All Episodes
Displaying 21 - 40 of 92 in total
Episode 21 — Build an AI Risk Program Charter: Scope, Objectives, and Success Measures (Domain 2)
Establishing a formal AI Risk Program Charter is a foundational step in Domain 2, providing the necessary authorization and structure for all subsequent risk managemen...
Episode 22 — Design the AI Risk Operating Model: People, Process, Tools, and Cadence (Domain 2)
The AI Risk Operating Model represents the functional mechanics of how risk is identified and managed on a day-to-day basis, a critical area of focus for Domain 2. Thi...
Episode 23 — Stand Up an AI Risk Intake Process: Bring New Use Cases Under Control (Domain 2)
An effective AI risk intake process serves as the "front door" for all AI-related initiatives, ensuring that no model is developed or deployed without a preliminary ri...
Episode 24 — Run AI Risk Assessments Consistently: Methods, Criteria, and Evidence Rules (Domain 2)
Consistency in running AI risk assessments is paramount to maintaining a defensible and objective risk posture, a core competency tested in Domain 2. This episode expl...
Episode 25 — Build a Living AI Risk Register: Structure, Owners, Updates, and Reporting (Domain 2)
An AI Risk Register is the central repository for all identified risks, and it must function as a "living" document that evolves alongside the technology it tracks. Th...
Episode 26 — Choose Risk Treatments Wisely: Avoid, Reduce, Transfer, Accept, or Retire (Domain 2)
Selecting the appropriate risk treatment is a strategic decision-making process that determines the ultimate trajectory of an AI project in Domain 2. This episode deta...
Episode 27 — Manage AI Risk Exceptions Safely: Approvals, Time Limits, and Compensating Controls (Domain 2)
Exceptions to AI risk policies are sometimes necessary for innovation or emergency situations, but they must be managed with extreme discipline to prevent them from be...
Episode 28 — Define AI Controls and Testing Plans: What to Verify and How Often (Domain 2)
The effectiveness of any AI risk program rests on the strength of its controls and the rigor of its testing plans, a key area of expertise for Domain 2. This episode d...
Episode 29 — Build Ongoing Monitoring: Drift, Performance, Incidents, and Emerging Threats (Domain 2)
AI risk management does not end at deployment; it requires continuous monitoring to detect the "silent failures" that often plague autonomous systems in Domain 2. This...
Episode 30 — Create Escalation Triggers: When AI Risk Must Go to Leadership (Domain 2)
Knowing when to escalate a technical AI issue to senior leadership is a vital skill that ensures high-stakes risks receive appropriate attention, a focus of Domain 2. ...
Episode 31 — Coordinate Across Teams: Legal, Privacy, Security, Data, and Product Alignment (Domain 2)
Effective AI risk management in Domain 2 requires deep cross-functional coordination, as the risks associated with machine learning often span multiple traditional cor...
Episode 32 — Make AI Vendor Risk Real: Due Diligence, Contracts, and Ongoing Oversight (Domain 2)
As organizations increasingly rely on third-party AI services, managing vendor risk becomes a primary focus of Domain 2. This episode covers the end-to-end vendor mana...
Episode 33 — Plan AI Risk Training That Sticks: Who Needs What and Why (Domain 2)
Training is a vital administrative control in Domain 2, designed to foster a risk-aware culture across the organization. This episode details how to design and deploy ...
Episode 34 — Build Evidence for Audits: Artifacts That Prove Control, Not Intentions (Domain 2)
Auditors require tangible proof of control effectiveness, making the creation of a robust evidence trail a core competency in Domain 2. This episode focuses on the tra...
Episode 35 — Spaced Retrieval Review: Program Management Decisions and Risk Response Recall (Domain 2)
Mastering Domain 2 requires a solid grasp of program management mechanics and the ability to choose the correct risk response under exam pressure. This episode utilize...
Episode 36 — Map the AI Lifecycle Clearly: From Idea to Retirement Without Blind Spots (Domain 3)
Domain 3 requires a granular understanding of the AI lifecycle, from the initial concept and data acquisition stages through to deployment, maintenance, and eventual d...
Episode 37 — Control Data Collection and Consent: Privacy, Purpose Limits, and Minimization (Domain 3)
The integrity of an AI system begins with the data used to build it, making data collection and consent a critical focus for Domain 3. This episode explores the legal ...
Episode 38 — Validate Data Quality Early: Completeness, Accuracy, Labeling, and Lineage (Domain 3)
Data quality is the most significant determinant of AI model performance and reliability, a key principle of Domain 3. This episode covers the technical aspects of dat...
Episode 39 — Detect and Reduce Bias: Representation, Measurement, and Fairness Tradeoffs (Domain 3)
Detecting and mitigating algorithmic bias is one of the most complex and critical tasks in Domain 3. This episode explores the different types of bias that can enter a...
Episode 40 — Manage Sensitive Data Risks: PII, PHI, Secrets, and Proprietary Content (Domain 3)
The use of sensitive data in AI training and inference poses significant security and privacy risks that are central to Domain 3. This episode details the specific haz...