Course overview

This course explores the challenges of complying with the Protection of Personal Information Act (POPIA) in the context of artificial intelligence (AI). It provides a systematic approach to lawful processing, risk management, and the integration of AI technologies. Drawing from comprehensive guidance, the course covers the 11 assurance objectives, practical tools, and case studies to help organizations embed data protection into their operations, ensuring accountability and resilience in high-risk scenarios.

Course objectives

Participants will obtain an understanding of :

1. Understand POPIA Fundamentals: Articulate POPIA's eight conditions for lawful processing and their application to AI.
2. Apply Assurance Objectives: Implement the 11 objectives, including accountability, minimization, and system intervenability.
3. Manage AI Risks: Identify and mitigate risks like bias, model drift, and adversarial attacks in AI-driven processing.
4. Conduct Assessments: Perform Personal Information Impact Assessments (PIIAs) for high-risk activities.
5. Fulfill Information Officer Duties: Navigate responsibilities, documentation, and potential liabilities.
6. Leverage Compliance Tools: Utilize systems for tracking, monitoring, and managing data subject requests.

Course outline

Participants will learn about:

Module 1: Introduction to POPIA and AI Challenges

POPIA Overview: Constitutional roots and eight conditions for lawful processing.

AI Integration Risks: Bias, profiling, and automated decisions.

Module 2: The Compliance Cycle

Develop, Implement, Monitor, Maintain: Structured framework for ongoing compliance.

11 Assurance Objectives: Detailed breakdown, focusing on AI-specific applications.

Module 3: Risk Management and Assessments

Risk Identification: Threats in AI processing and evaluation levels.

PIIAs and Prior Authorization: Regulation 4(1)(b) requirements for high-risk activities.

Module 4: Documentation and Accountability

Record-Keeping: Inventories, risk registers, and PAIA manuals.

Information Officer Role: Duties, liabilities, and personal accountability.

Module 5: Practical Tools and Case Studies

Compliance Systems: Tools for managing activities, risks, and requests.

Real-World Examples: Retail bank AI fraud detection case study.

Module 6: Building a Data Protection Culture

Proactive Measures: Embedding protection in AI design and operations.

Continuous Adaptation: Monitoring and evolving with AI advancements.