All Episodes
Displaying 41 - 58 of 58 in total
Episode 41 — Assess Release Readiness with Model Cards and Conformity Requirements
This episode explains how organizations determine whether an AI system is ready to move from testing into real use without treating release as a guess or a deadline-dr...
Episode 42 — Build Continuous Monitoring, Maintenance, Updates, and Retraining Rhythms for Released AI
This episode focuses on what happens after launch, when an AI system must be monitored and maintained as a living system rather than treated as a finished product. You...
Episode 43 — Assess Production AI After Release with Audits, Red Teaming, Threat Modeling, and Security Testing
This episode explains how organizations should examine AI systems in production using methods that go beyond routine monitoring and basic performance checks. You will ...
Episode 44 — Investigate AI Incidents with Cross-Functional Teams Tracing Drift, Data Gaps, and Brittleness
This episode focuses on incident investigation when an AI system behaves unexpectedly, causes harm, or fails under real-world conditions. You will learn why AI inciden...
Episode 45 — Meet Transparency Duties with Technical Documentation, Instructions, and Monitoring Plans
This episode explains how transparency becomes operational through documentation, user-facing instructions, and monitoring plans that make an AI system understandable ...
Episode 46 — Review AI Development Governance from Impact Assessments to Public Disclosures
This episode pulls together the development lifecycle by showing how governance starts with early impact assessments and continues through design reviews, testing evid...
Episode 47 — Evaluate Deployment Context, Business Goals, Ethics, Data, and Workforce Readiness
This episode explains why a technically capable AI system can still be a poor deployment decision if the surrounding business and operational context are not ready for...
Episode 48 — Compare AI Model Types Before Choosing What Your Organization Will Deploy
This episode focuses on comparing model types so organizations choose an approach that fits the use case, risk profile, explainability needs, and operational environme...
Episode 49 — Choose Deployment Options Across Cloud, On-Premise, Edge, Fine-Tuning, RAG, and Agentic Architectures
This episode explains how deployment architecture shapes governance by affecting data exposure, control boundaries, latency, integration complexity, and responsibility...
Episode 50 — Assess Selected AI Systems with Focused Impact Reviews Before Deployment
This episode explains why organizations should conduct focused impact reviews before deployment even after a system has already been selected, because choosing a tool ...
Episode 51 — Evaluate Vendor Contracts and Licensing Terms Before You Deploy AI
This episode explains why AI governance must include careful review of vendor contracts and licensing terms before deployment, because legal and operational exposure o...
Episode 52 — Understand the Unique Risks, Opportunities, and Obligations of Deploying Proprietary AI
This episode focuses on proprietary AI systems, which can offer performance, customization, or competitive advantage while also creating governance demands that differ...
Episode 53 — Apply Governance Controls to Deployment Through Data, Risk, Issue, and User Training
This episode explains how deployment governance becomes real through operational controls that shape how data is handled, how risks are tracked, how issues are escalat...
Episode 54 — Conduct Ongoing Monitoring, Maintenance, Updates, and Retraining After Deployment
This episode focuses on post-deployment stewardship, which is essential because AI systems continue to change in effect even when their code appears stable. You will l...
Episode 55 — Verify Deployed AI with Audits, Red Teaming, Threat Modeling, and Security Testing
This episode explains how deployed AI systems should be verified through deliberate assurance activities that test more than routine business performance. You will lea...
Episode 56 — Document Incidents and Post-Market Monitoring While Reducing Secondary Uses and Downstream Harms
This episode focuses on the governance work that follows deployment when organizations must document incidents, sustain post-market monitoring, and control how AI syst...
Episode 57 — Establish External Communication Plans and Deactivation or Localization Controls for AI
This episode explains why deployment governance must include plans for what the organization will say externally and what technical or operational controls it can use ...
Episode 58 — Synthesize Development and Deployment Governance into One Defensible Decision-Making Framework
This episode brings the full course together by showing how development governance and deployment governance should operate as one connected decision-making framework ...