Episode Overview

Good AI governance is built into the lifecycle, not added at the end. This episode of Checks & Algorithms walks through the four phases of AI development, Planning, Design, Development, and Implementation, and the governance, privacy, testing, and monitoring controls that belong in each. It is designed for candidates preparing for the IAPP AIGP certification and for leaders responsible for governing AI from idea to production.

Topics Covered

• Phase 1, Planning: Defining the business case, scope, and requirements; setting up governance roles, cross-functional oversight, and risk tolerance; and running an early impact assessment to confirm AI is the right solution, identify applicable laws, and map risks.
• Phase 2, Design: Data strategy and governance, including lawful collection, quality, provenance, and lineage; data cleansing and representative labeling; privacy by design through minimization, anonymization, synthetic data, federated learning, and differential privacy; and model selection, including the trade-off between accuracy and explainability.
• Phase 3, Development: Feature engineering that avoids spurious correlations and historical bias; model training across learning approaches; and testing, evaluation, verification, and validation (TEVV), covering performance, security, bias, fairness, and interpretability, with counterfactual explanations and documented results.
• Phase 4, Implementation: Readiness assessments, model cards, and conformity requirements before release; deployment to cloud, on-premise, or edge environments with human oversight; monitoring for model and data drift; champion and challenger models; ongoing red teaming and security testing; and clear procedures to roll back or deactivate a model when it fails.

Intended Audience

• AIGP Candidates: Coverage aligned with the AIGP body of knowledge on governing AI development and the AI system lifecycle.
• Data Science and ML Engineering Managers: Practical ways to build privacy, security, and ethics checks into MLOps pipelines.
• Risk, Audit, and Compliance Professionals: A clear view of model card expectations, TEVV, and post-deployment monitoring.

Checks & Algorithms is a podcast on AI governance, covering the policies, standards, and accountability practices shaping artificial intelligence.