Statistical Challenges with Making Super IQ babies
This is a critique of How to Make Superbabies on LessWrong. Disclaimer: I am not a geneticist[1], and I've tried to use as little jargon as possible. so I used the word mutation as a stand in for SNP (single nucleotide polymorphism, a common type of genetic variation). Background The Superbabies article has 3 sections, where they show: * Why: We should do this, because the effects of editing will be big * How: Explain how embryo editing could work, if academia was not mind killed (hampered by institutional constraints) * Other: like legal stuff and technical details. Here is a quick summary of the "why" part of the original article articles arguments, the rest is not relevant to understand my critique. 1. we can already make (slightly) superbabies selecting embryos with "good" mutations, but this does not scale as there are diminishing returns and almost no gain past "best of 40" 2. They show that when you edit, you don't have the issue outlined above, because each edit helps, here the only source of diminishing returns is that you of course pick the most important mutations first. 3. Then they switch from IQ to a disease focus by removing bad mutations. They also show that most diseases risk can be reduced 50-100% by 3-25 mutations, but if you swap from disease association to life expectancy, then 300 edits may only gain you 14 years, Interesting it only take 16 edits to get the first 5 years. 4. They show that there are less tradeoffs between mutations than one might initially anticipate, the correlations are mostly positive, ie, curing one disease might protect you from another one. 5. Then they use chicken becoming 4 times larger over 50 year, which is 40 standard deviation! to motivate the intuition that a specie can go fare out of equilibrium, using selective breeding, so selective editing should allow us to push even further. 6. Finally, they make theoretical curves for IQ gain and longevity, under the assumption that if we had more data, we
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