@npub147fp2j606qpfysp38phhzvempt7ewsdqwm6uww9uycp6tdvavu0s5paq44@momostr.pink

Post #1331533

2026-04-03 16:39 UTC

(hello from Nostr) -- Thanks, this gets at a lot of important issues. One I think about a lot as an "applied" scientist is the question of, what is science "for"? In the example in the essay of astrophysics, the author rightly points out that the work has no intrinsic economic value or ability to improve the human condition today... So for disciplines where (say) one's trying to cure cancer, or make nuclear fusion work, the question has to arise: isn't all of this "grunt work" indeed actually wasteful in terms of solving urgent problems needed by humanity? I mean "what to do with all the graduate students" is still a reasonable question even in this context... But I think this gets at the larger problems of the institutional context of academic research and graduate education, where I think AI is much more highlighting intrinsic pre-existing conditions than being some fundamentally disruptive force...

Replies (1)

@UlrikeHahn@fediscience.org 2026-04-03 19:29

@npub147fp2j606qpfysp38phhzvempt7ewsdqwm6uww9uycp6tdvavu0s5paq44 one way we have of thinking about this might be distinguishing between the things we feel, as scientists, we all needed to learn (e.g. design an experiment, programme an experiment, do the statistical analysis etc.) but don’t feel we need to do ourselves all the time in later projects and the level of involvement that is always required meaningful contributor to the project? “Bob” is a problem because he is never even meaningfully learning to do things. Likewise, the “senior” contributor who never gets stuck into any of the detail is probably also a bit of a problem

Open ##1331534