ISO 7098:2015 Information and documentation -- Romanization of Chinese Quiz 04 24Mar25 - Practice Quiz

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InnovAI, a multinational corporation specializing in AI-driven personalized medicine, recently experienced a critical incident where its diagnostic AI misclassified a rare genetic marker, leading to delayed treatment for several patients. Following the incident, the internal audit team initiated a comprehensive review of the AI management system, aiming to leverage this experience for continuous improvement, as mandated by ISO 42001:2023. Considering the diverse facets of an AI management system, which of the following approaches would most effectively translate the lessons learned from this incident into tangible improvements across InnovAI\'s AI operations, ensuring enhanced safety, reliability, and ethical compliance in future AI deployments? The company is committed to upholding the highest standards of AI governance and ethical conduct.

Establish a closed-loop system where the incident report triggers a root cause analysis, leading to updates in data governance protocols, model validation procedures, retraining of AI development teams on bias detection, and revisions to the AI ethics policy, with regular audits to ensure sustained compliance and effectiveness of the implemented changes.

Focus primarily on enhancing the technical aspects of the AI model by adjusting the algorithm's sensitivity to genetic markers and increasing the volume of training data related to rare genetic conditions, while documenting the changes made for future reference.

Implement a new incident reporting system with mandatory training for all employees on how to identify and report potential AI-related incidents, coupled with the creation of a dedicated incident response team responsible for immediate containment and resolution.

Conduct a one-time review of the AI system's performance metrics and recalibrate the model's parameters to improve its accuracy in detecting genetic markers, followed by a company-wide announcement emphasizing the importance of vigilance in AI system monitoring.

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