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Governance & Policy

AI Products must declare the governance policies that apply to their design, deployment, and use.
Governance ensures AI Products operate within legal, ethical, and organizational boundaries.

Why Governance & Policy Matter​

  • Accountability → Consumers and regulators need to know what rules apply.
  • Compliance → AI laws (e.g., EU AI Act) require policy declarations and evidence.
  • Risk Management → High-risk AI Products demand stronger safeguards.
  • Transparency → Policies make clear what is allowed, restricted, or prohibited.

Governance Requirements​

An AI Product must declare:

  1. Applicable Regulations

    • Global, regional, and sector-specific standards (e.g., GDPR, HIPAA, ISO/IEC 42001).
    • AI-specific frameworks (EU AI Act, NIST AI RMF).

  2. Organizational Policies

    • Internal data handling policies.
    • AI ethics guidelines.
    • Security, privacy, and compliance frameworks.

  3. Risk Classification

    • Declared as Minimal, Limited, High, or Unacceptable Risk.
    • Determines governance obligations (e.g., documentation, monitoring, human oversight).

  4. Policy Enforcement Hooks

    • Automated enforcement (access restrictions, usage limits).
    • Manual oversight (approvals, audits).
    • Governance checkpoints in the product lifecycle.

  5. Evidence Artifacts

    • Audit logs, test reports, validation datasets.
    • Model or system cards for ethical transparency.
    • Compliance certificates.

Governance Integration​

Governance metadata must integrate with:

Example​

AI Product: Credit Scoring Classifier

  • Applicable Regulations: EU AI Act (high-risk), GDPR (Art. 22 automated decisions).
  • Organizational Policies: Enterprise AI Ethics Charter.
  • Risk Classification: High Risk.
  • Policy Enforcement:
    • Automated: Restricted to authorized risk teams only.
    • Manual: Quarterly compliance reviews.
  • Evidence Artifacts: Fairness audits, explainability reports, drift monitoring logs.

Summary​

  • Governance policies must be declared, enforced, and evidenced.
  • They cover regulations, organizational rules, risk classification, and enforcement mechanisms.
  • Governance metadata links to security, prohibited uses, and quality metrics.

Principle: An AI Product without declared governance policies is unaccountable — and risks misuse or non-compliance.