World Model · podcast knowledge graph

#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS

2022-12-26 · 14 min · episode 94 · 15 entities

episode page audio

Asserted relationships

  • 0.77
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://amazon.co.uk/Does-Not-Hate-You-Superintelligence/dp/1474608795
  • 0.77
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://medium.com/@francois.chollet/the-impossibility-of-intelligence-explosion-5be4a9eda6ec
  • 0.77
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://amazon.co.uk/Superintelligence-Dangers-Strategies-Nick-Bostrom/dp/0199678111
  • → references arxiv.org concept
    0.77
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://arxiv.org/abs/cs/0004001
  • → discusses Technology company
    0.40
    evidence rules-v4
    Feed category: Technology
  • → references XBMnOsv9 Pk website
    0.38
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://youtu.be/XBMnOsv9_pk

Entities found in this episode

books 4

  • 0.90
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://amazon.co.uk/Does-Not-Hate-You-Superintelligence/dp/1474608795
  • 0.90
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://amazon.co.uk/Superintelligence-Dangers-Strategies-Nick-Bostrom/dp/0199678111
  • 0.77
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://amazon.co.uk/Does-Not-Hate-You-Superintelligence/dp/1474608795
  • 0.77
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://amazon.co.uk/Superintelligence-Dangers-Strategies-Nick-Bostrom/dp/0199678111

websites 4

  • 0.90
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://medium.com/@francois.chollet/the-impossibility-of-intelligence-explosion-5be4a9eda6ec
  • 0.77
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://medium.com/@francois.chollet/the-impossibility-of-intelligence-explosion-5be4a9eda6ec
  • mentioned XBMnOsv9 Pk website
    0.45
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://youtu.be/XBMnOsv9_pk
  • references XBMnOsv9 Pk website
    0.38
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://youtu.be/XBMnOsv9_pk

concepts 4

  • mentioned arxiv.org concept
    0.90
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://arxiv.org/abs/cs/0004001
  • references arxiv.org concept
    0.77
    evidence rules-v4
    Link in episode "#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS": https://arxiv.org/abs/cs/0004001
  • mentioned ALAN concept
    0.35
    evidence rules-v4
    ALAN
  • mentioned CHAN concept
    0.35
    evidence rules-v4
    CHAN

companys 2

  • mentioned Technology company
    0.50
    evidence rules-v4
    Feed category: Technology
  • discusses Technology company
    0.40
    evidence rules-v4
    Feed category: Technology

podcasts 1

Episode description as stored
Support us! https://www.patreon.com/mlst Alan Chan is a PhD student at Mila, the Montreal Institute for Learning Algorithms, supervised by Nicolas Le Roux. Before joining Mila, Alan was a Masters student at the Alberta Machine Intelligence Institute and the University of Alberta, where he worked with Martha White. Alan's expertise and research interests encompass value alignment and AI governance. He is currently exploring the measurement of harms from language models and the incentives that agents have to impact the world. Alan's research focuses on understanding and controlling the values expressed by machine learning models. His projects have examined the regulation of explainability in algorithmic systems, scoring rules for performative binary prediction, the effects of global exclusion in AI development, and the role of a graduate student in approaching ethical impacts in AI research. In addition, Alan has conducted research into inverse policy evaluation for value-based sequential decision-making, and the concept of "normal accidents" and AI systems. Alan's research is motivated by the need to align AI systems with human values, and his passion for scientific and governance work in this field. Alan's energy and enthusiasm for his field is infectious. This was a discussion at NeurIPS. It was in quite a loud environment so the audio quality could have been better. References: The Rationalist's Guide to the Galaxy: Superintelligent AI and the Geeks Who Are Trying to Save Humanity's Future [Tim Chivers] https://www.amazon.co.uk/Does-Not-Hate-You-Superintelligence/dp/1474608795 The implausibility of intelligence explosion [Chollet] https://medium.com/@francois.chollet/the-impossibility-of-intelligence-explosion-5be4a9eda6ec Superintelligence: Paths, Dangers, Strategies [Bostrom] https://www.amazon.co.uk/Superintelligence-Dangers-Strategies-Nick-Bostrom/dp/0199678111 A Theory of Universal Artificial Intelligence based on Algorithmic Complexity [Hutter] https://arxiv.org/abs/cs/0004001 YT version: https://youtu.be/XBMnOsv9_pk MLST Discord: https://discord.gg/aNPkGUQtc5