Governance of Deployment, Use and Ongoing Controls
This topic covers applying policies and best practices to deployment, data governance, risk management, issue management, user training, continuous monitoring, maintenance, updates, retraining, audits, red teaming, threat modeling, performance, reliability, safety, incident documentation, downstream harms, external communication, deactivation, and localization.
How to study for IAPP AIGP
Treat each question as a governance decision: identify the AI role and life-cycle stage, classify the legal or risk issue, then choose the control, evidence, and accountability path.
Core concepts
Concept 1
Deployment governance applies policies, controls, user training, data governance, risk management, and issue management to real-world AI use.
Exam cue: Use user training when people need to understand system limits and escalation paths.
Concept 2
Ongoing monitoring should address performance, reliability, safety, maintenance, updates, retraining, audits, red teaming, threat modeling, and security testing.
Exam cue: Use downstream harm analysis when AI outputs could be reused or affect others indirectly.
Concept 3
Organizations should plan for incidents, downstream harms, unintended uses, external communications, deactivation, localization, and regulatory or performance-driven changes.
Exam cue: Use deactivation or localization controls when performance, legal, or regional issues require limiting use.
Risk pitfalls and guardrails
Treating deployment approval as the end of governance.
Guardrail: Avoid treating vendor tools as risk-free, relying on aggregate accuracy alone, or stopping governance after deployment approval.
Ignoring secondary uses of AI output after the first workflow.
Guardrail: Avoid treating vendor tools as risk-free, relying on aggregate accuracy alone, or stopping governance after deployment approval.
Communicating externally without a prepared incident and transparency plan.
Guardrail: Avoid treating vendor tools as risk-free, relying on aggregate accuracy alone, or stopping governance after deployment approval.
Memory anchors
User Training
User training teaches appropriate AI use, limits, escalation, and human review expectations.
Issue Management
Issue management captures, triages, tracks, remediates, and documents AI problems.
Downstream Harm
Downstream harm occurs when AI outputs cause later or indirect negative effects.
Secondary Use
Secondary use is using AI data or output for a new purpose beyond the original context.
External Communication
External communication explains AI incidents, limitations, obligations, or changes to outside stakeholders.
Deactivation Control
A deactivation control allows an AI system to be suspended or disabled when risk requires it.
Localization Control
Localization control changes or limits AI operation for a jurisdiction, language, market, or context.
Ongoing Governance
Ongoing governance keeps AI controls active through monitoring, review, maintenance, and improvement.
Checkpoint rule
Do the check-up only after you can summarize each concept in one sentence and identify one dangerous pitfall from memory.
Knowledge Check (after reading)
Short check-up to confirm understanding of this module.
Check-up Questions
Why should the organization enforce that a deployed AI system is used within its approved scope?
Why should access controls govern who can use a deployed AI system and its data?
Answer all questions to submit.
Next step personalized recommendations
Continue learning
Move forward only after this module is stable.
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