Experimental research examines how consumers judge AI behavior in various contexts, indicating implications for ethical design.
As artificial intelligence (AI) and robots become embedded in everyday service interactions, consumers face not only functional failures but morally consequential violations. Integrating Moral Foundations Theory and Self-Determination Theory, this research examines how consumers morally judge robots that commit harm violations (e.g., causing financial or physical loss) or authority violations (e.g., disregarding or overriding a user's explicit choices). Across three studies involving real-time chatbot interactions in financial, health, and retail contexts, we found that moral judgment depends not only on the violation type but also on consumers’ relational motivations. Effectance-oriented individuals judge harm violations more harshly, whereas affiliation-oriented individuals react more strongly to authority violations. These effects are mediated by competence need and relatedness need frustration, respectively. This research offers a nuanced understanding of how consumers judge AI behavior through a self-referential lens, with implications for ethical AI design and communication in marketing contexts.
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Heo et al. (2026) studied this question.
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