The Intersection of AI and Regulation How Organisations and Regulators Should...
summary
Panel lays out concrete frictions and fixes: the AI Act creates sandbox legal basis to repurpose training data and an Article 10(5) bias exemption allowing sensitive-data use only for bias detection, while gaps remain between provider/deployer roles and GDPR controller rules. Industry examples include a contractual trust layer that forbids LLM providers from retaining customer prompts and a Data Cloud service to select minimized, high‑quality training data. Regulators form task forces (EDPB ChatGPT work) and plan joint guidance to coordinate enforcement across 38 OECD members and 47 adherents.
AI-written summary · about
chapters (9)
- 0:00AI regulation and privacy
- 3:15Global AI governance
- 15:25GDPR and EU AI Act
- 25:55Regulatory enforcement challenges
- 34:57Company compliance and innovation
- 44:08GDPR lessons for AI
- 52:00AI accountability programs
- 1:01:58EU and OECD AI-Privacy
- 1:10:01Closing remarks
related talks
01h 08mTHE GOVERNANCE OF AI: CONVERGENCE OR DIVERGENCE?
01h 09mGOVERNANCE AND REGULATION OF AI FROM THE PERSPECTIVE OF AUTONOMY AND PRIVACY
01h 14mNavigating regulatory complexities Enforcing data protection in the field of AI
31mPanel: Navigating the AI Policy Landscape
01h 10mNavigating the Interface Between the AI Act and GDPR Combining Innovation and ..
01h 06mEMPOWERING THE AI ACT: LIMITS AND OPPORTUNITIES
30mAI & Data Protection: Regulation as Brake or Accelerator?
53m10 Key Challenges for AI within the EU Data Protection Framework