong with the equipment.  Or one of the human beings measuring the light could have made a mistake.  Or a rival scientist could have deliberately sabotaged the experiment.  A bet – rather than a flat prediction – incorporates all of these contingencies.  And reminds us to focus not on any particular bet, but on the bettors’ track record.  That’s the best guide to whose judgment we should trust.

Given my still-perfect betting record, I’ll admit this is a suspicious conclusion.  And if that’s what you’re thinking, good for you.  You’re using psycho-logic to ferret out the truth, as every thoughtful person must.

Bryan Caplan
Bryan Caplan is Professor of Economics at George Mason University and Senior Scholar at the Mercatus Center. He has published in the New York Times, the Washington Post, the Wall Street Journal, the American Economic Review, the Economic Journal, the Journal of Law and Economics, and Intelligence, and has appeared on 20/20, FoxNews, and C-SPAN. Bryan Caplan blogs on EconLog.

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