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Although more individuals are relying on information provided by nonhuman agents, such as artificial intelligence and robots, little research has examined how persuasion attempts made by nonhuman agents might differ from persuasion attempts made by human agents. Drawing on construal-level theory, we posited that individuals would perceive artificial agents at a low level of construal because of the agents' lack of autonomous goals and intentions, which directs individuals' focus toward how these agents implement actions to serve humans rather than why they do so. Across multiple studies (total N = 1,668), we showed that these construal-based differences affect compliance with persuasive messages made by artificial agents. These messages are more appropriate and effective when the message represents low-level as opposed to high-level construal features. These effects were moderated by the extent to which an artificial agent could independently learn from its environment, given that learning defies people's lay theories about artificial agents.
Kim et al. (Mon,) studied this question.