Definition #
The organizational structures, policies, and processes that ensure AI systems are developed and used ethically, legally, and in alignment with business objectives.
Key Characteristics #
- Risk assessment protocols
- Compliance tracking mechanisms
- Stakeholder accountability matrices
- Model documentation standards (e.g., model cards)
Why It Matters #
62% of enterprises report AI governance gaps leading to compliance fines (MIT Sloan, 2023). Critical for regulated industries like healthcare and finance.
Common Use Cases #
- Pharmaceutical clinical trial AI oversight
- Bank loan approval system audits
- Public sector algorithmic impact assessments
Examples #
- IBM AI Governance Toolkit
- Microsoft Responsible AI Dashboard
- EU AI Act compliance templates
FAQs #
Q: How does governance differ from ethics?
A: Governance enforces compliance through systems, while ethics focuses on moral principles.
Q: Who owns AI governance in organizations?
A: Typically a cross-functional team with legal, data science, and ops representatives.