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This is my first attempt at starting a casual conversation on LW where people don't have to worry about winning or losing points, and can just relax and have social fun together.

So, Big Bang Theory. That series got me wondering. It seems to be about "geeks", and not the basement-dwelling variety either; they're highly successful and accomplished professionals, each in their own field. One of them has been an astronaut, even. And yet, everything they ever accomplish amounts to absolutely nothing in terms of social recognition or even in terms of personal happiness. And the thing is, it doesn't even get better for their "normal" counterparts, who are just as miserable and petty.

Consider, then; how would being rationalists would affect the characters on this show? The writing of the show relies a lot on laughing at people rather than with them; would rationalist characters subvert that? And how would that rationalist outlook express itself given their personalities? (After all, notice how amazingly different from each other Yudkowsky, Hanson, and Alicorn are, just to name a few; they emphasize rather different things, and take different approaches to both truth-testing and problem-solving).

Note: this discussion does not need to be about rationalism. It can be a casual, normal discussion about the series. Relax and enjoy yourselves.

But the reason I brought up that series is that its characters are excellent examples of high intelligence hampered by immense irrationality. The apex of this is represented by Dr. Sheldon Cooper, who is, essentially, a complete fundamentalist over every single thing in his life; he applies this attitude to everything, right down to people's favorite flavor of pudding: Raj is "axiomatically wrong" to prefer tapioca, because the best pudding is chocolate. Period. This attitude makes him a far, far worse scientist than he thinks, as he refuses to even consider any criticism of his methods or results. 

Interesting corollary to Tyler Cowen's TED talk:

Models this complex -- whether of cellular biology, the weather, the economy, even highway traffic -- often fail us, because the world is more complex than our models can capture. But sometimes they can predict accurately how the system will behave. At their most complex these are sciences of emergence and complexity, studying properties of systems that cannot be seen by looking only at the parts, and cannot be well predicted except by looking at what happens.

[...]

With the new database-based science, there is often no moment when the complex becomes simple enough for us to understand it. The model does not reduce to an equation that lets us then throw away the model. You have to run the simulation to see what emerges. For example, a computer model of the movement of people within a confined space who are fleeing from a threat--they are in a panic--shows that putting a column about one meter in front of an exit door, slightly to either side, actually increases the flow of people out the door. Why? There may be a theory or it may simply be an emergent property. We can climb the ladder of complexity from party games to humans with the single intent of getting outside of a burning building, to phenomena with many more people with much more diverse and changing motivations, such as markets. We can model these and perhaps know how they work without understanding them. They are so complex that only our artificial brains can manage the amount of data and the number of interactions involved.

[...]

Model-based knowing has many well-documented difficulties, especially when we are attempting to predict real-world events subject to the vagaries of history; a Cretaceous-era model of that eras ecology would not have included the arrival of a giant asteroid in its data, and no one expects a black swan. Nevertheless, models can have the predictive power demanded of scientific hypotheses. We have a new form of knowing.