Table 4 Examines how trust patterns vary across advice quality by analyzing reliance on correct versus incorrect advice separately using the four-week experimental period. The dependent variables are the weight on wrong advice (WOWA) and the weight on correct advice (WOCA). WOWA takes the value of ‘1’ if the subject follows the wrong advice and ‘0’ otherwise, while WOCA takes the value of ‘1’ if the subject follows the correct advice and ‘0’ otherwise. Our main explanatory variables (Gender, AI advice, and High-knowledge) are binary, and the coefficients can be interpreted in percentage terms. Feedback is a binary variable that takes the value of ‘1’ for observations after the second week. The table reports OLS coefficient estimates and (in parentheses) p-values based on robust standard errors clustered by subject and question. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels (two-tailed), respectively.

From: Gender, knowledge, and trust in artificial intelligence: a classroom-based randomized experiment