10 Key Challenges for AI within the EU Data Protection Framework
summary
Conference session lists ten concrete problems uniting the AI Act and GDPR and shows why they collide: differing scopes and fines (up to 35 million under the AI Act vs 20 million under GDPR), unclear legal basis for training sets, impossible deletion after model training, and unpredictable inferential data that can reveal sensitive traits. Remedies discussed include DPIAs with ethical impact layers, ISO/NIST alignment, use of differential privacy, validity codes for authenticity, and an Oxford conformity self‑check by Luciano Floridi’s team.
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chapters (13)
- 0:00Introduction and scope
- 3:55Legislative approaches
- 6:54Risk assessment frameworks
- 13:02Accountability and governance
- 15:28Data subject rights
- 20:08Purpose and legal basis
- 22:35GDPR compliance case study
- 25:41Inferential data challenges
- 31:48Transparency in AI
- 34:04Accuracy and deepfakes
- 37:40Managing AI bias
- 42:09Operational responsibilities
- 44:26Q&A and concluding remarks
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