Aug 2026· AI & SOCIETY· 0 citations· 45 references
Abstract
Autonomous systems (ASs) will eventually make many decisions in moral dilemmas without human oversight. How humans will respond to the presence of ASs and whether humans will accept them will crucially depend on how ASs’ decisions are programmed. For example, how moral dilemmas are approached in the programming of autonomous vehicles (AVs) is stated as an important factor by potential adopters of this technology. After all, how risks are assigned between different road users will have a strong impact on the socioeconomic structures of society’s mobility. Until now, research on preferences for the programming of ASs in moral dilemmas confronts participants in many instances with life-and-death scenarios based on abstract philosophical thought experiments. This paper offers a first step in evaluating how new knowledge in this area can be acquired through the combination of disciplines. Three empirical studies illustrate the potential advantages of a behavioral economics approach for this string of research. We compare choices in high-stakes hypothetical vignette dilemmas with choices in structurally equivalent low-stakes incentivized experiments. We find that, especially for dilemmas with self-interest, incentivized experiments can provide important additional information, as people tend to overstate their altruistic tendencies in hypothetical dilemmas.
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...
F. Mansilla, Aloysius Y. F. Tok, B. Guellaï et al.· 0 citations
The growing use of autonomous artificial intelligence agents in high-risk areas such as -driving cars, medical triage tools, military robots, and disaster-response drones, has made AI ethics an important concern for researchers. Current alignment methods, especially Reinforcement Learning from Human Feedback, have show...
S. Liyanage, S. Rajasingham· Journal of Multidisciplinary...· 0 citations
Research suggests that individuals are generally skeptical about the use of artificial intelligence (AI) in moral contexts, favoring human decision-makers over AI. Yet, in two experiments involving a total of 5639 participants, we find that individuals facing a real-life moral decision delegate significantly more often...
Investigating how different stakeholders evaluate traffic situations is essential for aligning autonomous vehicle (AV) decision-making with common-sense moral expectations. Yet, empirical studies on traffic moral judgment remain limited and almost exclusively focused on dramatic high-stakes situations. To address this...
Dario Cecchini, Michael Pflanzer, Sam Cacace et al.· Frontiers in Psychology· 0 citations
Society constantly has to determine the boundaries of what it deems acceptable, from legislative decisions to the guardrails governing autonomous systems. We initiate the axiomatic study of collective consent: given individuals'attitudes toward options, which options should receive societal consent? We organize our ana...
Chris Dong, Sonja Kraiczy, Rohit Vasishta et al.· 0 citations
Cyber physical systems such as autonomous vehicles operate in highly dynamic environments where interactions with other autonomous and human agents is inevitable. Reinforcement learning (RL) is a well-established paradigm to allow agents to learn behaviors through interactions with the environment when a model of the e...
John Lewis, Josiah Mesler, Bhaskar Ramasubramanian· Conference on Control Techno...· 0 citations
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