Publications
Publications
- April 2024
- Strategic Management Journal
Decision Authority and the Returns to Algorithms
By: Hyunjin Kim, Edward L. Glaeser, Andrew Hillis, Scott Duke Kominers and Michael Luca
Abstract
We evaluate a pilot in an Inspections Department to explore the returns to a pair of algorithms that varied in their sophistication. We find that both algorithms provided substantial prediction gains, suggesting that even simple data may be helpful. However, these gains did not result in improved decisions. Inspectors often used their decision authority to override algorithmic recommendations, partly to consider other organizational objectives without improving outcomes. Interviews with 55 departments find that while some ran pilots seeking to prioritize inspections using data, all provided considerable decision authority to inspectors. These findings suggest that for algorithms to improve managerial decisions, organizations must consider both the returns to algorithms in the context and how decision authority is managed.
Keywords
Algorithmic Aversion; Algorithmic Decision Making; Algorithms; Public Entrepreneurship; Govenment; Local Government; Crowdsourcing; Crowdsourcing Contests; Inspection; Principal-agent Theory; Government Administration; Decision Making; Public Administration Industry; United States
Citation
Kim, Hyunjin, Edward L. Glaeser, Andrew Hillis, Scott Duke Kominers, and Michael Luca. "Decision Authority and the Returns to Algorithms." Strategic Management Journal 45, no. 4 (April 2024): 619–648.