Brand new paper with @johnjhorton that I'm very excited to share: "General Social Agents" Suppose we wanted to create AI agents for simulations to make predictions in never-before-seen settings. How might we do this? We explore an approach to answering that question!

I've reread this sentence at least 50 times in the last two days of editing. I giggle every single time 😅

Always great when your serious model rewrite turns into a comparison of human and AI… "structures"

I binged every episode of this podcast. Petition to have more guests please - a great start with the inimitable Bo Cowgill!

I made a list of forecasts of the impact of AI on economic growth over the next decade. A few observations... (🧵): https://t.co/eCaw0qPNaA

AI presents a fundamental threat to our ability to use polls to assess public opinion. Bad actors who are able to infiltrate panels can flip close election polls for less than the cost of a Starbucks coffee. Models will also infer and confirm hypotheses in experiments. Current

@nberpubs @BenSManning @AndreyFradkin @johnjhorton Here’s a short thread where we walk through the main points: https://t.co/XMljBHWXPJ

And yes—we’re putting some money where our mouths are. An empirical paper is on the way. Stay tuned ;) cc: @gilirusak @johnjhorton

Examining how AI agents transform markets by lowering transaction costs and enabling new designs. Also discussing agent demand, supply, and design, from @Peyman_Shahidi, Gili Rusak, @BenSManning, @AndreyFradkin, and @johnjhorton https://t.co/IOQHvxqnC4

updating our paper abstract: "in this paper, we demonstrate that there is insane alpha in checking both Uber and Lyft before booking"

Has anyone ever analyzed the bargaining data from pawn stars? With the transcripts of the episodes, it would be pretty easy to parse the back and forth. Like how much better is Rick at bargaining than the laymen who come into sell stuff?

This excellent review paper by @johnjhorton and colleagues explores the impact of AI on firm boundaries, organization, and strategy, focusing on the role of AI agents in performing search, bargaining, and contracting functions on behalf of consumers. 3/3

This looks awesome - I've been waiting for someone to write a paper like this! I can't wait to read.

@daniel_p_gross @abhishekn @danielrock @arpitrage @nummoose I think standard for minimum publishable piece will go way up. Novel data creation will still be useful. "Taste" will be more valued in research questions. Not using AI tools for steps that can be completely automated will be like doing regressions by hand. What do you think?

Starting in less than an hour. Join us if you can!

Excited to be on the job market! This paper is part of my broader agenda to understand AI adoption through a behavioral economics lens. Thanks to Alex for the guidance and support!

My student David Almog (@davidalmog25) is on the job market. His JMP identifies important barrier to AI adoption: Image concerns. In a clever field study, workers are less likely to adopt/follow *useful* AI recs if they know AI reliance will known to managers (links in reply).

Like, @m_sendhil and jens Ludwig’s ML + hypothesis generation paper — something that inspired me to get a PhD— https://t.co/rmTvktKXp7 is 5+ years old. Yet we still aren’t trying to push and imagine better in one of the world’s top scientific journals?? Sad

This is disheartening. Skimming w/o any prior info would leave with me feeling neutral/negative on the possibilities of AI x social science. But the status quo of social science leaves so much to be desired - and with AI, we ALREADY can do fantastical and inspiring new things!

Are there any startups that have done a reasonably good job at creating an AI data scientist? If not, what are the main barriers?

🦜@ExpectedParrot is an open-source framework for simulating your customers with AI agents. Test pricing, refine messaging, and explore product feedback and decisions in minutes, not weeks. https://t.co/f6JKZvUd8l Congrats on the launch, @johnjhorton and Robin!