When I think of how I approach solving this problem in practice, I think of interfacing with structures within ML systems that satisfy an increasing list of desiderata for values, covering the rest with standard mech interp techniques, and then steering them with human preferences. I certainly think it’s probable that there are valuable insights to this process from neuroscience, but I don’t think a good solution to this problem (under the constraints I mention above) requires that it be general to the human brain as well. We steer the system with our preferences (and interfacing with internal objectives seems to avoid the usual problems with preferences) - while something that allows us to actually directly translate our values from our system to theirs would be great, I expect that constraint of generality to make it harder than necessary.
I think the seeds of an interdisciplinary agenda on this are already there, see e.g. https://manifund.org/projects/activation-vector-steering-with-bci, https://www.lesswrong.com/posts/GfZfDHZHCuYwrHGCd/without-fundamental-advances-misalignment-and-catastrophe?commentId=WLCcQS5Jc7NNDqWi5, https://www.lesswrong.com/posts/GfZfDHZHCuYwrHGCd/without-fundamental-advances-misalignment-and-catastrophe?commentId=D6NCcYF7Na5bpF5h5, https://www.lesswrong.com/posts/wr2SxQuRvcXeDBbNZ/bogdan-ionut-cirstea-s-shortform?commentId=A8muL55dYxR3tv5wp and maybe my other comments on this post.
I might have a shortform going into more details on this soon, ot at least by the time of https://foresight.org/2024-foresight-neurotech-bci-and-wbe-for-safe-ai-workshop/.