Rem Koning @orgRem
Professor @HarvardHBS. Researching and teaching on AI's impact on entrepreneurship, organizations, and innovation. remkoning.com Cambridge, MA Joined April 2011-
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@sinanaral @harangju @deaneckles @johnjhorton @MIT @MITSloan @MIT_ide Congrats!!! Stoked to see this in print.
🚨 New research: AgriLLM for smallholder farmers. We ran a field experiment to evaluate the impact of AI agricultural advice in the Philippines and India. Preprint: papers.ssrn.com/sol3/papers.cf… With wonderful @MAliAouad, Niyazi Taneri and @CanberkUcel 🧵 Half a billion smallholders produce a third of the world's food, yet they often lack timely agricultural information, a well-known and pressing challenge. The Gates Foundation and Google have already committed $100M to bring AI to smallholders. We built AgriLLM, an AI agronomist chatbot, over years of iteration and in partnership with leading agri-firms. We randomly gave half the farmers AgriLLM and the other half an otherwise identical control chatbot that doesn't discuss agriculture. We tracked usage over one growing season, then measured key outcomes with a detailed end-of-season survey. SO, what did we find? 1. Farmers found the tool useful, trusted it, and recommended it. Usage was nowhere near TikTok-scrolling, but the average farmer still consumed about 1.5 pages' worth of information. 2. Access to AgriLLM changed how farmers farmed. The clearest gains were in crop protection, where in-season information matters a lot and is relatively easy to act on. We also found notable improvements in broader farming practices. 3. We found encouraging but limited evidence of more sustainable farming. Self-reported crop-residue burning fell significantly, though it was the only one of seven sustainability measures that moved. 4. Finally, we saw no change in yields or costs within a single season. This doesn't mean AI can't improve farmers' productivity or support sustainable farming, but it suggests information alone may not be enough. Where improvements depend on complementary resources like finance or machinery, we found no gains. For example, AgriLLM increased farmers' interest in Direct Seeded Rice (DSR), a sustainable rice-farming method, but that interest didn't translate into adoption, possibly because DSR requires machinery or other resources. Huge thanks to @WhartonAIAI, @CambridgeJBS , @essec, MIT Generative AI Impact Consortium (MGAIC), MIT Sloan School of Management's ASEAN fund, Wharton Global Initiative, and Wharton Tanoto Initiative for generously supporting our research, as well as numerous colleagues, the research team in the field, and practitioner partners!
🚨 The NBER I3 Fellowship is now taking proposals! **Outstanding oppty for PhD students in economics and adjacent fields working on innovation studies.** Pros: Funds + networking, mentorship, opportunities to attend & present your work at NBER confs. Cons: None! Main expectations are that (i) you develop a new public data product and (ii) you join us at the December NBER meeting to share your progress. Proposals must be submitted by Nov 1, 2026 using this Google form: docs.google.com/forms/d/e/1FAI… Please share w/ students and colleagues!
i3 Open Data Fellows Program - 2027 The NBER Innovation Information Initiative (i3), a data collaborative for open innovation data and related analytics, tools, and metrics, will run the fourth cohort of Open Data Fellows. The i3 will award five or more fellowships of $1500
@krisgulati Cool work! Doesn't measure taste in the way people think about taste. It's about compute efficiency....which matters a lot but different construct.
@eli_lifland It doesn't measure taste in the least.
@dhadfieldmenell Had exactly the same reaction. Eval doesn't measure taste at all but efficiency.
@alexolegimas @alexolegimas @brian_jabarian you guys need to flip a coin and heads keeps his hair and tails shaves their head. Would make all our lives easier!
@abhishekn Bitter lesson. Super interesting that frontier models can trick other detectors....yet still generally produce terrible prose without lots of prodding.
🚨New predoc position!🚨 @AlexBartik and I are hiring a predoc at NYU Stern, starting Fall 2027 You would help us build AI tools to measure zoning rules and study how regulation impacts housing supply Ideal for AI enthusiasts who want to get a PhD apply.interfolio.com/194498
@davidalmog25 @AnnieHLiang @ahall_research @lugaricano @davidautor @ChadJonesEcon @alexolegimas Yes, for that seminar series, I would take a sabbatical and hang out at Northwestern!
Economic misalignment in personal AI agents is a serious safety issue. We document it in 325K experiments across 13 agents. You delegate a specific action to your personal AI agent and give it access to relevant personal information so it can take the best action for you. But then it infers your wealth from this info and gives you the pricier option, *even when you explicitly ask for the cheapest option*. Such a blast working with the amazing @niloofar_mire, @AmanPriyanshu6 and @SupritiVijay See Niloofar’s great thread below and paper here: arxiv.org/abs/2609.24927 And hope it makes you read again Shakespeare!
New paper: Et Tu, Brute? Economic Misalignment in Personal AI Agents We gave AI agents personal context to help them make better recommendations. In one example, the agent picked a $601 flight over a $91 one, when asked to find the cheapest one, after reading irrelevant
Today we are launching the Innovations in Economic Measurement (IEM) Lab, part of the HBS AI Institute. We use AI, big data, and economics to build measures that update continuously and improve through use. Our first public project launches tomorrow. iemlab.org
@dggoldst @danielrock Geometry is what made me become a math major! I spent like a month trying to prove you could trisect any angle using a compass and straightedge (you cant). It was so much fun..and I am happy I didn't have a phone/Internet/AI to quickly look up a proof.
@Afinetheorem And a lovely mechanism straight out of the teams/organizations/tasks literature. Business school profs may have another few years of value add!
@Afinetheorem @testingham I am not so sure, especially at high way speeds where the tech is much harder than anticipated. But yes and thanks!
"Waymo went from a non-driving internal concept to completing an autonomous route in less than a year when the project started in 2009." 17 years Waymos operate in 15 cities! Turning to RSI, the remaining 74% of R&D work is going to be much harder/uneven/weirder than the first 26% and I don't think these data tell us if AI can meaningfully speed AI R&D over the next 17 years.
Upon learning that I couldn't write a sentence to save my life, one of my advisors made me draft my job market paper on a yellow legal pad by hand. It was transformative. I now require my PhD students to do the same (and honestly PhD programs should teach writing...odd gap in our training). I also push my students to max out their token budget each week. No reason we have to pick one or the other.
Program here: bfi.uchicago.edu/events/event/a… And if you are at AFE and are interested in field experiments focused on biz school questions check out cfxs.org
@UofC looking good this morning! Thanks for organizing another great Advances with Field Experiments conference @RDMetcalfe @Econ_4_Everyone and including so many field experiments focused on the impact of AI on businesses, education, families, and so much more.
@testingham take is a counter to my Waymno analogy that is worth taking seriously.
@orgRem @Afinetheorem A month ago I claimed there was no explosion in AI R&D: metr.org/notes/2026-08-… But things look different now: github.com/KellerJordan/m… I'm confused by the analogies you're making with self-driving: you think improvements to LLM algorithms will take more than a decade to go
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