AI Governance
AI governance refers to the organizational policies, processes, and oversight mechanisms that ensure ethics, transparency, and accountability in AI system development and operation.
As AI is increasingly used for business decisions, questions like "Why did this AI make this decision?", "Is there bias?", and "Who takes responsibility?" become unavoidable. AI governance is the framework that prepares answers to these questions from both technical and institutional perspectives.
Specifically, it encompasses bias auditing of training data, ensuring explainability of outputs, human-in-the-loop intervention for final decisions, and responsibility allocation during incidents. Frameworks are being developed across regions: the EU AI Act, Japan's AI Business Guidelines, and NIST AI RMF among others.
Organizational adoption requires more than just policy creation—it demands model card management, risk assessment workflow integration, and regular fairness audits. For companies deploying AI in Thailand and ASEAN countries, ensuring alignment with PDPA (Personal Data Protection Act) is also a critical practical concern.
On the technical side, methods for quantitatively detecting training data bias (Fairness Metrics) and visualizing model reasoning (SHAP, LIME) are in practical use, and governance automation is gradually progressing.
Related Terms
AI Literacy (AI Literacy)
Knowledge and skills to understand the basic concepts, limitations, and risks of AI, and to appropriately utilize it in the workplace. Organizations are required to ensure this under the EU AI Act.
EU AI Act (EU Artificial Intelligence Act)
The EU AI Act (EU Artificial Intelligence Act) is a comprehensive European Union regulation that establishes legal obligations based on the risk level of AI systems. It classifies AI into four tiers — "unacceptable risk," "high risk," "limited risk," and "minimal risk" — imposing stricter requirements as the risk level increases.
Shadow AI
Shadow AI refers to the collective term for AI tools and services used by employees in their work without the approval of the company's IT department or management. It carries risks of information leakage and compliance violations.
