Blaming Humans and Machines: What Shapes People's Reactions to Algorithmic Harm

Abstract

Artificial intelligence (AI) systems can cause harm to people. This research examines how individuals react to such harm through the lens of blame. Building upon research suggesting that people blame AI systems, we investigated how several factors influence people's reactive attitudes towards machines, designers, and users. The results of three studies (N = 1,153) indicate differences in how blame is attributed to these actors. Whether AI systems were explainable did not impact blame directed at them, their developers, and their users. Considerations about fairness and harmfulness increased blame towards designers and users but had little to no effect on judgments of AI systems. Instead, what determined people's reactive attitudes towards machines was whether people thought blaming them would be a suitable response to algorithmic harm. We discuss implications, such as how future decisions about including AI systems in the social and moral spheres will shape laypeople's reactions to AI-caused harm.

ACM CHI 2023

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• Perceptions of Sentient AI and Other Digital Minds: Evidence from the AI, Morality, and Sentience (AIMS) Survey
• Public Opinions About Copyright for AI-Generated Art: The Role of Egocentricity, Competition, and Experience
• Should AI Mimic People? Understanding AI-Supported Writing Technology Among Black Users
• "Till I can get my satisfaction": Open Questions in the Public Desire to Punish AI