AI System Standardization Advisory offers comprehensive evaluation and expert advisory on the accuracy, reliability, and security of data analysis and modeling utilizing big data, machine learning, and AI technologies during public sector information system audit. It provides in-depth reviews of data analysis methodologies, machine learning model implementations, AI algorithm suitability, and regulatory compliance, delivering actionable recommendations to enhance the quality and efficiency of AI/ML-driven public services.

Key Audit Advisory Points(based on ISO/IEC 42001 AIMS)

Key Audit Areas	Essential Review Items	Priority			Remarks
		High	Med	Low
AI Governance Framework	Organizational structure and responsibilities for AI system management	V			Senior management approval required
Risk Management Framework	Methodology for AI system risk identification and assessment	V			Regular updates required
Data Management Policy	Quality, bias, and security management of training/validation data	V			Include data source traceability
Model Development Process	Documentation of model design, development, testing, and deployment processes		V		Include version control
Transparency and Explainability	Methodology for explaining AI system decision-making processes	V			Customized explanation for different stakeholders
Fairness and Bias Management	Tools/methodologies for bias identification and mitigation		V		Continuous monitoring required
Performance Monitoring	Framework for measuring and monitoring AI system performance		V		Definition of Key Performance Indicators (KPIs) required
Human Oversight and Control	Mechanisms for human supervision and intervention	V			Human review process for critical decisions
Security and Privacy	Data security and privacy measures for AI systems	V			Compliance with relevant regulations (e.g., GDPR)
Internal Audit System	Process for regular audits and improvements of AI systems		V		At least annual audit recommended
Documentation and Records Management	Documentation of key decisions and change history		V		Maintain in audit-traceable format

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BI Value Exchanger offers comprehensive evaluation and expert advisory on the accuracy, reliability, and security of data analysis and modeling utilizing big data, machine learning, and AI technologies during public sector information system audit. It provides in-depth reviews of data analysis methodologies, machine learning model implementations, AI algorithm suitability, and regulatory compliance, delivering actionable recommendations to enhance the quality and efficiency of AI/ML-driven public services.