Course overview

This course is designed to equip professionals with the knowledge and practical skills needed to implement the Protection of Personal Information Act (POPIA) within their organizations. Focused on the POPIA Compliance Management System (PCMS), this course provides a structured framework to translate POPIA's legal requirements into actionable, operational steps. Participants will explore the 11 key assurance objectives that form the backbone of the PCMS, learning how to embed data protection into day-to-day operations across various activities, including standard operations, marketing, handling sensitive information, and AI-driven processes.

Course objectives

Participants will obtain an understanding of :

• Understand the core requirements of POPIA and their relevance to organizational data processing activities.
• Apply the 11 key assurance objectives of the PCMS to ensure compliance with POPIA.
• Implement technical and organizational measures to address data protection risks across the personal information lifecycle.
• Develop strategies for managing sensitive data, such as health records or children’s information, in compliance with POPIA’s stricter requirements.
• Address the challenges of AI and algorithmic processing, ensuring fairness, transparency, and human oversight.
• Conduct Personal Information Impact Assessments (PIIAs) and maintain robust documentation to demonstrate compliance.
• Foster a proactive culture of data protection through continuous monitoring and refinement of compliance practices.

Course outline

Participants will learn about:

Module 1: Introduction to POPIA and the Compliance Management System

Overview of POPIA and its significance in data protection.

Introduction to the POPIA Compliance Management System (PCMS) as a continuous cycle of development, implementation, monitoring, and maintenance.

Understanding the role of the 11 key assurance objectives as operational pillars for compliance.

Module 2: Exploring the 11 Key Assurance Objectives

Accountability: Demonstrating compliance through due diligence and documentation (Section 8).

Lawful and Fair Processing: Ensuring a legal basis for all data processing and preventing unfair or biased outcomes (Sections 9, 11, 71).

Data Minimization: Collecting and processing only essential personal information to reduce risk (Sections 10, 13, 14).

Disassociability: Preventing unauthorized linking of data across purposes (Sections 13, 15).

Integrity, Confidentiality, and Availability: Securing personal information against tampering, unauthorized access, and ensuring accessibility for legitimate use (Section 19).

Transparency: Providing clear information to data subjects about data usage (Sections 17, 18).

Data Subject Controllability: Enabling individuals to exercise their rights, such as access, correction, and objection (Sections 23–25, 71).

Resilience: Building robust systems to withstand and recover from incidents (Section 19).

System Intervenability: Ensuring human oversight in automated decision-making processes, particularly AI (Section 71).

Module 3: Applying the Objectives in Practice

Case Study: Using personal information for marketing.

Managing consent and opt-out processes (Section 69).

Implementing data minimization in marketing campaigns.

Case Study: Handling sensitive data (e.g., health records, children’s information).

Applying strict confidentiality measures, such as encryption and role-based access (Sections 27, 35).

Using pseudonymization and anonymization techniques.

Case Study: AI-driven processing (e.g., job applicant screening, credit scoring).

Mitigating algorithmic bias through testing and fairness-aware techniques.

Ensuring transparency and intervenability with explainable AI tools (Section 71).

Module 4: Risk-Based Approach and Documentation

Conducting Personal Information Impact Assessments (PIAs) to identify and mitigate risks.

Maintaining detailed records of processing activities and audit logs (Section 17).

Building a culture of accountability through continuous documentation and policy updates.

Module 5: Adapting to Technological Advancements

Addressing the evolving risks of AI and complex data processing.

Ensuring ongoing compliance through dynamic application of the PCMS framework.

Strategies for continuous monitoring, staff training, and system resilience to safeguard individual rights in a rapidly changing digital landscape.