Episode 29: Beyond Optimization: Building Better AI for People
Are you ready for a new era of business transformation, driven by empathy and ethics? Lukas Egger invites Joel Lehman to spotlight the transformative potential, and risks, of AI as it becomes a trusted partner in our daily lives. This episode unpacks how AI can foster connection, enhance trust, and…
Sangeet Paul Choudary — AI and our System Reshuffle (EP.282)
Sangeet Paul Choudary, bestselling author of Platform Revolution and Reshuffle, and senior fellow at UC Berkeley, joins the show to challenge the conventional wisdom about AI's impact on our economy. We explore why knowledge workers risk falling "below the algorithm," how curiosity and judgment bec…
Kenneth Stanley — The Trap of the Objective (EP.288)
Ken Stanley – AI researcher and author of "Why Greatness Cannot Be Planned" – joins me to explore why ambitious objectives can blind us to the stepping stones that make breakthroughs possible. Ken is the inventor of the novelty search algorithm and co-creator of Picbreeder, a crowdsourced evolution…
Iason Gabriel: Value Alignment and the Ethics of Advanced AI Systems
Episode 143
I spoke with Iason Gabriel about:
* Value alignment
* Technology and worldmaking
* How AI systems affect individuals and the social world
Iason is a philosopher and Senior Staff Research Scientist at Google DeepMind. His work focuses on the ethics of artificial intelligence, including q…
How to actually achieve greatness (Why Greatness Cannot Be Planned by Joel Lehman and Kenneth Stanley)
Lessons from reading Why Greatness Cannot Be Planned by Joel Lehman and Kenneth Stanley.
University Design: “Interestingness” with David J. Staley
In this episode, David J. Staley reads his latest CHELIP: University Design column, “Interestingness,” inspired by Kenneth O. Stanley and Joel Lehman’s Why Greatness Cannot Be Planned: The Myth of the Objective.
What if the pursuit of clearly defined objectives is actually the enemy of breakthrough…
Sam Arbesman: Complex Systems, Code, and Human Understanding | Episode 167
Sam Arbesman is a complexity scientist, writer, and Scientist in Residence at Lux Capital, known for his books The Half-Life of Facts, Overcomplicated, and The Magic of Code. In this episode, we explore human understanding, its limits, the power and unpredictability of technology, our relationship …
Derek Sivers - Living Many Lives: Parenting, Moving Countries & AI (Ep. 329)
Derek Sivers, author, entrepreneur, TED speaker, and founder of CD Baby, joins Jim O'Shaughnessy on Infinite Loops to talk about parenting a teenager who is ready to leave home, why he moves countries on purpose and plans to live in Bangalore and Shanghai next, the certainty slider, and how AI can …
What Most People Get Wrong About Evolution | Akarsh Kumar
A lot of people in AI treat evolution as a dumb fallback, basically random search for when you can't take a gradient. Akarsh Kumar thinks that is wrong. Selection hangs on to partial solutions, so mutations only need to be useful about 1% of the time for the search to keep making progress.Akarsh is…
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