On Data Consent, feat. Shayne Longpre | Rabbit Hole Research Appendix 41

In this insightful episode, Shane returns to the show to discuss the delicate balance AI must strike between personalization and universal values. The conversation explores how social media platforms like TikTok and Facebook handle personalization, the implications for AI, and the challenges of maintaining transparency and accountability. 

The discussion also delves into the significance of the robots.txt file for web consent, changes in data availability for AI, and the consequences for academic and research purposes. 

Join us for a philosophical yet pragmatic analysis of AI, data consent, and the evolving digital landscape.

Find me at cristian@ccb.life

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About the Guest:
Shayne Longpre is a PhD Candidate at MIT, where he works on training language models, and understanding their broader social challenges. In particular he investigates their risks, access and transparency, with an emphasis on training data. He leads the Data Provenance Initiative, and co-organized the AI safe harbor open letter (co-signed by 350+ researchers and journalists), advocating for better independent research access to closed models. His work has been covered by the New York Times, the Washington Post, and VentureBeat.

Set-Up:
- Camera: https://amzn.to/3PZVscb (don't laugh)
- Microphone: https://amzn.to/46f3pB5
- Teleprompter Stand: https://amzn.to/3tgS98y
- Telepromter App: https://amzn.to/46jdH31
- Teleprompter Screen:  https://amzn.to/3PNfKFI (yup)
- Headphones: https://amzn.to/46gMSwo

#AI #Personalization #UniversalValues #SocialMedia #TikTok #Facebook #Transparency #Accountability #RobotsTxt #WebConsent #DataAvailability #AcademicResearch #PhilosophicalDiscussion #PragmaticAnalysis #DigitalLandscape