HumenhukAIGP Study Guide
Module 8: AI Governance Vocabulary

Governance, assurance and oversight

Reviewed by Victor Humenhuk. Published . Reviewed .

The accountability vocabulary - who answers, who checks, who can challenge. Conformity assessment is the EU AI Act gate for high-risk systems before market, and explainability (why an output) is distinct from interpretability (how the model works inside).

This is the accountability vocabulary: who answers, who checks, who can challenge. AI governance is the rules, policies, processes and accountability structures steering responsible AI across its whole life cycle, and Accountability - people and orgs answerable for a system's functioning and impacts - is its anchor.

  • AI assurance → the measurable mechanisms (evaluations, audits, certifications, documentation) that demonstrate trustworthiness and compliance.
  • AI audit → an independent, systematic review of a system or its governance against defined criteria.
  • Oversight → the supervision arrangements, human or institutional, that monitor, review and can intervene.
  • Transparency → making information available to stakeholders: a system's existence, capabilities, data, logic and limits.
  • Contestability → people's ability to challenge an AI-influenced decision and obtain review or redress.
  • Impact assessment → a risk tool assessing benefits, risks and limitations throughout the life cycle.
  • Human in the loop (HITL) → keeping a human in the decision path to review, confirm or override.
  • Human-centric AI (designed around human needs and dignity) and Trustworthy AI (lawful, ethical and robust) frame the values.
Conformity assessment = EU AI Act gate

Conformity assessment is the process demonstrating a system meets specified legal or standards requirements - and specifically the EU AI Act's gate for high-risk systems before they reach market. Don't confuse it with an audit (independent review) or impact assessment (risk tool).

Explainability vs interpretability

Explainability → describing in plain terms why a model produced a particular output. Interpretability → how the model works inside, consistently and predictably. Explainability is the why this output; interpretability is the how it works.

Key terms - quick answers

What is “AI governance”?
Rules, policies, processes and accountability structures steering responsible AI across its life cycle.
What is “Accountability”?
Identified people/orgs answerable for an AI system's functioning and impacts; anchor of governance.
What is “AI assurance”?
Measurable mechanisms demonstrating a system is trustworthy and compliant (evals, audits, certs, docs).
What is “AI audit”?
Independent, systematic review of an AI system or its governance against defined criteria.

Sources and study method

This independent lesson uses active recall, spaced retrieval and scenario practice. Read the full study method.