rw_eevee t1_isxukxi wrote on October 19, 2022 at 2:26 PM

Bigger problem for non-ML. It’s one thing to generate non-sense about Shakespeare or LGBTQ glaciology, it’s another to generate a even a bad ML paper complete with derivations, proofs, and experiments. And if a model can produce compelling ML papers, it should be allowed in on principle (though the experiments would be an issue, e.g., if the model completely fabricated the graphs reviewers won’t easily catch this. But this could be treated the same as a researcher fabricating data.)

TheLastVegan t1_isycgq5 wrote on October 19, 2022 at 4:27 PM

Writing gibberish is a coveted skill in politics because an unreadable proposal is harder to criticize, and any logical fallacy can be supported by semanticism to give the illusion of substance! In identity politics, writing fluff is necessary to signal cultural affiliation, which adds emotional weight to the gibberish in an essay. If a grad student needs to cite 20 puff pieces to get approved by their thesis supervisor, then they're going to need the manifold hypothesis either way! In the social sciences, structuring data to fit or obfuscate a sketchy narrative will generally be more lucrative than writing an unbiased analysis.