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Duration 14 hours
Course Outline
Shifts in Decision-Making: From Human Judgment to Models
- Transitioning from rule-based and human judgments to scored algorithmic options
- Increased speed and scale of automated actions
- Emerging failure modes and gaps in accountability
Decision Inventory and Risk Categorization
- Mapping out automated decision points
- Assessing impact, reversibility, and affected stakeholders
- Defining risk tiers and corresponding control requirements
- Assigning ownership for each decision class
Accountability and Human Oversight Mechanisms
- Distinguishing between meaningful and nominal human review
- Setting autonomy thresholds as a governance strategy
- Defining escalation pathways and response time standards
- Identifying the accountable owner and final sign-off authority
Decision Records and Explainability Standards
- Components of a defensible decision record
- Retaining data on confidence levels, options considered, and context
- Ensuring traceability of model versions and iterations
- Communicating decision logic to customers or regulators
Policy Management and Boundary Controls
- Managing approved option sets and implementing change controls
- Governing thresholds and conducting periodic reviews
- Establishing prohibited decisions and hard stops
- Implementing policy as code alongside model outputs
Regulatory Compliance Requirements
- EU AI Act obligations applicable to decision systems
- Specific sector regulations in finance, insurance, and healthcare
- Data protection laws and rights regarding automated decisions
- Preparing documentation and evidence of conformity
Risks in Vendor Selection, Licensing, and Provenance
- Comparing hosted decision APIs with open-weight models
- Navigating license terms for derivative and embedded models
- Assessing supplier dependency and discontinuation risks
- Ensuring weight integrity and version pinning
Bias, Fairness, and Outcome Monitoring
- Tracking outcome disparities across different groups
- Identifying proxy variables and issues with option framing
- Analyzing appeal and complaint signals
- Conducting regular fairness reviews
Incident Response for Incorrect Decisions
- Detecting systematic errors in decision-making
- Implementing containment measures and suspending autonomy
- Executing remediation and providing customer redress
- Identifying root causes and updating controls
Assurance Review of the Decision Layer
- Evidentiary requirements for auditors
- Verifying accuracy and calibration claims through testing
- Sampling decisions and manual overrides
- Reporting findings and insights to the board
Requirements
- Basic familiarity with AI or automation initiatives in a corporate environment.
- Knowledge of risk, compliance, or audit workflows.
- No programming skills are necessary.
Intended Audience
- Risk, compliance, and model risk officers
- Internal auditors responsible for reviewing automated decisions
- Leads in AI governance and data protection
- Product owners with accountability for automated workflows
- Architects responsible for integrating oversight into agent systems
