The relationship of IQ to scientific achievement might be a step function.
I wonder about this. Isn’t it the case [translation: I’m sure I read in some general-audience psychology book once] that for just about every human activity, scientific research included, there’s a certain level above which differences in intelligence, at least in the sense of what intelligence tests measure, seem to have very little correlation with differences in effectiveness?
The mechanism is likely to be that a smarter researcher sees solutions intuitively, whereas a dumber one has to try lots of things that don’t work before getting to the correct solution; this would produce super linear speedup I think, because as you get smarter you avoid more and more wasted effort. There’s also the issue of status producing more motivation, which produces more achievement, which produces more status. This adds a significant nonlinearity.
Miscommunication. My point was only that I expect the function that describes the relationship to be a smooth curve. I wouldn’t be too surprised if the relationship between IQ and research productivity is stronger at the high end than in the middle.
Sounds unlikely to me too, but it could explain the phenomenon underlying glm’s quote (that above a certain threshold intelligence doesn’t make much of a difference in “effectiveness”), assuming that the result is valid (which I would want to know how “effectiveness” was measured).
Your question about how they measured “effectiveness” is right on.
My guess is that marginal benefits to IQ depend on the task, and the IQ range. For tasks of medium difficulty, the marginal benefits of IQ will probably increase as one goes from the low-IQ to average, flatten out and then decrease as one gets to a very high range. But higher IQ allows you to efficiently attempt more much more difficult (and arguably important) tasks.
Human ability generally seems to be power-law distributed—the “80-20” rule often hold in research. I’m just checking out Murray’s “Human Accomplishment”, and this is the impression I get from his data—whether it is valid data remains to be seen. But this might have many other causes, from Matthew effects where widely cited people become even more cited (and maybe get great research environments) to multiplicator effects where productivity is due to multiplicative effects of more or less random factors—only a few gets a lot of them, and the result is a lognormal distribution.
IQ, as ability to make rational inferences in new domains, may be just one of these factors. Low IQ certainly precludes much scientific achievement. There are also selection effects where getting into the right schools or professions require overcoming IQ-loaded hurdles. The real benefits of IQ among geniuses might be smaller than other factors—but having more people with high IQ will certainly not decrease the pool of potential geniuses.
The relationship of IQ to scientific achievement might be a step function.
I am curious about how this was measured.
What sort of mechanism would produce a step function? Sounds highly unlikely to me.
Added: I would expect the curve to be smooth.
The mechanism is likely to be that a smarter researcher sees solutions intuitively, whereas a dumber one has to try lots of things that don’t work before getting to the correct solution; this would produce super linear speedup I think, because as you get smarter you avoid more and more wasted effort. There’s also the issue of status producing more motivation, which produces more achievement, which produces more status. This adds a significant nonlinearity.
Miscommunication. My point was only that I expect the function that describes the relationship to be a smooth curve. I wouldn’t be too surprised if the relationship between IQ and research productivity is stronger at the high end than in the middle.
Sounds unlikely to me too, but it could explain the phenomenon underlying glm’s quote (that above a certain threshold intelligence doesn’t make much of a difference in “effectiveness”), assuming that the result is valid (which I would want to know how “effectiveness” was measured).
Your question about how they measured “effectiveness” is right on.
My guess is that marginal benefits to IQ depend on the task, and the IQ range. For tasks of medium difficulty, the marginal benefits of IQ will probably increase as one goes from the low-IQ to average, flatten out and then decrease as one gets to a very high range. But higher IQ allows you to efficiently attempt more much more difficult (and arguably important) tasks.
My guess is that it is superlinear. Look at, e.g. Von Neumann.
Human ability generally seems to be power-law distributed—the “80-20” rule often hold in research. I’m just checking out Murray’s “Human Accomplishment”, and this is the impression I get from his data—whether it is valid data remains to be seen. But this might have many other causes, from Matthew effects where widely cited people become even more cited (and maybe get great research environments) to multiplicator effects where productivity is due to multiplicative effects of more or less random factors—only a few gets a lot of them, and the result is a lognormal distribution.
IQ, as ability to make rational inferences in new domains, may be just one of these factors. Low IQ certainly precludes much scientific achievement. There are also selection effects where getting into the right schools or professions require overcoming IQ-loaded hurdles. The real benefits of IQ among geniuses might be smaller than other factors—but having more people with high IQ will certainly not decrease the pool of potential geniuses.