125. Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety?

125. Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety?

Author: The TDS team September 7, 2022 Duration: 48:19

It’s no secret that the US and China are geopolitical rivals. And it’s also no secret that that rivalry extends into AI — an area both countries consider to be strategically critical.

But in a context where potentially transformative AI capabilities are being unlocked every few weeks, many of which lend themselves to military applications with hugely destabilizing potential, you might hope that the US and China would have robust agreements in place to deal with things like runaway conflict escalation triggered by an AI powered weapon that misfires. Even at the height of the cold war, the US and Russia had robust lines of communication to de-escalate potential nuclear conflicts, so surely the US and China have something at least as good in place now… right?

Well they don’t, and to understand the reason why — and what we should do about it — I’ll be speaking to Ryan Fedashuk, a Research Analyst at Georgetown University’s Center for Security and Emerging Technology and Adjunct Fellow at the Center for a New American Security. Ryan recently wrote a fascinating article for Foreign Policy Magazine, where he outlines the challenges and importance of US-China collaboration on AI safety. He joined me to talk about the U.S. and China’s shared interest in building safe AI, how reach side views the other, and what realistic China AI policy looks like on this episode of the TDs podcast.


While the active production of Towards Data Science has concluded, its archive remains a vital resource. Created by The TDS team, this collection captures a specific moment in the rapid evolution of data science and artificial intelligence. Each conversation pulls you directly into the room with leading researchers and practitioners who were shaping the tools and theories of their time. The discussions are not abstract lectures; they are grounded explorations of real-world problems, ethical dilemmas, and technical challenges that defined the field's trajectory. You'll hear experts dissect the implications of their work, from algorithmic fairness to the practicalities of deploying models at scale. This podcast served as a forum for nuanced debate, where complex ideas were unpacked with clarity and depth. Listening now offers a unique historical perspective, a chance to understand the foundational conversations that continue to influence where technology is headed next. The archive of Towards Data Science stands as a substantive record of insight, preserving the voices and questions from the forefront of a digital revolution.
Author: Language: en-us Episodes: 50

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