Human Perceptions on Moral Responsibility of AI: A Case Study in AI-Assisted Bail Decision-Making
This addresses the problem of responsibility attribution in AI-assisted high-stakes decisions for policymakers and HCI designers, but it is incremental as it builds on existing debates in humanities and social sciences.
This study investigated how people attribute moral responsibility to AI versus human agents in bail decision-making, finding that AI is held causally responsible and blamed similarly to humans, but humans are ascribed higher degrees of present- and forward-looking moral responsibility.
How to attribute responsibility for autonomous artificial intelligence (AI) systems' actions has been widely debated across the humanities and social science disciplines. This work presents two experiments ($N$=200 each) that measure people's perceptions of eight different notions of moral responsibility concerning AI and human agents in the context of bail decision-making. Using real-life adapted vignettes, our experiments show that AI agents are held causally responsible and blamed similarly to human agents for an identical task. However, there was a meaningful difference in how people perceived these agents' moral responsibility; human agents were ascribed to a higher degree of present-looking and forward-looking notions of responsibility than AI agents. We also found that people expect both AI and human decision-makers and advisors to justify their decisions regardless of their nature. We discuss policy and HCI implications of these findings, such as the need for explainable AI in high-stakes scenarios.