Starting in 20 to 30 years the most important AGI precursor technology will be genetic engineering or some other technology for increasing human intelligence. Any long term estimate of our ability to create AGI has to take into account the strong possibility that the people writing the software and designing the hardware will be much, much smarter than currently exist, possibly 30 standard deviations above the human mean in intelligence.
possibly 30 standard deviations above the human mean in intelligence
So humans with IQ 550..., and 7.5 meters tall.
I don’t think that genetics work that way. Extraordinary claims require extraordinary evidence, not naive extrapolations from a binomial distribution model.
His Wikipedia page doesn’t seem particularly impressive.
Anyway, there are Nobel laureates who believe in homoeopathy and ESP, hence even if he was indeed a “leading expert on the genetics of intelligence”, his word alone, especially a blog post, doesn’t remotely look like enough evidence for such an extreme claim.
The best evidence would be if animal breeders can move targeted traits by at least 30 standard deviations. If they do, the 30 std IQ claim wouldn’t be extraordinary.
Even though cows are producing 23,000 pounds per year on average, some herds produce more than 30,000 per head—and he’s found exceptional animals that can produce between 45,000 and 50,000.
...”We learn new things about dairy cows almost every day,” Cook says. “I never thought I’d see cows producing 200 pounds of milk a day. That was beyond my ability to imagine 20 years ago.”
The graph indicates that the average output per cow in 1990 (24 years ago) was ~15,000 pounds per year. It’s unclear what the SD is, but given the peak mentioned of 50,000 pounds, an SD of 1000 pounds alone would imply breeding and other practices have shifted the cow population by an enormous amount over the very recent past.
This itself seem to be a huge improvement over a lot of places: http://www.dairymoos.com/how-much-milk-do-cows-give/ gives a graph of unknown source http://www.dairymoos.com/wp-content/uploads/2013/08/image.png which compares cross-nationally; the USA is not at the top for average pounds of milk for cows, but what’s interesting is contemporary Ethiopia has an entry indicating their cows are at 838 pounds. Ethiopia is a poor impoverished country with lots of traditional agriculture… so in other words, the normal human condition for most of history.
If we set an SD as 838 (the Ethiopian SD is surely smaller, but let’s go with it), then humanity has already improved cows by 17 SDs ((15000-838) / 838) and if we could get to the 50k some cows have performed at, then we would have improved milk yield by 58 SDs.
There are probably a lot of comparable examples for horse speed, hog size, beef growing speed, etc, but I’m not an agriculture expert so this is just one I remember running into focusing on the incredible gains made in recent times.
I don’t know, but if we can see easily >58SDs from a combination of carefully engineered environment and centuries of breeding… And I don’t know how much of that is simply being fed nutrient-rich feed, given the doubling of productivity over the past 2 decades, unless dairy farmers only then realized ‘oh, we should feed cows more!’, which seems unlikely.
That said, even just breeding is now old-fashioned; these days, the cutting edge in cow tech is using genotyping + phenotype data to more accurately estimate ‘lifetime net merit’ and pick animals to breed (a form of molecular breeding).
Hsu links a review paper70305-4/fulltext “‘Reliability of genomic predictions for North American Holstein bulls’, VanRaden et al 2009”) on the topic which discusses the usefulness of genetic prediction using cheap small SNP chips and how well it fits the highly-polygenic non-fixed model (which would imply that there’s still a very long way to go before gains from breeding disappear):
Marker effects for most other traits were evenly distributed across all chromosomes with only a few regions having larger effects, which may explain why the infinitesimal model and standard quantitative genetic theories have worked well. The distribution of marker effects indicates primarily polygenic rather than simple inheritance and suggests that the favorable alleles will not become homozygous quickly, and genetic variation will remain even after intense selection. Thus, dairy cattle breeders may expect genetic progress to continue for many generations.
Nonlinear and linear predictions were correlated by >0.99 for most traits. The nonlinear genomic model had little advantage in R2 over the linear model except for fat and protein percentages with increases of 8 and 7%, respectively (Table 2). Gains in R2 averaged 3% with simulated data (VanRaden, 2008) but generally were smaller with real data, which indicated that most traits are influenced by more loci than the 100 QTL used in simulation. The R2 improved when the prior assumption was that all markers have some effect rather than that most have no effect.
If I understand correctly, the inheritability of a trait often increases with a decrease of environmental variability.
In this study they are comparing cattle raised in modern times in a developed country (the Netherlands, I think), hence the environment was likely about optimal, and unsurprising most of the observed phenotypic variation had a genetic origin. Ethiopian subsistence farmers probably don’t have access to cheap soy and corn and have their cows graze on marginal lands, therefore nutrient availability is likely the limiting factor in their milk production. Similar patterns can be found in traits like human stature and IQ, which are more inheritable in developed countries rather than in third-world countries, and are subject to quick bursts when a country becomes more developed.
Also, in the modern dairy industry, cows are slaughtered around the age four and sold for beef, while in subsistence farming they are likely to be kept for many years past peak milk production, resulting in lower lifetime averages.
As for the specific of the inheritability of a continuous trait, I’m not an expert of genetics, but it seems to me that a polygenic model makes intuitive sense, as was quantitatively confirmed by this study. They found that a non-linear model predicts the data better than a linear model, which is however quite good, and again I don’t find this particularly surprising since linear approximations often perform well on sufficiently smooth functions, especially in the neighbourhood of a stationary point (where you can expect the genotypes of a relatively stable population to be, approximately).
My problem with Hsu line of argument is that he extrapolates predictions of these kinds of linear models way past observed phenotypes, which is something that has no theoretical basis, especially given that non-linear effects (logarithmic and logistic responses, square-cube effects, etc.) are ubiquitous in biology.
If I understand correctly, the inheritability of a trait often increases with a decrease of environmental variability.
Yes. (More relevantly, I’d say that as the environment gets better, the heritability will increase.)
Overall, your points about the Ethiopian cows are correct but I don’t think they would account for more than a relatively small chunk of the difference between the best American milk cows and regular Ethiopian milk cows. It really does look to me like humanity has pushed milk capacity dozens of standard deviations past where it would have been even centuries ago.
They found that a non-linear model predicts the data better than a linear model, which is however quite good, and again I don’t find this particularly surprising since linear approximations often perform well on sufficiently smooth functions, especially in the neighbourhood of a stationary point (where you can expect the genotypes of a relatively stable population to be, approximately).
Not surprising no, but people have seriously argued to me that things like embryo selection will not work well or at all because it’s possible important stuff will be due to nonlinear genetic interactions (most recently on Google+, but I’ve seen it elsewhere). So it’s something that apparently needs to be established.
My problem with Hsu line of argument is that he extrapolates predictions of these kinds of linear models way past observed phenotypes, which is something that has no theoretical basis, especially given that non-linear effects
I’m not sure how seriously Hsu takes the 30SD part as translating to underlying intelligence; the issue of SDs/normal ordinal distribution of intelligence in the population vs a hypothetical underlying cardinal scale of intelligence (http://lesswrong.com/lw/kcs/what_resources_have_increasing_marginal_utility/b0qb) is not really easy to come down to a hard conclusion except to note that in some areas AI progress curves spend a while in the human range but often go steadily beyond (eg computer chess), which suggests to me that large difference in human intelligence rankings do translate to fairly meaningful (albeit not huge) absolute intelligence differences, in which case the 30SDs might translate to a lot of real intelligence and not some trivial-but-statistically-measurable improvements in how fast they can do crosswords or something.
I think probably the best response here is to take it as saying that the lower limit will be extremely high and equivalent to the top observed phenotype, like a von Neumann. Since right now estimates of IVF sperm donor usage in the USA suggest something like 30-60k kids a year are born that way*, if the fertility doctors dropped in an iterated embryo selection procedure before implantation. I think 30-60k geniuses would make a major difference to society**, and if they happened to be even smarter than the previous top observed phenotypes...?
* I use this figure because looking into the matter, I don’t think many women who could bear kids normally would willing sign up for IVF just to get the benefits of embryo selection. It’s much too painful, inconvenient, and signals the wrong values. But women who have to do IVF if they ever want to have a kid would be much more likely to make use of it.
** to put 30-60k in perspective, the USA has around 4m babies a year, so ignoring demographics, the top 1% (roughly MENSA level, below-average for LW, well below average for cutting-edge research) of babies represents 40k. If all the IVFers used embryo selection and it boosted the IVF babies to an average of just 130, well below genius, it’d practically single-handedly double the 1%ers.
The most extreme example I’m aware of is the size of dogs: a chihuahua is about 4.3 times smaller than a gray wolf in terms of shoulder height, 4 stds of the wolf height. Increasing size seems much more difficult than decreasing it, as the tallest dogs, great danes, are in the same range of wolves. Some breeds of dogs are shorter and more massive than wolves, but not by much.
Other domesticated species, AFAIK, show much less variance.
Starting in 20 to 30 years the most important AGI precursor technology will be genetic engineering or some other technology for increasing human intelligence. Any long term estimate of our ability to create AGI has to take into account the strong possibility that the people writing the software and designing the hardware will be much, much smarter than currently exist, possibly 30 standard deviations above the human mean in intelligence.
So humans with IQ 550..., and 7.5 meters tall.
I don’t think that genetics work that way. Extraordinary claims require extraordinary evidence, not naive extrapolations from a binomial distribution model.
The 30 std link is to a blog of one of the world’s leading experts on the genetics of intelligence.
His Wikipedia page doesn’t seem particularly impressive.
Anyway, there are Nobel laureates who believe in homoeopathy and ESP, hence even if he was indeed a “leading expert on the genetics of intelligence”, his word alone, especially a blog post, doesn’t remotely look like enough evidence for such an extreme claim.
The best evidence would be if animal breeders can move targeted traits by at least 30 standard deviations. If they do, the 30 std IQ claim wouldn’t be extraordinary.
Hsu has oft cited the example of oil content of plants. Another interesting example is breeding cows for milk: http://www.washingtonpost.com/blogs/wonkblog/wp/2014/02/17/cows-are-incredible-they-might-just-keep-producing-more-milk-forever/
The graph indicates that the average output per cow in 1990 (24 years ago) was ~15,000 pounds per year. It’s unclear what the SD is, but given the peak mentioned of 50,000 pounds, an SD of 1000 pounds alone would imply breeding and other practices have shifted the cow population by an enormous amount over the very recent past.
This itself seem to be a huge improvement over a lot of places: http://www.dairymoos.com/how-much-milk-do-cows-give/ gives a graph of unknown source http://www.dairymoos.com/wp-content/uploads/2013/08/image.png which compares cross-nationally; the USA is not at the top for average pounds of milk for cows, but what’s interesting is contemporary Ethiopia has an entry indicating their cows are at 838 pounds. Ethiopia is a poor impoverished country with lots of traditional agriculture… so in other words, the normal human condition for most of history.
If we set an SD as 838 (the Ethiopian SD is surely smaller, but let’s go with it), then humanity has already improved cows by 17 SDs (
(15000-838) / 838) and if we could get to the 50k some cows have performed at, then we would have improved milk yield by 58 SDs.There are probably a lot of comparable examples for horse speed, hog size, beef growing speed, etc, but I’m not an agriculture expert so this is just one I remember running into focusing on the incredible gains made in recent times.
How much of that gain is genetic?
If I understand correctly, cows in developed countries are feed nutrient-rich feed, such as soy and corn.
I don’t know, but if we can see easily >58SDs from a combination of carefully engineered environment and centuries of breeding… And I don’t know how much of that is simply being fed nutrient-rich feed, given the doubling of productivity over the past 2 decades, unless dairy farmers only then realized ‘oh, we should feed cows more!’, which seems unlikely.
That said, even just breeding is now old-fashioned; these days, the cutting edge in cow tech is using genotyping + phenotype data to more accurately estimate ‘lifetime net merit’ and pick animals to breed (a form of molecular breeding).
Hsu links a review paper70305-4/fulltext “‘Reliability of genomic predictions for North American Holstein bulls’, VanRaden et al 2009”) on the topic which discusses the usefulness of genetic prediction using cheap small SNP chips and how well it fits the highly-polygenic non-fixed model (which would imply that there’s still a very long way to go before gains from breeding disappear):
Thanks for the link.
If I understand correctly, the inheritability of a trait often increases with a decrease of environmental variability.
In this study they are comparing cattle raised in modern times in a developed country (the Netherlands, I think), hence the environment was likely about optimal, and unsurprising most of the observed phenotypic variation had a genetic origin.
Ethiopian subsistence farmers probably don’t have access to cheap soy and corn and have their cows graze on marginal lands, therefore nutrient availability is likely the limiting factor in their milk production.
Similar patterns can be found in traits like human stature and IQ, which are more inheritable in developed countries rather than in third-world countries, and are subject to quick bursts when a country becomes more developed.
Also, in the modern dairy industry, cows are slaughtered around the age four and sold for beef, while in subsistence farming they are likely to be kept for many years past peak milk production, resulting in lower lifetime averages.
As for the specific of the inheritability of a continuous trait, I’m not an expert of genetics, but it seems to me that a polygenic model makes intuitive sense, as was quantitatively confirmed by this study.
They found that a non-linear model predicts the data better than a linear model, which is however quite good, and again I don’t find this particularly surprising since linear approximations often perform well on sufficiently smooth functions, especially in the neighbourhood of a stationary point (where you can expect the genotypes of a relatively stable population to be, approximately).
My problem with Hsu line of argument is that he extrapolates predictions of these kinds of linear models way past observed phenotypes, which is something that has no theoretical basis, especially given that non-linear effects (logarithmic and logistic responses, square-cube effects, etc.) are ubiquitous in biology.
Yes. (More relevantly, I’d say that as the environment gets better, the heritability will increase.)
Overall, your points about the Ethiopian cows are correct but I don’t think they would account for more than a relatively small chunk of the difference between the best American milk cows and regular Ethiopian milk cows. It really does look to me like humanity has pushed milk capacity dozens of standard deviations past where it would have been even centuries ago.
Not surprising no, but people have seriously argued to me that things like embryo selection will not work well or at all because it’s possible important stuff will be due to nonlinear genetic interactions (most recently on Google+, but I’ve seen it elsewhere). So it’s something that apparently needs to be established.
I’m not sure how seriously Hsu takes the 30SD part as translating to underlying intelligence; the issue of SDs/normal ordinal distribution of intelligence in the population vs a hypothetical underlying cardinal scale of intelligence (http://lesswrong.com/lw/kcs/what_resources_have_increasing_marginal_utility/b0qb) is not really easy to come down to a hard conclusion except to note that in some areas AI progress curves spend a while in the human range but often go steadily beyond (eg computer chess), which suggests to me that large difference in human intelligence rankings do translate to fairly meaningful (albeit not huge) absolute intelligence differences, in which case the 30SDs might translate to a lot of real intelligence and not some trivial-but-statistically-measurable improvements in how fast they can do crosswords or something.
I think probably the best response here is to take it as saying that the lower limit will be extremely high and equivalent to the top observed phenotype, like a von Neumann. Since right now estimates of IVF sperm donor usage in the USA suggest something like 30-60k kids a year are born that way*, if the fertility doctors dropped in an iterated embryo selection procedure before implantation. I think 30-60k geniuses would make a major difference to society**, and if they happened to be even smarter than the previous top observed phenotypes...?
* I use this figure because looking into the matter, I don’t think many women who could bear kids normally would willing sign up for IVF just to get the benefits of embryo selection. It’s much too painful, inconvenient, and signals the wrong values. But women who have to do IVF if they ever want to have a kid would be much more likely to make use of it.
** to put 30-60k in perspective, the USA has around 4m babies a year, so ignoring demographics, the top 1% (roughly MENSA level, below-average for LW, well below average for cutting-edge research) of babies represents 40k. If all the IVFers used embryo selection and it boosted the IVF babies to an average of just 130, well below genius, it’d practically single-handedly double the 1%ers.
The most extreme example I’m aware of is the size of dogs:
a chihuahua is about 4.3 times smaller than a gray wolf in terms of shoulder height, 4 stds of the wolf height. Increasing size seems much more difficult than decreasing it, as the tallest dogs, great danes, are in the same range of wolves.
Some breeds of dogs are shorter and more massive than wolves, but not by much.
Other domesticated species, AFAIK, show much less variance.