Join the meeting here<https://teams.microsoft.com/l/meetup-join/19%3ameeting_OTkzYzAyOTctOWY1My00Z...> Title: Understanding Student Perceptions of Human vs. Algorithmic Recommendations in College Applications Faidra Monachou , Yale School of Management Abstract: This study examines student preferences for human versus algorithmic recommendations in college applications across 14 public high schools. We find that students exhibit aversion to algorithmic recommendations when the basis is more objective but not when it is most subjective. Aversion is strongly driven by perceptions of the recommender’s intent, alongside alignment with personal goals, ability, and comprehension. Free-text responses suggest that students seek guidance on study options from human counselors but rely on algorithms for grade-based recommendations. Using an optimization approach, we show how a policymaker can navigate heterogeneity in recommendation adoption and optimally assign human versus algorithmic recommenders under capacity constraints. A targeting policy based on readily available student and school features can closely approximate a first-best, personalized approach. These findings underscore the importance of understanding student preferences for effective, equitable recommendation systems and highlight the potential of hybrid approaches integrating human guidance with algorithms. <https://arxiv.org/abs/2407.02191>Bio: Faidra Monachou is an Assistant Professor of Operations Management at the Yale School of Management. She is interested in market design and operations for social impact, with a particular focus on education. She uses mathematical tools from operations research, economics, and data science to design operational interventions that optimally balance efficiency and equity. Her research has received the Best Paper with a Student Presenter Award at the ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO) and the first place in the inaugural INFORMS DEI Best Student Paper competition. Faidra completed her PhD in Operations Research at the Management Science and Engineering department at Stanford University and her undergraduate studies in Electrical and Computer Engineering at the National Technical University of Athens in Greece. Prior to joining Yale, she was a Postdoctoral Fellow at Harvard University. Subscribe to future talk announcements: Anyone outside Bell Labs can receive talk announcements by subscribing to the mailing list. To subscribe, send an empty email with the subject line "Subscribe RAI" to daniele.quercia@nokia-bell-labs.com<mailto:daniele.quercia@nokia-bell-labs.com>.