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

TL;DR

This study investigates how people perceive moral responsibility of AI versus humans in bail decisions, revealing AI are seen as causally responsible but less morally responsible, emphasizing the need for explainable AI in critical contexts.

Contribution

It provides empirical evidence on public perceptions of AI moral responsibility, highlighting differences from human responsibility and implications for policy and HCI design.

Findings

AI are held causally responsible similar to humans

Humans are ascribed higher moral responsibility than AI

People expect explanations from both AI and humans

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.