Matt Beane - How to Save Human Ability in the Age of Intelligent Machines - The Skills Code

In this episode, Matt Beane - How to Save Human Ability in the Age of Intelligent Machines - The Skills Code, Lauren Hawker Zafer is joined by Matt Beane.

Lauren and Matt shape an accessible conversation around the future of work and what it means to be human in a world of intelligent machines.

Who is Matt Beane?

Matt Beane does field research on work involving robots and AI to uncover systematic positive exceptions that we can use across the broader world of work. His award-winning research has been published in top management journals such as Administrative Science Quarterly and Harvard Business Review, and he graced the TED stage.

He also took a two-year hiatus from his PhD at MIT’s Sloan School of Management to help found and fund Humatics, a full-stack IoT startup. In 2012 he was selected as a Human-Robot Interaction Pioneer, and in 2021 was named to the Thinkers50 Radar list.

Beane is an assistant professor in the Technology Management department at the University of California, Santa Barbara, and a Digital Fellow with Stanford’s Digital Economy Lab and MIT’s Initiative on the Digital Economy. When he’s not studying intelligent technologies and learning, he enjoys playing guitar; his morning coffee ritual with his wife, Kristen; and reading science fiction.

“If you’re worried about your skills becoming obsolete, this book may be your saving grace. Matt Beane has spent his career studying how to gain and maintain expertise as technology evolves, and his analysis is both engrossing and edifying.” —Adam Grant, #1 New York Times bestselling author of Hidden Potential and Think Again, and host of the TED podcast WorkLife

“Beane shows us the true human-centered approach to AI advancements and how we must act now to achieve the next generation of human skills coupled with the productivity gains from AI.” —Fei Fei Li, Sequoia Professor of Computer Science, Founding, Director of Stanford Institute for Human-centered AI (HAI), Stanford University

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