AI Governance
Frameworks and rules that ensure AI systems operate safely, ethically, and aligned with organizational and societal values.
In Plain English
AI governance is the set of policies, oversight processes, and decision-making structures that an organization or society puts in place to guide how AI is developed, deployed, and monitored. It covers questions like: Who approves new AI projects? How do we audit AI for bias? What happens when an AI system makes a harmful decision? What data can it access? Governance becomes especially important as AI systems grow more autonomous and influential—it's the guardrail system. Effective AI governance balances innovation with safety, transparency, accountability, and fairness, and often involves input from technologists, ethicists, legal experts, and affected communities.
💡Real-World Example
A hospital implementing an AI system to help diagnose cancer might establish a governance framework that requires: radiologists to review all AI recommendations before treatment, regular testing for bias across different patient demographics, and a clear process for patients to appeal AI-influenced decisions. This ensures the AI improves care while protecting patients and staff.
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