CMU's Human-AI complementarity workshop is returning this September! Submit abstracts here by July 17; travel funding is available for accepted presenters. www.cmu.edu/ai-sdm/resea...
LLMs are increasingly used as agents for decisions under uncertainty, e.g. medical diagnosis. But do they act like rational agents with coherent beliefs and preferences? Much of the difficulty is telling whether a model's response to.a prompt ("What is the probability of X?") is a "real" belief.
LLMs are increasingly used as agents for decisions under uncertainty, e.g. medical diagnosis. But do they act like rational agents with coherent beliefs and preferences? Much of the difficulty is telling whether a model's response to.a prompt ("What is the probability of X?") is a "real" belief.
In applications based on medical diagnosis, the answer is...sometimes! In some settings, we can prove that no rational agent could hold beliefs expressed by the model. But in others, particularly for stronger models, outputs are close to consistent with rational belief
We give a framework to test whether the model's stated belief functions *as if it were* a rational agent's subjective probability by comparing with its decisions. We give empirically checkable conditions that don't require any assumptions about the model's "utility function".
You might think that models don't have coherent beliefs at all. Or, you might think that they don't report truthfully in response to any given prompt. How could we possibly tell?
The EAAMO conference deadline is coming up! conference.eaamo.org/cfp/
Great community at intersection of CS-Operations-Econ and social good. Flexible publication format (e.g., non-archival option) and so costless to submit here as well!
Deploying algorithmic research in practice is an opaque process. We're organizing a workshop at EC to share behind-the-scenes stories and move the field foward. Call for submissions open!
With @nkgarg.bsky.social @ericachiang.bsky.social, Bailey Flanigan
sites.google.com/cornell.edu/...
Paper here: arxiv.org/abs/2602.06286. Led by my excellent PhD student Khurram Yamin
As UKRI explores using LLMs to review grants, it's a good time to revisit Bryan Wilder's excellent blog post.
There are a lot of naive reasons to oppose AI review ("you'll never automate human intuition!"). But there are also good reasons, including the *load-bearing role of human disagreement.*
Bryan Wilder
Bryan Wilder
Bryan Wilder
Bryan Wilder
Bryan Wilder
Bryan Wilder
Bryan Wilder
Bryan Wilder
Nikhil Garg
Ted Underwood
conference.eaamo.org
ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization
