All of Eric Hester's Comments + Replies

Excellent post. Could you expand further on your point:

“I think the AI (or perhaps Computer Science) research community is doing a great job (much better than in other areas) at innovating a lot on different peer review systems”

It would be interesting to see how things are done differently in these fields. Even a link to other resources would be great. Thanks.

1
PabloAMC
2y
Hey Eric, Thanks! I think that in AI conferences, organizers have played around with a few things: * Some conferences have a two-phase review system (AAAI) , others only one (NeurIPS). * Sometimes the chair might read and discard papers beforehand. * Reviews are sometimes published in OpenReview so that everyone can see them. * Referees are asked to provide confidence ratings in their assessments. Etcetera (see for example https://blog.ml.cmu.edu/2020/12/01/icml2020exp/). In Physics (my field) things look much lamer. To start with, we only publish in Journals, which might be ok, but means an ever-larger reviewing process length. Single-blind is still widely used. Sharing the code is fully optional (just say that you'll provide it upon reasonable request). And there are often just 2 (or even 1) referees, if you're lucky you may go up to 4. But the problem is the lack of assessment of the reviewing process: I don't think they are trying to make any efforts to improve it except to "look good" (open access stuff, maybe double-blind)... Since we do not conduct experiments or try to improve it, it stays behind I'd bet that in other sciences it is even worse: chemists and biologists are not even used to using arxiv equivalent. Social sciences... social sciences is unclear to me, but seems probably worse (p-value tweaking...). 😅