AI Memory, Confirmation Bias, and Polarization

Study ID sspp-2026-0044-v1

General Details

Project AI, Confirmation Bias, and Polarization
Study ID sspp-2026-0044-v1
Study Title AI Memory, Confirmation Bias, and Polarization
Authors Michael Thaler, Ze Wang
Completion Time 15 Minutes
Close Date (UTC) Oct. 31, 2026
Discipline Economics
Field Political Economics, Experimental Economics, Behavioral Economics
Country United States
Abstract
This survey asks for your predictions about an experiment on AI memory and belief updating. We recently recruited 1,000 U.S. participants for an experiment where they made predictions about Donald Trump's approval ratings. The experiment first had participants discuss their views about Trump's economic and trade policies with an AI interviewer. Participants then made incentivized predictions about whether Trump's approval would increase or decrease on these topics. Before making predictions, they were randomly assigned to either make predictions without AI assistance ("No AI"), make predictions with the option to use an AI assistant with access to their interview ("Memory On"), or make predictions with the option to use an AI assistant without access to their interview ("Memory Off"). We study how this form of AI memory of users affects usage of AI, AI predictions, human belief updating, and subjective confidence. This survey will ask you to predict treatment effects on each of these outcomes. The survey should take about 10-15 minutes to complete, and we will offer a $5 payment for completing the study as a token of our thanks. We recommend you take the survey on a larger device (computer or tablet).

Incentive Details

Incentive Type Flat rate for participation
Incentive Size $5.00
Recipient Pool Everyone receives the incentives

Citation
Thaler, Michael, and Ze Wang. 2026. "AI Memory, Confirmation Bias, and Polarization." Social Science Prediction Platform. September 5. https://socialscienceprediction.org/s/x6ybfz