Christian Meesters

@tomkalei ah, yes.

I was trying to make a point about AI usage in general. And the impact on a culture of insufficient scepticism. (Or rather on a publish-or-perish culture where a prezi presentation has more impact that paper with equations: It is a long-established fact, that in bio* papers with equations are cited less often than other papers. And I witnessed a prezi presentation which gave a mathematically illiterate person a professorship.)

Speaking about LLMs I could rant about vibe coding in bioinformatics. Brings us plenty of slop applications. Yet, just lately I attended a symposium in medicine. There just is some overlap of what I do.

Anyway, it was AI here and AI there. Not only are people doing diagnostic predictions with their models (where back in my day, work was slower and with plenty of pitfalls, we were doing things analytically - which means, in the end we could interpret why which weights are associated with which term if we were lucky. Not so any more.) Also, LLMs are heavy in use in that sector: particularly with the hope of easing work in the clinical sector.

What really bothers me: it seems as from conceptualization to paper LLMs are all over the place. Already >> 80 % of all biomedical papers are written with the help of LLMs. This already is debatable.

Also, yes, people ignore "the maths" and resort to an LLM instead.

@tomkalei
Or better: parts of biology are already there....

@tomkalei
A Nobel prize has already been awarded for the prediction of protein structures. At no time it was perfect nor did we learn anything from it regarding the nature of the problem.

And people were cheering nevertheless.

Where in the past careers were built upon crystallization projects or similar endeavours in NMR or EM, now people turn to AI. Yes, this has been tremendous progress. And we made progress since the prize. And yet, striving for verification became harder.

Which means the risk of faulty conclusions is ever increasing.

In other words: biologists are already there... and nobody seems to be bothered.

Well, I do not have much Twitter experience. Jumped on that ship, just before it was sunk.

But I get it: "Science-Twitter was so much better!"

Yes, yes. Now, there are Threads, Bluesky, LinkedIn, ...., and the chaotic Fediverse. People are realizing the inevitable: Less activity here, in the Fediverse. This happens, when people follow the herd. Whether the grass is really greener elsewhere remains to be seen, though.

Yesterday, I learned that an organization I am affiliated with is posting on #LinkedIn . Presumably for better reach. 🙄

It is true: People will not sign up for a mastodon server, just because it's there. In scicomm we have to choose: Where is my audience? How can I reach it?

So much, so trivial. We also have the option to shape that outcome. By not only posting on enshittified media, by using fediwalls or mastowall (which allow accountless views), by choosing which QR-codes to share, by forgoing ai slop images, etc. etc. etc.

1/n

#scicomm #fediverse #academicchatter