Human Perceptions on Moral Responsibility of AI: A Case Study in AI-Assisted Bail Decision-Making

• URL: http://arxiv.org/abs/2102.00625v1
• Date: Mon, 1 Feb 2021 04:07:38 GMT
• Title: Human Perceptions on Moral Responsibility of AI: A Case Study in AI-Assisted Bail Decision-Making
• Authors: Gabriel Lima, Nina Grgi\'c-Hla\v{c}a, Meeyoung Cha
• Abstract summary: We measure people's perceptions of eight different notions of moral responsibility concerning AI and human agents. We show that AI agents are held causally responsible and blamed similarly to human agents for an identical task. We find that people expect both AI and human decision-makers and advisors to justify their decisions regardless of their nature.
• Score: 8.688778020322758
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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