AI-Induced Human Responsibility (AIHR) in AI-Human teams
As organizations increasingly deploy AI as a teammate rather than a standalone tool, morally consequential mistakes often arise from joint human-AI workflows in which causality is ambiguous. We ask how people allocate responsibility in these hybrid-agent settings. Across four experiments (N = 1,801) in an AI-assisted lending context (e.g., discriminatory rejection, irresponsible lending, and low-harm filing errors), participants consistently attributed more responsibility to the human decision maker when the human was paired with AI than when paired with another human (by an average of 10 points on a 0-100 scale across studies). This AI-Induced Human Responsibility (AIHR) effect held acro...
| Authors | Greg Nyilasy, Brock Bastian, Jennifer Overbeck et al. |
|---|---|
| Primary category | cs.HC |
| Published | 10 April 2026 |
| Last updated at source | 10 April 2026 |
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