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EMAC 2024 Annual


Decisions for an Individual or for a Group: Preference Shifts between Algorithmic and Human Decision-Makers
(A2024-119303)

Published: May 28, 2024

AUTHORS

Xuesong Shang, Zhengzhou University; Xilin Li, China Europe International Business School; Tian Qiu, East China Normal University; Jingyi Lu, East China Normal University

ABSTRACT

Decisions often fall into two distinct categories: those targeted at individuals (e.g., specific patient medical decisions) and those targeted at groups (e.g., managerial decisions affecting an entire company). Despite the increasing integration of algorithms into decision-making, it remains unclear whether preferences for algorithmic versus human decision-makers vary depending on the decision target—an individual or a group. Seven studies spanning diverse domains uncovered a greater preference for algorithms over human decision-makers when making decisions for a group (vs. an individual; Studies 1–3). This tendency emerges primarily due to heightened fairness concerns and diminished uniqueness concerns in decisions for groups (vs. individuals), alongside the perception of algorithms as fair but limited in considering uniqueness (Studies 4 and 5). This tendency is attenuated when group preferences are homogeneous (Study 6) or when decisions are targeted at individual group members rather than at the group as a whole (Study 7).