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The Organization–AI–User Responsibility Triangle: Public Understandings of AI and Expectations for Organizational Responses in AI-Service-Failure Crises

Ke Huang,Fang Wu

Published 2025 in Emerging Media

ABSTRACT

Advances in artificial intelligence (AI) have facilitated its adoption in professional service sectors such as finance and healthcare, but AI projects exhibit a failure rate nearly double that of non-AI projects. These failures, considered corporate crises, have sparked public criticism and damaged corporate–public relationships. Within the framework of the media evocation paradigm, this study examines public perceptions of the roles of AI and humans, along with the subsequent attribution of responsibility and expectations for corporate crisis communication strategies in AI-service-failures. Four semistructured focused group interviews were conducted with a purposively selected sample of participants (N = 21), stratified by AI expertise (with vs without) and AI usage experience (extensive vs limited). Key findings reveal three critical insights: (1) ontological perceptions: the public predominantly rejects the notion of AI as a unique social actor within AI-service-failure crises, instead conceptualizing it as an advanced instrument; (2) responsibility attribution framework: an Organization-AI-User responsibility triangle demonstrates asymmetric accountability—corporations bear maximized responsibility, AI systems are absolved of moral/legal responsibility, and user accountability remains conditional and context-dependent; (3) human-centered expectations: the public's demands align with human-centered AI principles. These expectations prioritize corporate apologies, precautionary measures, and corrective actions over evasive strategies like the contested “mirror strategy” that enables involved companies to deflect responsibility for AI failures by attributing them to broader societal factors.

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