A new theoretical framework proposes a sociotechnical approach to understanding brand crises stemming from artificial intelligence failures. The paper distinguishes between AI incidents, crises, and scandals, suggesting that responsibility attribution is shaped by how an incident is configured and perceived by different actors. It introduces "accountable transparency" as a response strategy that combines timely notice, clear explanations, acknowledgement of responsibility, and evidence of correction. AI
IMPACT Provides a framework for understanding and managing reputational damage from AI system failures.
RANK_REASON Academic paper on AI safety and responsibility. [lever_c_demoted from research: ic=1 ai=1.0]
- artificial intelligence
- chatbot
- generative interfaces
- Hugging Face
- Mohammad Saleh Torkestani
- Recommendation Systems
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