ISO 20775:2009 Information and documentation -- Schema for holdings information Free Practice Test — 30 Questions

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InnovAI, a rapidly growing fintech company, has recently implemented an AI-powered loan application system to streamline its lending process and improve customer experience. The system was designed and developed following industry best practices, incorporating fairness and transparency principles during the initial stages. After six months of operation, complaints regarding unexpected loan denial rates among certain demographic groups have surfaced, despite the initial fairness assessments. Internal audits reveal that the AI model, while performing well on overall metrics, exhibits subtle biases due to evolving market conditions and data drift. Furthermore, compliance with updated regulatory guidelines on AI lending practices is unclear. The company\'s AI governance board is now evaluating strategies to mitigate these risks and ensure ongoing compliance with ISO 42001. Considering the entire AI system lifecycle, which of the following actions is most critical for InnovAI to effectively address the identified issues and maintain a robust AI risk management framework?

Conducting a thorough post-implementation review and evaluation of the AI system, focusing on bias detection, performance analysis, and alignment with updated regulatory guidelines, to inform iterative improvements and risk mitigation strategies.
Re-evaluating the initial design specifications and development processes to identify potential flaws in the original AI model architecture and implement necessary code modifications.
Deploying a new version of the AI model with enhanced explainability features to improve transparency and provide clearer justifications for loan decisions to applicants.
Strengthening the data governance policies and procedures to ensure data quality and representativeness, while also increasing the frequency of data refreshes for the AI model training.

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