In 2018, a self-driving Uber vehicle in Tempe, Arizona, tragically killed a pedestrian, raising urgent questions about responsibility in the age of autonomous technology. Traditional blame on individuals such as drivers or leaders is no longer sufficient, as decisions now emerge from complex interactions between humans and AI systems. This shift necessitates moving away from assigning fault towards building a shared understanding of responsibility through “narrative responsibility.” Unlike classic linear models that pinpoint a single cause, narrative responsibility recognizes accountability as distributed across teams, technology, and organizational culture. It encourages mapping the full story beyond immediate errors, distributing ownership collectively rather than blaming individuals, and embedding continuous reflection about decisions into daily practices. Examples from Google’s handling of AI failures to aviation safety panels and healthcare incident reviews illustrate how organizations can institutionalize this approach to strengthen learning and resilience. While narrative responsibility complements existing legal and ethical standards without replacing them, it offers a vital framework for navigating accountability amid the rapid evolution of AI-driven systems.
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