One data point that’s highly relevant to this conversation is that, at least in Europe, intelligence has undergone quite significant selection in just the last 9000 years. As measured in a modern environment, average IQ went from ~70 to ~100 over that time period (the Y axis here is standard deviations on a polygenic score for IQ)
I don’t have time to read the book “Innate”, so please let me know if there are compelling arguments I am missing, but based on what I know the “IQ-increasing variants have been exhausted” hypothesis seems pretty unlikely to be true.
There’s well over a thousand IQ points worth of variants in the human gene pool, which is not what you would expect to see if nature had exhaustively selected for all IQ increasing variants.
Unlike traits that haven’t been heavily optimized (like resistance to modern diseases)
Wait, resistance to modern diseases is actually the single most heavily selected for thing in the last ten thousand years. There is very strong evidence of recent selection for immune system function in humans, particularly in the period following domestication of animals.
Like there has been so much selection for human immune function that you literally see higher read errors in genetic sequencing readouts in regions like the major histocompatibility complex (there’s literally that much diversity!)
but suggests the challenge may be greater than statistical models indicate, and might require understanding developmental pathways at a deeper level than just identifying associated variants.
If I have one takeaway from the last ten years of deep learning, it’s that you don’t have to have a mechanistic understanding of how your model is solving a problem to be able to improve performance. This notion that you need a deep mechanical understanding of how genetic circuits operate or something is just not true.
What you actually need to do genetic engineering is a giant dataset and a means of editing.
Statistical methods like finemapping and adjusting for population level linkage disequilibrium help, but they’re just making your gene editing more efficient by doing a better job of identifying causal variants. They don’t take it from “not working” to “working”.
Also if we look at things like horizontal gene transfer & shifting balance theory we can see these as general ways to discover hidden genetic variants in optimisation and this just feels highly non-trivial to me? Like competing against evolution for optimal information encoding just seems really difficult apriori? (Not a geneticist so I might be completely wrong here!)
Horizontal gene transfer doesn’t happen in humans. That’s mostly something bacteria do.
There IS weird stuff in humans like viral DNA getting incorporated into the genome, (I’ve seen estimates that about 10% of the human genome is composed of this stuff!) but this isn’t particularly common and the viruses often accrue mutations over time that prevents them from activating or doing anything besides just acting like junk DNA.
Occasionally these viral genes become useful and get selected on (I think the most famous example of this is some ancient viral genes that play a role in placental development), but this is just a weird quirk of our history. It’s not like we’re prevented from figuring out the role of these genes in future outcomes just because they came from bacteria.
One data point that’s highly relevant to this conversation is that, at least in Europe, intelligence has undergone quite significant selection in just the last 9000 years. As measured in a modern environment, average IQ went from ~70 to ~100 over that time period (the Y axis here is standard deviations on a polygenic score for IQ)
The above graph is from David Reich’s paper
I don’t have time to read the book “Innate”, so please let me know if there are compelling arguments I am missing, but based on what I know the “IQ-increasing variants have been exhausted” hypothesis seems pretty unlikely to be true.
There’s well over a thousand IQ points worth of variants in the human gene pool, which is not what you would expect to see if nature had exhaustively selected for all IQ increasing variants.
Wait, resistance to modern diseases is actually the single most heavily selected for thing in the last ten thousand years. There is very strong evidence of recent selection for immune system function in humans, particularly in the period following domestication of animals.
Like there has been so much selection for human immune function that you literally see higher read errors in genetic sequencing readouts in regions like the major histocompatibility complex (there’s literally that much diversity!)
If I have one takeaway from the last ten years of deep learning, it’s that you don’t have to have a mechanistic understanding of how your model is solving a problem to be able to improve performance. This notion that you need a deep mechanical understanding of how genetic circuits operate or something is just not true.
What you actually need to do genetic engineering is a giant dataset and a means of editing.
Statistical methods like finemapping and adjusting for population level linkage disequilibrium help, but they’re just making your gene editing more efficient by doing a better job of identifying causal variants. They don’t take it from “not working” to “working”.
Horizontal gene transfer doesn’t happen in humans. That’s mostly something bacteria do.
There IS weird stuff in humans like viral DNA getting incorporated into the genome, (I’ve seen estimates that about 10% of the human genome is composed of this stuff!) but this isn’t particularly common and the viruses often accrue mutations over time that prevents them from activating or doing anything besides just acting like junk DNA.
Occasionally these viral genes become useful and get selected on (I think the most famous example of this is some ancient viral genes that play a role in placental development), but this is just a weird quirk of our history. It’s not like we’re prevented from figuring out the role of these genes in future outcomes just because they came from bacteria.