Academics Need to Wake Up on AI

kazinator•about 2 hours ago

Author doesn't seem to understand that LLM AI works by predicting tokens out of training data. The model writes a research summary because it digested academic papers and other sources in its training. When you say "AI can already do social science research better than most professors" that is false unless you mean the colloquial sense of "research" meaning "reading other people's existing stuff and paraphrasing it in my own words". But the AI doesn't even have "own words"; they are the training data's words.

If all scientists suddnenly do nothing all day but play with AI --- all research grinds to a halt!

lubujackson•28 minutes ago

Don't undersell AI - it also synthesizes and recombines those summaries in a purposeful way. Otherwise it couldn't product code that works in an existing codebase.

So it is able to process and act upon summaries and concepts. In other words, apply synthesis. What it can't do is understand what a useful result looks like without direction. So it could synthesize a billion pointless claims from source material, but we still need a human to know which ones matter (without a specialized framework to comprehend this). If you provide LLMs with an objective and source materials it is certainly capable of following threads of logic or building an argument backed by sources.

I understand the concerns about AI, but it is a powerful tool for discovery and synthesis.

in-silico•about 1 hour ago

This is true after pretraining, but reinforcement learning allows the model to discover strategies and ideas that weren't in its training corpus.

squidbeak•about 1 hour ago

What about Alphafold?

> But the AI doesn't even have "own words"; they are the training data's words.

If the AI understands those words, in what sense aren't they its 'own words'? Are you arguing that nothing but neologisms count?

kazinator•about 1 hour ago

I would say that I don't consider that to be an LLM.

jdlyga•about 2 hours ago

CS Academia tends to lag behind industry practices. The research frontier can be very cutting edge, but course curriculum, assignments, and institutional norms are slower and more conservative. That’s usually manageable when the shift is something like cloud adoption, new tooling, or a new dominant programming language. But this particular industry trend, use of AI in software development, is massive and fast moving (especially the agentic workflow growth over the last 6 months). And we're just now understanding where everything fits in and its limitations.

frozenseven•27 minutes ago

Journal articles are sometimes years behind. There are still papers coming out that use GPT-3.5 (!) for their main result. These days I'm basically only reading arXiv preprints (and whatever is trending on GitHub).

laughingcurve•about 2 hours ago

As an academic this article was a fantastic position piece. I loved this and enjoyed reading it even if I didn't agree 100% thank you for sharing

34ajHa•about 2 hours ago

"P.P.S. That is, entirely generated based on my artisanal, hand-crafted human social media posts and thoughts on the topic. So who wrote it, really? You tell me."

We can't since it is a vapid, unsourced, AI mania fueled piece that could have been written by AI.

I suppose the associate professor wants AI funding.

buffer_overlord•about 10 hours ago

and web's dead baby....web's dead.

dyauspitr•about 3 hours ago

Is this the new clickbait? AI written AI scare papers.

Academics Need to Wake Up on AI

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