yeah, i think the lack of a direct optimizer may matter. the question isn’t just whether evolution could be more efficient, but efficient at what.
this reminded me of a point from deutsch in deutsch files iv: he says ribosomes are the educational institutions of cells, and that their job is to pass on cellular knowledge as faithfully as evolution can make it. i might be misinterpreting, but that connection seemed relevant.
i take the lesson as: evolutionary processes don’t just favor more experimentation. some parts of the process can be selected to reduce variation and preserve a pattern accurately. that can be good if the pattern is already valuable, but it’s different from open-ended creativity.
so maybe there are several separate issues:
- how variants are generated
- how aggressively variants are pruned
- what gets preserved with high fidelity
- whether the process can make explanatory jumps instead of only local improvements
that makes me less inclined to treat more direct fitness measurement as automatically better. it might make some engineering searches more efficient relative to the metric, but it could also make the process narrower depending on what the measure rewards.