AFAIK in wet science you need (or needed) to do tons of experimentations with liquids with specific molar compositions and temperatures splurging in and out of test tubes - basically just physically navigating a search space. I would view an AI model with super powerful guestimation capability as a much faster way of A) cutting through search space B) providing accidental discoveries while at it

Now, if we look at history of science and technology, there is a shit ton of practical stuff that was found only by pure accident - discoveries of which could not be predicted from any previous theory.

I would view both A) and B) as net positives. But our teaching of the next generation of scientists needs to adapt.

The worst case scenario is of course that the middle management driven enshittification of science will proceed to a point where there are only few people who actually are scientists and not glorified accountants. But I’m optimistic this will actually super charge science.

With good luck we will get rid of the both of the biggest pathologies in modern science - 1. number of papers published and referred as a KPI 2. Hype driven super politicized funding where you can focus only one topic “because that’s what’s hot” (i.e. string theory).

The best possible outcome is we get excitement and creativity back into science. Plus level up our tech level in this century to something totally unforeseen (singularity? That’s just a word for “we don’t know what’s gonna happen” - not a specific concrete forecasted scenario).