Written by: Stephen Hsu
Primary Source: Information Processing
Readers might be interested in this interview I did, which is on the MIRI (Machine Intelligence Research Institute, in Berkeley) website. Some excerpts below.
… I think there is good evidence that existing genetic variants in the human population (i.e., alleles affecting intelligence that are found today in the collective world population, but not necessarily in a single person) can be combined to produce a phenotype which is far beyond anything yet seen in human history. This would not surprise an animal or plant breeder — experiments on corn, cows, chickens, drosophila, etc. have shifted population means by many standard deviations (e.g., +30 SD in the case of corn).
… I think we already have some hints in this direction. Take the case of John von Neumann, widely regarded as one of the greatest intellects in the 20th century, and a famous polymath. He made fundamental contributions in mathematics, physics, nuclear weapons research, computer architecture, game theory and automata theory.
In addition to his abstract reasoning ability, von Neumann had formidable powers of mental calculation and a photographic memory. In my opinion, genotypes exist that correspond to phenotypes as far beyond von Neumann as he was beyond a normal human.
I have known a great many intelligent people in my life. I knew Planck, von Laue and Heisenberg. Paul Dirac was my brother in law; Leo Szilard and Edward Teller have been among my closest friends; and Albert Einstein was a good friend, too. But none of them had a mind as quick and acute as Jansci [John] von Neumann. I have often remarked this in the presence of those men and no one ever disputed me. – Nobel Laureate Eugene Wigner
You know, Herb, how much faster I am in thinking than you are. That is how much faster von Neumann is compared to me. – Nobel Laureate Enrico Fermi to his former PhD student Herb Anderson.
One of his remarkable abilities was his power of absolute recall. As far as I could tell, von Neumann was able on once reading a book or article to quote it back verbatim; moreover, he could do it years later without hesitation. He could also translate it at no diminution in speed from its original language into English. On one occasion I tested his ability by asking him to tell me how The Tale of Two Cities started. Whereupon, without any pause, he immediately began to recite the first chapter and continued until asked to stop after about ten or fifteen minutes. – Herman Goldstine, mathematician and computer pioneer.
I always thought Von Neumann’s brain indicated that he was from another species, an evolution beyond man. – Nobel Laureate Hans A. Bethe.
The quantitative argument for why there are many SD’s to be had from tuning genotypes is so simple that I’ll summarize it here (see also, e.g., here or here). Suppose variation in cognitive ability is
- highly polygenic (i.e., controlled by N loci, where N is large; N is almost certainly more than 1k — perhaps roughly 10k), and
- approximately linear (note the additive heritability of g is larger than the non-additive part).
Then the population SD for the trait corresponds to an excess of roughly Sqrt(N) positive alleles. A genius like vN might be +6 SD, so would have roughly 6 Sqrt(N) more positive alleles than the average person (e.g., 200 extra positive alleles if N = 1000). But there are roughly +Sqrt(N) SDs in phenotype to be had by an individual who has essentially all of the N positive alleles. As long as Sqrt(N) >> 6, there is ample extant variation for selection to act on to produce a type superior to any that has existed before. (The probability of producing a “maximal type” through random breeding is ~ exp( – N), and for large N the historical human population is insufficient to have made this likely.)
This basic calculation underlies the work of animal and plant breeders, who have in many cases (corn, drosophila, cows, dogs) moved the “wild type” population by many SD through selection. See, e.g., this essay by famed geneticist James Crow of Wisconsin.
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- MSU Research Update (video) - April 17, 2019
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