The current research aims to answer the following question: “who will be held responsible for harm involving an artificial intelligence system?” Drawing upon the literature on moral judgments, we assert that when people perceive an AI system’s action as causing harm to others, they will assign blame to different entity groups involved in an AI’s life cycle, including the company, the developer team, and even the AI system itself, especially when such harm is perceived to be intentional. Drawing upon the (...) theory of mind perception, we hypothesized that two dimensions of mind: perceived agency—attributing intention, reasoning, pursuing goals, and communicating to AI, and perceived experience—attributing emotional states, such as feeling pain and pleasure, personality, and consciousness to AI—mediated the relationship between perceived intentional harm and blame judgments toward AI. We also predicted that people are likely to attribute higher mind characteristics to AI when harm is perceived to be directed to humans than when it is perceived to be directed to non-humans. We tested our research model in three experiments. In all experiments, we found that perceived intentional harm led to blame judgments toward AI. In two experiments, we found perceived experience, not agency, mediated the relationship between perceived intentional harm and blame judgments. We also found that companies and developers were held responsible for moral violations involving AI, with developers received the most blame among the entities involved. Our third experiment reconciles the findings by showing that perceived intentional harm directed to a non-human entity did not lead to increased attributions of mind to AI. These findings have implications for theory and practice concerning unethical outcomes and behavior associated with AI use. (shrink)

A robot's decision to harm a person is sometimes considered to be the ultimate proof of it gaining a human‐like mind. Here, we contrasted predictions about attribution of mental capacities from moral typecasting theory, with the denial of agency from dehumanization literature. Experiments 1 and 2 investigated mind perception for intentionally and accidentally harmful robotic agents based on text and image vignettes. Experiment 3 disambiguated agent intention (malevolent and benevolent), and additionally varied the type of agent (robotic and human) using (...) short computer‐generated animations. Harmful robotic agents were consistently imbued with mental states to a lower degree than benevolent agents, supporting the dehumanization account. Further results revealed that a human moral patient appeared to suffer less when depicted with a robotic agent than with another human. The findings suggest that future robots may become subject to human‐like dehumanization mechanisms, which challenges the established beliefs about anthropomorphism in the domain of moral interactions. (shrink)