Charles Isbell: Computing, Interactive AI, and Race in America | Lex Fridman Podcast #135

ℹ️ EPISODE INFO

Released

November 2, 2020

Duration

2h 23m

Channel

Lex Fridman Podcast

Watch on YouTube

▶ Open ↗

📝 EPISODE DESCRIPTION

Charles Isbell is the Dean of the College of Computing at Georgia Tech. Please support this podcast by checking out our sponsors:

• Neuro: https://www.getneuro.com and use code LEX to get 15% off
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• Cash App: https://cash.app/ and use code LexPodcast to get $10

EPISODE LINKS: Charles's Twitter: https://twitter.com/isbellHFh Charles's Website: https://www.cc.gatech.edu/~isbell/ PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 OUTLINE: 0:00 - Introduction 2:36 - Top 3 movies of all time 8:45 - People are easily predictable 14:27 - Breaking out of our bubbles 26:13 - Interactive AI 32:45 - Lifelong machine learning 41:12 - Faculty hiring 48:47 - University rankings 56:15 - Science communicators 1:05:39 - Hip hop 1:14:39 - Funk 1:16:03 - Computing 1:31:55 - Race 1:47:59 - Cop story 1:56:20 - Racial tensions 2:05:42 - MLK vs Malcolm X 2:09:03 - Will human civilization destroy itself? 2:13:34 - Fear of death and the passing of time CONNECT:

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🎤 SPEAKERS

• Lex Fridman

  host

• Charles Isbell

  guest

• Narrator

  other

🧾 EPISODE SUMMARY

In this episode of Lex Fridman Podcast, featuring Lex Fridman and Charles Isbell, Charles Isbell: Computing, Interactive AI, and Race in America | Lex Fridman Podcast #135 explores interactive AI, human behavior, and race: Charles Isbell’s perspective Lex Fridman and Charles Isbell explore the nature of computing, interactive AI, and how human behavior shapes and is shaped by technology. Isbell frames computing as a discipline defined by executable models, languages, and machines, and emphasizes that real intelligence is inherently social and adaptive over long timescales. They discuss how data reveals human predictability, how AI might help bridge ideological divides by highlighting commonalities, and why education in computing must teach ways of thinking, not just coding. Woven throughout are frank reflections on race in America, policing, academia’s structures and rankings, and how empathy and narrative shape both injustice and progress.

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