When Richard Feynman started investigating irrationality in the 1970s, he quickly begun to realize the problem wasn't limited to the obvious irrationalists.

Uri Geller claimed he could bend keys with his mind. But was he really any different from the academics who insisted their special techniques could teach children to read? Both failed the crucial scientific test of skeptical experiment: Geller's keys failed to bend in Feynman's hands; outside tests showed the new techniques only caused reading scores to go down.

What mattered was not how smart the people were, or whether they wore lab coats or used long words, but whether they followed what he concluded was the crucial principle of truly scientific thought: "a kind of utter honesty--a kind of leaning over backwards" to prove yourself wrong. In a word: self-skepticism.

As Feynman wrote, "The first principle is that you must not fool yourself -- and you are the easiest person to fool." Our beliefs always seem correct to us -- after all, that's why they're our beliefs -- so we have to work extra-hard to try to prove them wrong. This means constantly looking for ways to test them against reality and to think of reasons our tests might be insufficient.

When I think of the most rational people I know, it's this quality of theirs that's most pronounced. They are constantly trying to prove themselves wrong -- they attack their beliefs with everything they can find and when they run out of weapons they go out and search for more. The result is that by the time I come around, they not only acknowledge all my criticisms but propose several more I hadn't even thought of.

And when I think of the least rational people I know, what's striking is how they do the exact opposite: instead of viciously attacking their beliefs, they try desperately to defend them. They too have responses to all my critiques, but instead of acknowledging and agreeing, they viciously attack my critique so it never touches their precious belief.

Since these two can be hard to distinguish, it's best to look at some examples. The Cochrane Collaboration argues that support from hospital nurses may be helpful in getting people to quit smoking. How do they know that? you might ask. Well, they found this was the result from doing a meta-analysis of 31 different studies. But maybe they chose a biased selection of studies? Well, they systematically searched "MEDLINE, EMBASE and PsycINFO [along with] hand searching of specialist journals, conference proceedings, and reference lists of previous trials and overviews." But did the studies they pick suffer from selection bias? Well, they searched for that -- along with three other kinds of systematic bias. And so on. But even after all this careful work, they still only are confident enough to conclude "the results…support a modest but positive effect…with caution … these meta-analysis findings need to be interpreted carefully in light of the methodological limitations".

Compare this to the Heritage Foundation's argument for the bipartisan Wyden–Ryan premium support plan. Their report also discusses lots of objections to the proposal, but confidently knocks down each one: "this analysis relies on two highly implausible assumptions ... All these predictions were dead wrong. ... this perspective completely ignores the history of Medicare" Their conclusion is similarly confident: "The arguments used by opponents of premium support are weak and flawed." Apparently there's just not a single reason to be cautious about their enormous government policy proposal!

Now, of course, the Cochrane authors might be secretly quite confident and the Heritage Foundation might be wringing their hands with self-skepticism behind-the-scenes. But let's imagine for a moment that these aren't just reportes intended to persuade others of a belief and instead accurate portrayals of how these two different groups approached the question. Now ask: which style of thinking is more likely to lead the authors to the right answer? Which attitude seems more like Richard Feynman? Which seems more like Uri Geller?

If you're interested in learning rationality, where should you start? Remember, instrumental rationality is about making decisions that get you what you want -- surely there are some lessons that will help you more than others.

You might start with the most famous ones, which tend to be the ones popularized by Kahneman and Tversky. But K&T were academics. They weren't trying to help people be more rational, they were trying to prove to other academics that people were irrational. The result is that they focused not on the most important biases, but the ones that were easiest to prove.

Take their famous anchoring experiment, in which they showed the spin of a roulette wheel affected people's estimates about African countries. The idea wasn't that roulette wheels causing biased estimates was a huge social problem; it was that no academic could possibly argue that this behavior was somehow rational. They thereby scored a decisive blow for psychology against economists claiming we're just rational maximizers.

Most academic work on irrationality has followed in K&T's footsteps. And, in turn, much of the stuff done by LW and CFAR has followed in the footsteps of this academic work. So it's not hard to believe that LW types are good at avoiding these biases and thus do well on the psychology tests for them. (Indeed, many of the questions on these tests for rationality come straight from K&T experiments!)

But if you look at the average person and ask why they aren't getting what they want, very rarely do you conclude their biggest problem is that they're suffering from anchoring, framing effects, the planning fallacy, commitment bias, or any of the other stuff in the sequences. Usually their biggest problems are far more quotidian and commonsensical.

Take Eliezer. Surely he wanted SIAI to be a well-functioning organization. And he's admitted that lukeprog has done more to achieve that goal of his than he has. Why is lukeprog so much better at getting what Eliezer wants than Eliezer is? It's surely not because lukeprog is so much better at avoiding Sequence-style cognitive biases! lukeprog readily admits that he's constantly learning new rationality techniques from Eliezer.

No, it's because lukeprog did what seems like common sense: he bought a copy of Nonprofits for Dummies and did what it recommends. As lukeprog himself says, it wasn't lack of intelligence or resources or akrasia that kept Eliezer from doing these things, "it was a gap in general rationality."

So if you're interested in closing the gap, it seems like the skills to prioritize aren't things like commitment effect and the sunk cost fallacy, but stuff like "figure out what your goals really are", "look at your situation objectively and list the biggest problems", "when you're trying something new and risky, read the For Dummies book about it first", etc. For lack of better terminology, let's call the K&T stuff "cognitive biases" and this stuff "practical biases" (even though it's all obviously both practical and cognitive and biases is kind of a negative way of looking at it). 

What are the best things you've found on tackling these "practical biases"? Post your suggestions in the comments.

My friend, hearing me recount tales of LessWrong, recently asked me if I thought it was simply a coincidence that so many LessWrong rationality nerds cared so much about creating Friendly AI. "If Eliezer had simply been obsessed by saving the world from asteroids, would they all be focused on that?"

Obviously one possibility (the inside view) is simply that rationality compels you to focus on FAI. But if we take the outside view for a second, it does seem like FAI has a special attraction for armchair rationalists: it's the rare heroic act that can be accomplished without ever confronting reality.

After all, if you want to save the planet from an asteroid, you have to do a lot of work! You have to build stuff and test it and just generally solve a lot of gritty engineering problems. But if you want to save the planet from AI, you can conveniently do the whole thing without getting out of bed.

Indeed, as the Tool AI debate as shown, SIAI types have withdrawn from reality even further. There are a lot of AI researchers who spend a lot of time building models, analyzing data, and generally solving a lot of gritty engineering problems all day. But the SIAI view conveniently says this is all very dangerous and that one shouldn't even begin to try implementing anything like an AI until one has perfectly solved all of the theoretical problems first.

Obviously this isn't any sort of proof that working on FAI is irrational, but it does seem awfully suspicious that people who really like to spend their time thinking about ideas have managed to persuade themselves that they can save the entire species from certain doom just by thinking about ideas.