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

AI related standards

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BI Data insight sharing and trading services play a pivotal role in maximizing the business intelligence (BI) value of enterprises. At its core, this involves leveraging the results of data analysis derived from vast amounts of big data through sophisticated machine learning and artificial intelligence (AI) technologies to generate valuable management insights. The primary objective is to foster a more advanced business environment and jointly pursue profit generation by sharing and mutually trading these data-driven insights among companies within the same industry. By actively sharing or, when necessary, transacting the core management insights hidden within the diverse data accumulated throughout business operations, participating companies can forge partnerships that transcend individual capabilities. Furthermore, the profound understanding gained through the process of data exchange and analysis offers opportunities to enhance the operational efficiency of each enterprise and uncover previously unnoticed innovative operational tips or strategic directions. This not only accelerates the growth of individual companies but also ultimately contributes to building a healthier and more competitive industrial ecosystem by promoting knowledge sharing and collaboration across the same industry.