The risk-based approach to privacy: How far should we go?
summary
GDPR already uses the word "risk" about 70–80 times and makes privacy impact assessments mandatory for high‑risk processing; anonymization is inherently risk‑based (four geolocations can reidentify someone in 10M records; five–six apps or unique web histories also reidentify). Technical tools discussed include k‑anonymity, differential privacy and machine‑learning reidentification attacks. Recommendations: third‑party, periodically re‑evaluated audits; limit high‑risk purposes; calibrate enforcement not replace legal rights; develop standardized risk metrics and public participation in impact assessment.
AI-written summary · about
chapters (5)
- 0:00Introduction to the panel
- 4:56Risk management in practice
- 18:03Technical views on privacy
- 32:09Legal and regulatory theory
- 50:13Broader perspectives and wrap-up
related talks
09mPrivacy Analytics and De-Identification
15mDe-identified, Anonymized, or Aggregated? A Look around the Globe
01h 06mRisking Fundamental Rights The Myriad Ways of Risk in EU Law and Policy
15mThe Missing Link in Privacy Risk Assessments
40mData Privacy and Security by Design
50mData Privacy Concerns - A Risk Based Approach to De-Identification
01h 14mSenior Academic Session I
27mThe ethical algorithm