Anonymization and Pseudonymization in Practice: Opportunities, Risks, and Technical Limits
Where data protection meets technology: How secure and compliant data processing works today
Data-driven innovation is at the core of modern AI developments, but organizations face a fundamental challenge: How can data be used effectively while protecting individual privacy?
This event takes a practical look at anonymization and pseudonymization from both a legal and technical perspective. Experts will explore what makes data truly anonymous, where anonymization reaches its technical limits, and how organizations can balance data utility with privacy requirements.
The program combines legal insights, technical approaches, and a live demonstration of anonymization and re-identification. It also looks at the growing privacy challenges associated with AI, including the risk of personal data being unintentionally exposed through AI systems.
Key topics:
Why anonymization is often more difficult than expected
Legal distinctions and implications: anonymization vs. pseudonymization
Technical approaches including k-anonymity, differential privacy, hashing, and tokenization
Re-identification: How real is the risk in practice?
How AI systems can unintentionally expose or leak personal data
Agenda
09:30 Welcome & Introduction
09:35 Legal Perspective: When Is Data Really Anonymous?
10:15 Technical Perspective: How Do You Actually Anonymize Data?
10:55 Coffee Break
11:10 Live Demo: What Is Really Anonymous? – Practical demonstration of anonymization, re-identification and the risks involved
11:30 Contribution Sharon Wulff, M&AI
11:55 Closing Words
12:00 Lunch and Networking