Do Consumers Accept AIs as Moral Compliance Agents?

Social conformity is a well-documented phenomenon in which individuals shift their opinions towards those of a social majority. As artificial intelligence (AI) becomes increasingly integrated into everyday life it may also create a novel source of influence giving rise to algorithmic conformity, mechanisms of which are poorly understood. The present study examined whether AI judgements affect moral decision-making in humans (n=165) adapting the classical Asch paradigm. Participants completed a series of moral dilemmas under three different conditions: in presence of social majority, with an AI model providing brief answers and with an AI model providing both answers and explanations of its choices. In all conditions the presented responses contradicted generally accepted moral norms. The results indicated that an AI model with a reasoning component affected the opinion of participants to a degree comparable to that of a human majority. These findings suggest that even moral judgements, despite their sensitivity and personal significance, may be susceptible to algorithmic conformity. However, the mechanism underlying algorithmic conformity appears to differ from the social one. Overall, the study challenges the assumption that moral decision-making lies in "AI inadmissibility zone" - a sphere that is considered as an area in which only human-made decisions are acceptable and highlights the need for a further investigation of this phenomenon as AI-based recommendations become increasingly embedded into human decision-making.

The growing use of generative AI raises ethical concerns about authorship and plagiarism. This study examines how people judge the reuse of AI-generated content, focusing on moral patiency and ownership perceptions. In an experiment, participants evaluated two substantively similar manuscripts in which the original source was described as authored by a human, an AI system, or an AI agent with a human-like name. Results showed that copying AI-generated work was judged less unethical, less plagiaristic, and less guilt-inducing than copying human-authored work. Mediation analyses revealed that this leniency stemmed from lower perceptions of AI's capacity to suffer harm (moral patiency) and greater ownership attributed to the human writer reusing AI-generated content. Anthropomorphic cues shaped moral evaluations indirectly by reducing perceived ownership. These findings shed light on how people morally disengage when using AI-generated work and highlight differences in how ethical judgments are applied to human versus AI-created content.

As LLMs take on roles requiring moral advice, understanding how they attribute moral agency becomes critical. Humans possess moral agency, the capacity to make ethically guided decisions and bear responsibility for their consequences, a well-established construct in moral psychology. Yet as artificial agents (AAs) such as robots, drones, and disembodied AI systems become increasingly embedded in smart city environments, the question of whether and how moral agency is attributed to them takes on new urgency. This paper presents, to the best of our knowledge, the first empirical study comparing how humans and LLMs evaluate perceived moral agency (PMA) across human and autonomous artificial agents varying in embodiment, situated in plausible smart city scenarios. Using an adaptation of a validated PMA scale, we applied a protocol to 190 human participants as well as various LLMs. Our evaluation reveals higher perceptions of moral agency in humans than in AAs. However, when facing moral dilemmas in concrete scenarios, LLMs reason outward from the situation, prioritizing harm severity and contextual urgency over any stable assessment of the agent itself, amplifying a context-sensitivity also present in human raters. These findings are particularly relevant as LLMs become increasingly involved in everyday moral decisions.