When you now get a lot of mutations that increase brain size, while this contributes to smartness, this also pulls you away from the species median, so the hyperparameters are likely to become less well tuned, resulting in a countereffect that also makes you dumber in some ways.
Actually maybe the effect I am describing is relatively small as long as the variation in brain size is within 2 SDs or so, which is where most of the data pinning down the 0.3 correlation comes from.
So yeah it’s plausible to me that your method of estimating is ok.
Intuitively I had thought that chimps are just much dumber than humans. And sure if you take −4SD humans they aren’t really able to do anything, but they don’t really count.
I thought it’s sorta in this direction but not quite as extreme:
(This picture is actually silly because the distance to “Mouse” should be even much bigger. The point is that chimps might be far outside the human distribution.)
But perhaps chimps are actually closer to humans than I thought.
(When I in the following compare different species with standard deviations, I don’t actually mean standard deviations, but more like “how many times the difference between a +0SD and a +1SD human”, since extremely high and very low standard deviation measures mostly cease to me meaningful for what was actually supposed to be measured.)
I still think −4.4SD is overestimating chimp intelligence. I don’t know enough about chimps, but I guess they might be somewhere between −12SD and −6SD (compared to my previous intuition, which might’ve been more like −20SD). And yes, considering that the gap in cortical neuron count between chimps and humans is like 3.5x, and it’s even larger for the prefrontal cortex, and that algorithmic efficiency is probably “orca < chimp < human”, then +6SDs for orcas seem a lot less likely than I initially intuitively thought, though orcas would still likely be a bit smarter than humans (on the way my priors would fall out (not really after updating on observations about orcas)).
Actually maybe the effect I am describing is relatively small as long as the variation in brain size is within 2 SDs or so, which is where most of the data pinning down the 0.3 correlation comes from.
So yeah it’s plausible to me that your method of estimating is ok.
Intuitively I had thought that chimps are just much dumber than humans. And sure if you take −4SD humans they aren’t really able to do anything, but they don’t really count.
I thought it’s sorta in this direction but not quite as extreme:
(This picture is actually silly because the distance to “Mouse” should be even much bigger. The point is that chimps might be far outside the human distribution.)
But perhaps chimps are actually closer to humans than I thought.
(When I in the following compare different species with standard deviations, I don’t actually mean standard deviations, but more like “how many times the difference between a +0SD and a +1SD human”, since extremely high and very low standard deviation measures mostly cease to me meaningful for what was actually supposed to be measured.)
I still think −4.4SD is overestimating chimp intelligence. I don’t know enough about chimps, but I guess they might be somewhere between −12SD and −6SD (compared to my previous intuition, which might’ve been more like −20SD). And yes, considering that the gap in cortical neuron count between chimps and humans is like 3.5x, and it’s even larger for the prefrontal cortex, and that algorithmic efficiency is probably “orca < chimp < human”, then +6SDs for orcas seem a lot less likely than I initially intuitively thought, though orcas would still likely be a bit smarter than humans (on the way my priors would fall out (not really after updating on observations about orcas)).