I agree that the data collection process wasn't ethical, and the professor should definitely be reprimanded for that. It's extremely sad that the coauthors were

I agree that the data collection process wasn't ethical, and the professor should definitely be reprimanded for that. It's extremely sad that the coauthors weren't aware of this as well. And I feel terrible for the undergrads: their first research experience was publically rebuked for no fault of their own. However, there is no shortage of projects with sketchy data collection methodologies on arXiv that haven't received this amount of attention. The point of putting stuff on arXiv _is_ that the paper will not pass / has not passed peer review in its current form! I might even call arXiv a safe space to publish ideas. We all benefit from this: a lot of interesting papers are only available on arxiv v.s. being shared between specific labs. I'm concerned that this fiasco was enabled by this new paradigm in AI social media reporting, where a project's findings are amplified and all the degrees of uncertainty are repressed. And I'm honestly not sure how to best deal with this other than either amplifying the uncertainty and jankyness in the paper itself to an annoyingly noticeable level, or just going back to the old way of privately sharing ideas. Maybe this is the best case scenario for these sorts of papers? They pushed a paper on a public journal, and got a public "peer review" of the paper. Turns out the community voted "strong reject;" and it also turns out that the stakes for public rejection are (uncomfortably, IMO) higher than for a normal rejection. Maybe this causes the researchers to only publically release better research, or (more likely) this causes the researchers to privately release all future papers.