Antonio Arechar is an Associate Professor in the Department of Economics at the Center for Research and Teaching in Economics (CIDE). His research interests are in the areas of Behavioral Economics, Microeconomics and Game Theory.
Involvement
Large language models can effectively convince people to believe conspiracies
LLMs are persuasive across a variety of contexts, but it’s unclear whether this persuasive power advantages truth over falsehood. We ran three preregistered experiments where participants discussed a conspiracy theory with GPT-4o, which was instructed to either argue against (“debunking”) or for (“bunking”) that conspiracy, and found that GPT-4o was just as effective at increasing belief in conspiracies as decreasing it.
It's the Thought that Counts: Evaluating the Attempts of Frontier LLMs to Persuade on Harmful Topics
In order to persuade users, LLMs must both be capable of persuading and willing to do so. Existing research explores the former, and we present the Attempt to Persuade Eval (APE) benchmark that tests how willing LLMs are to generate content aimed at shaping beliefs and behavior to flesh out the latter.