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Miles Brundage on AI Misuse and Trustworthy AI

Miles Brundage on AI Misuse and Trustworthy AI

FromThe Gradient: Perspectives on AI


Miles Brundage on AI Misuse and Trustworthy AI

FromThe Gradient: Perspectives on AI

ratings:
Length:
54 minutes
Released:
Nov 23, 2021
Format:
Podcast episode

Description

In episode 17 of The Gradient Podcast, we talk to Miles Brundage, Head of Policy Research at OpenAI and a researcher passionate about the responsible governance of artificial intelligence. Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSLinks:* Will Technology Make Work Better for Everyone?* Economic Possibilities for Our Children: Artificial Intelligence and the Future of Work, Education, and Leisure* Taking Superintelligence Seriously* The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation* Release Strategies and the Social Impact of Language Models* All the News that’s Fit to Fabricate: AI-Generated Text as a Tool of Media Misinformation* Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable ClaimsTimeline:(00:00) Intro(01:05) How did you get started in AI(07:05) Writing about AI on Slate(09:20) Start of PhD(13:00) AI and the End of Scarcity(18:12) Malicious Uses of AI(28:00) GPT-2 and Publication Norms(33:30) AI-Generated Text for Misinformation(37:05) State of AI Misinformation(41:30) Trustworthy AI(48:50) OpenAI Policy Research Team(53:15) OutroMiles is a researcher and research manager, and is passionate about the responsible governance of artificial intelligence. In 2018, he joined OpenAI, where he began as a Research Scientist and recently became Head of Policy Research. Before that, he was a Research Fellow at the University of Oxford's Future of Humanity Institute, where he is still a Research Affiliate).He also serves as a member of Axon's AI and Policing Technology Ethics Board. He completed a PhD in Human and Social Dimensions of Science and Technology from Arizona State University in 2019.Podcast Theme: “MusicVAE: Trio 16-bar Sample #2” from "MusicVAE: A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music"Hosted by Andrey Kurenkov (@andrey_kurenkov), a PhD student with the Stanford Vision and Learning Lab working on learning techniques for robotic manipulation and search. Get full access to The Gradient at thegradientpub.substack.com/subscribe
Released:
Nov 23, 2021
Format:
Podcast episode

Titles in the series (100)

Interviews with various people who research, build, or use AI, including academics, engineers, artists, entrepreneurs, and more. thegradientpub.substack.com