Algorithm Aversion: Theory and Evidence from Robo-Advice

Explore the concept of algorithm aversion in the context of robo-advice through this 52-minute lecture delivered by Alberto Rossi from Georgetown University's McDonough School of Business. Delve into theoretical frameworks and empirical evidence surrounding individuals' reluctance to adopt algorithmic decision-making tools in financial contexts. Gain insights into the implications of this phenomenon for the wealth management industry and the broader field of artificial intelligence in finance. Examine real-world applications and challenges faced by robo-advisors, and understand the factors influencing user trust and adoption of automated financial services. This talk, part of the Fields CFI Workshop on Quantitative Methods for Wealth Management, offers valuable perspectives for researchers, finance professionals, and technology enthusiasts interested in the intersection of human behavior and algorithmic decision-making in financial services.

Algorithm Aversion: Theory and Evidence from Robo-Advice