Artificial intelligence has quickly integrated into human society and its moral decision-making has also begun to slowly seep into our lives. The significance of moral judgment research on artificial intelligence behavior is becoming increasingly prominent. The present research aims at examining how people make moral judgments about the behavior of artificial intelligence agents in a trolley dilemma where people are usually driven by controlled cognitive processes, and in a footbridge dilemma where people are usually driven by automatic emotional responses. Through three experiments (n = 626), we found that in the trolley dilemma (Experiment 1), the agent type rather than the actual action influenced people’s moral judgments. Specifically, participants rated AI agents’ behavior as more immoral and deserving of more blame than humans’ behavior. Conversely, in the footbridge dilemma (Experiment 2), the actual action rather than the agent type influenced people’s moral judgments. Specifically, participants rated action (a utilitarian act) as less moral and permissible and more morally wrong and blameworthy than inaction (a deontological act). A mixed-design experiment provided a pattern of results consistent with Experiment 1 and Experiment 2 (Experiment 3). This suggests that in different types of moral dilemmas, people adapt different modes of moral judgment to artificial intelligence, this may be explained by that when people make moral judgments in different types of moral dilemmas, they are engaging different processing systems.

Along with the increasing development of information technology, the interaction between artificial intelligence and humans is becoming even more frequent. In this context, a phenomenon called “medical AI aversion” has emerged, in which the same behaviors of medical AI and humans elicited different responses. Medical AI aversion can be understood in terms of the way that people attribute mind capacities to different targets. It has been demonstrated that when medical professionals dehumanize patients—making fewer mental attributions to patients and, to some extent, not perceiving and treating them as full human—it leads to more painful and effective treatment options. From the patient’s perspective, will painful treatment options be unacceptable when they perceive the doctor as a human but disregard his or her own mental abilities? Is it possible to accept a painful treatment plan because the doctor is artificial intelligence? Based on the above, the current study investigated the above questions and the phenomenon of medical AI aversion in a medical context. Through three experiments it was found that: (1) human doctor was accepted more when patients were faced with the same treatment plan; (2) there was an interactional effect between the treatment subject and the nature of the treatment plan, and, therefore, affected the acceptance of the treatment plan; and (3) experience capacities mediated the relationship between treatment provider (AI vs. human) and treatment plan acceptance. Overall, this study attempted to explain the phenomenon of medical AI aversion from the mind perception theory and the findings are revealing at the applied level for guiding the more rational use of AI and how to persuade patients.

The absence of anthropology from cognitive science may be related to the fact that the Western-dominated cognitive approach is not human-centered. From an anthropological perspective, we propose a possible social cognitive model-the human-centered social cognitive chain. It is a theory of the human cognitive process that includes two phenomena- anthropomorphism and dehumanization; has two directions-upward and downward; involves two dimensions-morality and competence; and produces two results-cuteness and coolness. It is a way for humans to understand the whole world with themselves as starting point and end point, governing social cognition. The human-centered social cognitive chain involves gods, humans, animals, plants, artificial objects, pure objects, and even abstract concepts, on the basis of which upward and downward anthropomorphism and upward and downward dehumanization arise. The existing research on anthropomorphism and dehumanization is slightly biased in that it only emphasizes upward anthropomorphism and downward dehumanization. Theoretically, both anthropomorphism and dehumanization should be two-stage processes based on essentialism, but humans engaged in cognition tend to adopt a dimensional view that simplifies them. The morality-competence dichotomy reflects this tendency and results in the cognitive outcomes of cuteness, where morality is valued higher than competence and coolness, where competence is valued higher than morality. The human-centered social cognitive chain is the paradigm by which humans understand themselves, their culture, and the world.