[Onawa]

I understand the point that you're making about overoptimizing for FOMO in science. I wanted to give you another perspective from a scientist working within the US government that doesn't care about playing that game.

Our governmental research agency, and NIH as a whole has TONS of research data that we don't have the manpower to screen and provess. There are also gaps in data that AI/ML could help us simulate. AI research assistants could potentially help us process and evaluate "what questions to ask" by, for example, looking for trends in QSAR (quantitative structure-activity relationship) models for novel chemicals and help us direct our attention to compounds of toxicological interest.

We've also been trying to use the AI research assistants to speed up the process of evaluating the scientific literature for toxicologists who have to make regulatory decisions. Our agency has a backlog of chemicals that we would love to evaluate, but lacks the manpower to do so.

No profit motive or much "clout" interest, at least that I've seen. Just a lot of public servant scientists who need some extra help protecting the public.