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Researcher with public evidence across AI research, Policy & governance, Culture, work & education.
Arxiv is limiting paper submissions to two per **submitter** (not per author) per month. Corrected link from the post below: blog.arxiv.org/2026/10/01/u...
arXiv has received a 17.2 million investment from three leading philanthropic organizations. Thank you to Simons Foundation International, Siegel Family Endowment, and XTX Markets for your support of arXiv! Read more: blog.arxiv.org/2026/09/23/arxiv-receives-multiyear-investment/
Earlier this month, we hosted a working group to think about how the TCS community should respond to AI progress. Their report, released on Monday, highlights 12 near-term actions that received broad support among the participants. simons.berkeley.edu/news-publica...
Here is one study, there are others too, which are pretty easy to find. Thakkar et al., "A large-scale randomized study of large language model feedback in peer review" (Nature Machine Intelligence 2026). www.nature.com/articles/s42...
Here is one study, there are others too, which are pretty easy to find. Thakkar et al., "A large-scale randomized study of large language model feedback in peer review" (Nature Machine Intelligence 2026). www.nature.com/articles/s42...
Here is one study, there are others too, which are pretty easy to find. Thakkar et al., "A large-scale randomized study of large language model feedback in peer review" (Nature Machine Intelligence 2026). www.nature.com/articles/s42...
Here is one study, there are others too, which are pretty easy to find. Thakkar et al., "A large-scale randomized study of large language model feedback in peer review" (Nature Machine Intelligence 2026). www.nature.com/articles/s42...
Here is one study, there are others too, which are pretty easy to find. Thakkar et al., "A large-scale randomized study of large language model feedback in peer review" (Nature Machine Intelligence 2026). www.nature.com/articles/s42...
Here is one study, there are others too, which are pretty easy to find. Thakkar et al., "A large-scale randomized study of large language model feedback in peer review" (Nature Machine Intelligence 2026). www.nature.com/articles/s42...
Here is one study, there are others too, which are pretty easy to find. Thakkar et al., "A large-scale randomized study of large language model feedback in peer review" (Nature Machine Intelligence 2026). www.nature.com/articles/s42...
Here is one study, there are others too, which are pretty easy to find. Thakkar et al., "A large-scale randomized study of large language model feedback in peer review" (Nature Machine Intelligence 2026). www.nature.com/articles/s42...
Here is one study, there are others too, which are pretty easy to find. Thakkar et al., "A large-scale randomized study of large language model feedback in peer review" (Nature Machine Intelligence 2026). www.nature.com/articles/s42...
I'm spending the 2026-2027 academic year in Paris as a Professeur Invité at @ceparis-saclay.bsky.social (Center for Economics at ENS Paris-Saclay) and @dataiainstitute.bsky.social (DATAIA). I'm looking forward to new collaborations, especially in areas related to Economics of AI and CS+Law.
My AI-related follows on Bluesky are a Markov chain. I add people when they (re)post principled AI-related content. I remove them when they (re)post crazy stuff.
AI review policies seem to be written to prevent laziness, with little recognition that AI can enhance the way reviewers evaluate the paper including (a) checking appendix proofs, (b) detailed comparison to the literature, (c) evaluating examples to get more intuition, (d) explaining lazy writing.
It is unfortunate to see so many progressives on the wrong side of the AI debate. We do not need to protect jobs from AI (or any technology), we need an economy and society organized so that the benefits of AI (or any technology) enhance the lives of all people, not just the tech executives.
There is lots of noise in the AI debates. One thing those debates do not need is pejorative framing: labels like “AI slop” and “plagiarism machine” that invite dismissal before evaluation. Academics need to have higher standards.
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