# Are smart people's personal experiences biased against general intelligence?

*TL;DR: Collider between* g *and valued traits in anecdotal experiences.*

IQ tests measure the *g* factor - that is, mental traits and skills that are useful across a wide variety of cognitive tasks. *g* appears to be important for a number of outcomes, particularly socioeconomic outcomes like education, job performance and income. *g* is often equated with intelligence.

I believe that smart people's personal experiences are biased against the *g* factor. That is, I think that people who are high in *g* will tend to see things in their everyday life that suggest to them that there is a tradeoff between being high *g* and having other valuable traits.

An example
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A while ago, Nassim Taleb published the article [IQ is largely a pseudoscientific swindle](https://medium.com/incerto/iq-is-largely-a-pseudoscientific-swindle-f131c101ba39). In it, he makes a number of bad and misleading arguments against IQ tests, most of which I'm not going to address. But one argument stood out to me: He claims that IQ tests only tap into abilities that are suitable for academic problems, and that they in particular are much less effective when dealing with problems that have long tails of big losses and/or big gains.

Essentially, Taleb insists that *g* is useless "in the real world", especially for high-risk/high-reward situations. It is unsurprising that he would care a lot about this, because long tails are the main thing Taleb is known for.[^kzzpnx67ot]

In a way, it might seem intuitive that there's something to Taleb's claims about *g* \- there is, after all, [no free lunch](https://en.wikipedia.org/wiki/No_free_lunch_theorem) in intelligence, so it seems like any skill would require some sort of tradeoff, and ill-defined risks seem like a logical tradeoff for performance at well-defined tasks. However, the fundamental problem with this argument is that it's wrong. Nassim Taleb does not provide any evidence, but generally studies on IQ don't find g to worsen performance, and tend to find it to improve performance, including on complex, long tail-heavy tasks like [stock trading](https://www.sciencedirect.com/science/article/abs/pii/S0304405X1100211X).[^gpow7h98wt]

But what I've realized is that there might be a charitable interpretation for Taleb's argument. Specifically, we have good reason to believe that his claim is a reflection of his personal experience and observations in life. Let's take a look:

Who is Nassim Taleb?
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Nassim Taleb used stock trading methods that were particularly suited to long tail scenarios to become financially independent. With his bounty of free time, he's written several books about randomness and long tails. Clearly, he cares quite a lot about long-tailed distributions, for good reasons. But perhaps he cares too much - he is characteristically easy to anger, and he spends a lot of time complaining about people who don't accept his points about long tails.

Based on this, I would assume that he quite heavily selects for people who care about and understand long tails when it comes to the people he hangs around. This probably happens both actively, as he e.g. loudly blocks anyone who disagrees with him on Twitter, and probably also passively, because people who agree with him are going to be a lot more interested in associating with him than people who he blows up at.

But in addition to selecting for people who care about long tails, I would assume he also selects for smart people. This is a general finding; people tend to associate with people who are of similar intelligence to themselves. It also seems theoretically right; he's primarily known for "smart topics" like long tail probabilities, and his work tends to be about jobs that are mostly held by people in the upper end of the IQ range.

Simulating collider bias
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Selecting for both intelligence and black swan awareness exposes Taleb to collider bias: If you select for multiple variables, you tend to induce a negative correlation between the variables in your observations. This is because the individuals who are low in both tend to be excluded from your observations. Let's plot it hypothetically, on a simulation:

![](https://39669.cdn.cke-cs.com/rQvD3VnunXZu34m86e5f/images/e3ac3783c506ed7b129b3d8c609d566fdbadebe6f2a4c681.png)

Simulated data showing two weakly correlated Gaussian variables; IQ and black swan awareness. A subset of the points whose sum is high has been selected out as people who Taleb might be likely to hang out with. While the correlation is positive in the overall sample, it becomes negative within Taleb's experiences.

But if Taleb's personal experiences involve a negative correlation between IQ-like intelligence and black swan awareness/long tail handling ability, then it's no wonder he sees IQ as testing for skills that deal poorly with the long tails of the real world; that's literally just what he sees when he looks at people.

Generalizing
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Lots of people have something they value. Maybe it's emotional sensitivity, maybe it's progressive politics, maybe it's something else. Smart people presumably select for both the thing they value and for intelligence in the people they hang out with - so as a result, due to the collider, you should expect them to see a negative, or at least downwards-biased, correlation between the traits.

But it seems like this would create a huge bias against general intelligence! Whenever a smart person has to think about whether general intelligence is good, they will notice that it tends to be accompanied with some bad stuff. So they will see it as a tradeoff, often even for things that are positively correlated.

*Thanks to Justis Mills for proofreading and feedback.*

[^kzzpnx67ot]: See e.g. his books Fooled By Randomness or The Black Swan. 

[^gpow7h98wt]: The linked study looks at stock trading behavior during the dot com bubble. It finds that smarter people earned more money, were less likely to lose big, entered the market earlier, and stopped entering the market once it reached its peak. It also finds some other things; go read the study if you want to learn the details.