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Question 1 of 30
Consider a scenario where an advanced AI-powered diagnostic tool, initially deployed in a controlled research environment, is being prepared for wider clinical adoption. The risk assessment conducted during the research phase identified potential biases in the training data and a low probability of misdiagnosis leading to minor patient inconvenience. However, during the transition to a real-world clinical setting, the AI system is exposed to a significantly broader and more diverse patient population, and its integration with existing hospital IT infrastructure introduces new potential failure points. Which of the following best reflects the approach mandated by ISO/IEC 23894:2023 for managing the risks associated with this transition?
Conduct a comprehensive re-assessment of all identified risks and identify new risks arising from the expanded operational context and system integration, updating mitigation strategies accordingly.
Rely on the initial risk assessment, assuming that the fundamental AI model remains robust and that any new risks are negligible given the system's proven performance in the research phase.
Focus solely on the technical risks introduced by the IT infrastructure integration, as the AI model's inherent performance has already been validated.
Implement a post-deployment monitoring system that only triggers a risk review if a significant number of adverse events are reported by clinicians.

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