111. Mo Gawdat - Scary Smart: A former Google exec’s perspective on AI risk

111. Mo Gawdat - Scary Smart: A former Google exec’s perspective on AI risk

Author: The TDS team January 26, 2022 Duration: 1:00:12

If you were scrolling through your newsfeed in late September 2021, you may have caught this splashy headline from The Times of London that read, “Can this man save the world from artificial intelligence?”. The man in question was Mo Gawdat, an entrepreneur and senior tech executive who spent several years as the Chief Business Officer at GoogleX (now called X Development), Google’s semi-secret research facility, that experiments with moonshot projects like self-driving cars, flying vehicles, and geothermal energy. At X, Mo was exposed to the absolute cutting edge of many fields — one of which was AI. His experience seeing AI systems learn and interact with the world raised red flags for him — hints of the potentially disastrous failure modes of the AI systems we might just end up with if we don’t get our act together now.

Mo writes about his experience as an insider at one of the world’s most secretive research labs and how it led him to worry about AI risk, but also about AI’s promise and potential in his new book, Scary Smart: The Future of Artificial Intelligence and How You Can Save Our World. He joined me to talk about just that 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

Towards Data Science
Podcast Episodes
127. Matthew Stewart - The emerging world of ML sensors [not-audio_url] [/not-audio_url]

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126. JR King - Does the brain run on deep learning? [not-audio_url] [/not-audio_url]

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122. Sadie St. Lawrence - Trends in data science [not-audio_url] [/not-audio_url]

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121. Alexei Baevski - data2vec and the future of multimodal learning [not-audio_url] [/not-audio_url]

Duration: 49:31
If the name data2vec sounds familiar, that’s probably because it made quite a splash on social and even traditional media when it came out, about two months ago. It’s an important entry in what is now a growing list of s…