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Divyansh Kaushik: The Realities of AI Policy

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Contenido proporcionado por The Gradient. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente The Gradient o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

In episode 94 of The Gradient Podcast, Daniel Bashir speaks to Divyansh Kaushik.

Divyansh is the Associate Director for Emerging Technologies and National Security at the Federation of American Scientists where his focus areas include, amongst other things, AI policy, STEM immigration, and US-China strategic competition. He holds a PhD from Carnegie Mellon University, where he focused on designing reliable AI systems that align with human values. In addition to his advocacy work on Capitol Hill, he also played a key role in establishing the Congressional Graduate Research and Development Caucus. He is a frequent contributor to leading publications, including Vox, National Defense Magazine, The Dispatch, Daily Caller, and Forbes.

Have suggestions for future podcast guests (or other feedback)? Let us know here or reach us at editor@thegradient.pub

Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSFollow The Gradient on Twitter

Outline:

* (00:00) Intro

* (02:20) Divyansh intro/background

* (06:00) Zachary Lipton Appreciation Session ( + advice from Prof Lipton)

* (08:00) How Divyansh got involved in policy

* (11:30) What does policy work look like? Divyansh’s early experiences

* (15:42) AI policy issues, divides, party lines

* (19:15) Bringing AI talent into the US

* (26:45) US/China saber rattling, impact of Xi Jinping’s presidency

* (33:49) China’s AI regulations, CCP motivations, China’s disadvantages in AI and benefits of the US policy process

* (42:42) Trading off AI governance and stifling innovation

* (51:17) AI governance comments from Jeremy Howard / Connor Leahy / Andrew Maynard, regulating use vs basic technology, limits on scaling

* (1:01:30) Articulating and communicating the issues for AI governance

* (1:03:10) Existential risk concerns in AI governance, theories of change

* (1:10:15) How can AI researchers/practitioners better communicate with policymakers?

* (1:16:57) Outro

Links:

* Divyansh’s Twitter and FAS page

* Divyansh’s policy work:

* The impact of international scientists, engineers, and students on US research outputs and global competitiveness

* How Congress can shape AI governance without stifling innovation

* How Do OpenAI’s Efforts To Make GPT-4 “Safer” Stack Up Against The NIST AI Risk Management Framework?

* Six Policy Ideas for the National AI Strategy

* Other work mentioned/discussed:

* Jeremy Howard’s AI Safety and the Age of Dislightenment

* Proposals from Connor Leahy

* Andrew Maynard’s Regulating Frontier AI: To Open Source or Not?


Get full access to The Gradient at thegradientpub.substack.com/subscribe
  continue reading

135 episodios

Artwork
iconCompartir
 
Manage episode 379589894 series 2975159
Contenido proporcionado por The Gradient. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente The Gradient o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

In episode 94 of The Gradient Podcast, Daniel Bashir speaks to Divyansh Kaushik.

Divyansh is the Associate Director for Emerging Technologies and National Security at the Federation of American Scientists where his focus areas include, amongst other things, AI policy, STEM immigration, and US-China strategic competition. He holds a PhD from Carnegie Mellon University, where he focused on designing reliable AI systems that align with human values. In addition to his advocacy work on Capitol Hill, he also played a key role in establishing the Congressional Graduate Research and Development Caucus. He is a frequent contributor to leading publications, including Vox, National Defense Magazine, The Dispatch, Daily Caller, and Forbes.

Have suggestions for future podcast guests (or other feedback)? Let us know here or reach us at editor@thegradient.pub

Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSFollow The Gradient on Twitter

Outline:

* (00:00) Intro

* (02:20) Divyansh intro/background

* (06:00) Zachary Lipton Appreciation Session ( + advice from Prof Lipton)

* (08:00) How Divyansh got involved in policy

* (11:30) What does policy work look like? Divyansh’s early experiences

* (15:42) AI policy issues, divides, party lines

* (19:15) Bringing AI talent into the US

* (26:45) US/China saber rattling, impact of Xi Jinping’s presidency

* (33:49) China’s AI regulations, CCP motivations, China’s disadvantages in AI and benefits of the US policy process

* (42:42) Trading off AI governance and stifling innovation

* (51:17) AI governance comments from Jeremy Howard / Connor Leahy / Andrew Maynard, regulating use vs basic technology, limits on scaling

* (1:01:30) Articulating and communicating the issues for AI governance

* (1:03:10) Existential risk concerns in AI governance, theories of change

* (1:10:15) How can AI researchers/practitioners better communicate with policymakers?

* (1:16:57) Outro

Links:

* Divyansh’s Twitter and FAS page

* Divyansh’s policy work:

* The impact of international scientists, engineers, and students on US research outputs and global competitiveness

* How Congress can shape AI governance without stifling innovation

* How Do OpenAI’s Efforts To Make GPT-4 “Safer” Stack Up Against The NIST AI Risk Management Framework?

* Six Policy Ideas for the National AI Strategy

* Other work mentioned/discussed:

* Jeremy Howard’s AI Safety and the Age of Dislightenment

* Proposals from Connor Leahy

* Andrew Maynard’s Regulating Frontier AI: To Open Source or Not?


Get full access to The Gradient at thegradientpub.substack.com/subscribe
  continue reading

135 episodios

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