How To Handle AI Anxiety: A Computer Scientist and a Buddhist Teacher On Managing Uncertainty | Cal Newport & Matthew Brensilver
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Episode Description
Will AI take our jobs? Kill us? This episode provides both fact-checking and a psychological survival guide.
Cal Newport is a Professor of Computer Science at Georgetown University, where he is also a founding faculty member of the Center for Digital Ethics and the inaugural Director of the Computer Science, Ethics and Society academic program. He is the New York Times bestselling author of eight books, including, most recently, Slow Productivity, A World Without Email, Digital Minimalism, and Deep Work. Newport is also a long-time contributing writer for the New Yorker and the host of the Deep Questions podcast.
Matthew Brensilver, MSW, PhD teaches retreats at the Insight Retreat Center, Spirit Rock Meditation Center and Insight Meditation Society. Before committing to teach meditation full-time, he spent years doing research on addiction pharmacotherapy at the UCLA Center for Behavioral and Addiction Medicine. Each winter and summer, he offers a four-month online Buddhist Psychology Training through Spirit Rock integrating Buddhist wisdom with modern psychotherapy. Matthew is the co-author of two books about meditation during adolescence and continues to be interested in the unfolding dialogue between Buddhism and science.
In this episode we talk about:
- What really happened when an AI agent hacked a company while running a test
- Why one Silicon Valley belief system may be fueling AI panic more than the tech itself
- Why senior programmers are quietly going back to writing code by hand
- Where Cal draws the line on using AI to help you write versus write for you
- Why Matthew worries AI could quietly replace the ordinary, unfinished parts of daily life
- Buddhist advice on being with this unprecedented moment
- How stabilizing your mind makes acceptance possible, and how to do it
- Why calming the sense of emergency doesn't erase uncertainty, but makes it easier to face
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