AI governance refers to the frameworks, policies, and standards that ensure the responsible development and use of artificial intelligence.

Purpose

  • Ensures compliance in regulated sectors (e.g. finance, healthcare).
  • Aligns AI deployment with legal, ethical, and societal norms.

Key Constraints

  • Legal compliance
  • Transparency (explainability, auditability)
  • Security (e.g. adversarial robustness)
  • Historical bias in data and models

Notable Standards & Frameworks

  • EU AI Act – risk-based regulatory framework.
  • OWASP LLM Top 10 – security-focused guidelines for large language models.

Tension

  • Governance vs Innovation: Oversight can slow down progress, but lack of it risks harm.
  • Ongoing challenge: Can bureaucracy keep pace with the speed of AI advancement?