Why Do Journals Need New Models for AI Proofs?

Ankur Moitra wants new models that ease the load on journals and conferences, including a shared effort to verify AI proofs, while the older publishing models stay in place.

Journals and conferences were already overloaded with review work. Now someone has to review AI-generated papers, and some of them were important, but it is hard to get the community on board. OpenAI results have included improvements on the fast Fourier transform, and tweet streams have carried people improving the idea. He is not on Twitter and wants other ways to track the improvements and organize the ideas. A publication still goes out as the author's own draft: the author posts it on an archive, may add a new version or a third version, and the draft belongs to the author. The community does not add notes that an argument could run differently or more simply. The panelist is all for other models that allow crowdsourcing so understanding can evolve.

Research talks already separate the key idea from the messy technical work of dotting every i and crossing every t. The part worth explaining is the key idea and the special case that shows why the idea is powerful. Asked about Lemma 57, he does not remember it. Lean formalizations can be trusted for some of the technical building blocks, so the writing can put more emphasis on spreading the ideas.