Sutirth Dey teaches a class of 300 and runs a lab. Both halves of that job have changed since 2024, and he has been keeping score.
He is a professor of biology at IISER Pune and chaired the committee that wrote the institute's AI policy, a document that inverts the default nearly everyone else chose. AI is permitted unless a faculty member forbids it in writing, and anyone who forbids it has to say up front how they intend to catch it.
He set 100 undergraduates a research grant proposal he could not have assigned before, then built an agentic system on Claude Opus to review the results, hit his session limits, bought more subscriptions and put four TAs on it. One student's proposal turned on eggs being blue-green; the AI caught it, and the eggs are brown. On the research side he expects AI peer review within a few years, and expects it to make journals think alike, which closes the door that path-breaking papers have always come through.
Highlights
Permitted by default — IISER Pune allows AI unless a faculty member forbids it in writing. The policy came out of an all-institute survey, six weeks of comments and a senate vote.
Forbid it and you must say how you will catch it — the clause that keeps the policy honest. No surprise accusations in week twelve.
Detection does not work — false positive and false negative rates on plagiarism tools are high enough that students will run their work through the detector until it stops complaining.
What he does instead — an unaided quiz after the assignment, with the mark penalty announced in advance.
An assignment that needed AI to exist — 100 students writing full grant proposals, at a level he would not have set before.
And needed AI to grade — 15 to 20 minutes of Claude Opus per report, session limits, extra subscriptions, four TAs. He says the reviews were good enough that he would have been glad to get them as a journal editor.
The egg — one proposal built its experimental design on the wrong shell colour. He checked Wikipedia; the AI was right.
"Am I going to do it again? Most probably not" — the effort was too high.
Grade appeals, automated — students photograph their marked scripts, feed them to AI and come back with a case. "We are not fighting the students anymore, we are fighting Claude."
AI peer review flattens science — a rejected paper wanders until it meets the one odd reviewer who says yes, and that is how a lot of good work got published. Run the same model at every journal and the wandering stops.
What is left for PhD students — he does not think good labs used them as cheap hands anyway, so he expects less disruption in research than in industry.
Motivation, not access, is the divide — the same tool speeds up the self-driven and lets everyone else coast. Second-years buy Claude Max to do number theory in Lean while classmates ask why they should attend a lecture.
Khanmigo worked and still failed — measurable exam gains for the students who used it, and Khan Academy called it a failure because 90% did not.
Cognitive friction — the movie-theatre argument, the maahaul a good teacher makes, and why he thinks learning from a screen alone does not stick.
Cost worries him at the lab, not the desk — free tiers are generous and students rotate between them. Funded groups pulling ahead of unfunded ones is the inequality he expects.
Notable quotes
Use of AI is permitted by default until and unless somebody, somebody as in either a faculty or a PI or an administrator explicitly and in writing forbids the use of AI.
You use AI in whatever way you seem fit, but end of the day, the responsibility for the content is entirely the authors. […] You cannot simply say that I use AI, ChatGPT told me so. Doesn't work.
This is a AI native use case, so to speak. […] Was it beneficial to the students? I would definitely like to think so. Am I going to do it again? Most probably not.
So we are not fighting the students anymore, we are fighting Claude.
You fight with 300 students for one-one mark, you decide only one way.
If you learn from AI, it is not possible for you to fall in love with what you are learning.
That cognitive friction, if AI totally eases it out, then where is the joy of finding things out?
— Ashish Kulkarni: Slight paraphrase, but I hope we end up titling this episode, No Student is an Island.
Links & resources
IISER Pune — where the policy was written, by a committee Sutirth chaired.
Daniel F. Chambliss, The Mundanity of Excellence — the study of swimmers at every level that Sutirth calls brilliant, and How College Works, written with Christopher G. Takacs, where his argument about college being mostly social comes from.
Isaac Asimov, The Fun They Had — the 1951 story he retells, about a child who finds out schools used to exist. He also paraphrases Asimov's "Such folly smacks of genius. A lesser mind would be incapable of it."
Hollis Robbins — writes Anecdotal Value on AI and higher education; Ashish's peg for the learning-rate question.
Khanmigo — Khan Academy's tutor, and Navin's example of a tool that works and goes unused.
Refine.ink — the AI paper-review service Sutirth prices at about $40 a review, and the peg for the West-versus-India cost question.
Claude, ChatGPT, Gemini, NotebookLM, and Lean — the tools named on air. NotebookLM, since renamed Gemini Notebook, for students working in a second language; Lean for the number theory.
Connect with Sutirth Dey
Email s.dey@iiserpune.ac.in, which he says is the best way to reach him
Population Biology Laboratory — his lab
