When Self-Humanization Leads to Algorithm Aversion

Abstract Decision support systems are increasingly being adopted by various digital platforms. However, prior research has shown that certain contexts can induce algorithm aversion, leading people to reject their decision support. This paper investigates how and why the context in which users making decisions (for-profit versus prosocial microlending decisions) affects degree of aversion ultimately preference for more human-like (versus computer-like) systems. The study proposes vary affordances self-humanization. Specifically, perceive as relevant self-humanization than for-profit contexts, and, consequence, they ascribe importance empathy autonomy while contexts. increased leads a higher aversion. At same time, it also stronger support, could therefore serve remedy an induced need results from online experiment theorizing. discusses both theoretical design implications, especially potential anthropomorphized conversational agents on platforms decision-making.