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Terence Tao (@tao@mathstodon.xyz)
mathstodon.xyzAttached: 2 images
As an experiment, I directed a coding agent to sort through recent #arXiv posts for similarity in topic or keywords to my own research papers, with additional weighting for papers authored by my former collaborators or mentees (such papers are marked with a star in the lists provided below). I also asked the agent to assess the degree of AI assistance in each paper using robot emojis, with one emoji denoting minor assistance, two denoting major assistance, and three denoting near-total automation. (A computer emoji is also used to indicate more traditional computer assistance, e.g., in numerics.) The lists produced by the agent for the months of July and of August respectively are provided below. (It is important to stress that the AI-generated rankings here are based on proximity to my own interests, and should not be regarded as an absolute ranking of importance of the result.)
The generation of these listings is highly unscientific and tailored to my own personal preferences (and there was at least one annotation error, in that the author Van Khu Vu was confused with my collaborator Van Ha Vu), but it does indicate to me the increasing adoption of AI assistance, at least in my own fields of interest.
Farther into the thread, he had this to say when asked what he thought of AI:
"I find AI is similar to other technologies, such as the automobile, in this regard: situationally very useful, but not universally so. (The article “AI as Normal Technology” https://knightcolumbia.org/content/ai-as-normal-technology is one elaboration of this point of view.) Technology is all about tradeoffs; it is almost impossible to avoid conceding some valuable good when using technology to obtain another valuable good, but the best one can do is be mindful both of what one is gaining and what one is giving up when using any technological tool, and explore ways to capture more benefits while simultaneously mitigating or reducing costs.
“For instance, the arXiv summaries I was able to get my agent to generate are certainly extremely convenient compared to manually reading all the submissions (which has become quite challenging in recent months due both to increased volume of arXiv activity, and decreased time available on my end), but come at the cost of serendipity - finding an unexpectedly interesting paper that would not have made it to my summary list due to its offbeat nature or lack of evident match with my previously declared interests. I am thinking of directing my agent to try to create some “artificial serendipity” by throwing in a few additional wildcard items to the summary lists, but this is a partial mitigation of the issue at best.”