
Paul Krugman: Economics of Innovation, Automation, Safety Nets & Universal Basic Income
Hosted by Lex Fridman
- 1h 3m
- Transcript
About this episode
Paul Krugman is a Nobel Prize winner in economics, professor at CUNY, and columnist at the New York Times. His academic work centers around international economics, economic geography, liquidity traps, and currency crises. This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter https://twitter.com/lexfridman, LinkedIn https://www.linkedin.com/in/lexfridman/, Facebook https://www.facebook.com/lexfridman, Medium https://medium.com/@lexfridman, or YouTube https://www.youtube.com/lexfridman where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts https://podcasts.apple.com/us/podcast/artificial-intelligence/id1434243584, follow on Spotify https://open.spotify.com/show/2MAi0BvDc6GTFvKFPXnkCL, or support it on Patreon https://www.patreon.com/lexfridman. This episode is presented by Cash App. Download it (App Store https://apps.apple.com/us/app/cash-app/id711923939, Google Play https://play.google.com/store/apps/details?id=com.squareup.cash&hl=en_US), use code “LexPodcast”. Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. 00:00 – Introduction 03:44 – Utopia from an economics perspective 04:51 – Competition 06:33 – Well-informed citizen 07:52 – Disagreements in economics 09:57 – Metrics of outcomes 13:00 – Safety nets 15:54 – Invisible hand of the market 21:43 – Regulation of tech sector 22:48 – Automation 25:51 – Metric of productivity 30:35 – Interaction of the economy and politics 33:48 – Universal basic income 36:40 – Divisiveness of political discourse 42:53 – Economic theories 52:25 – Starting a system on Mars from scratch 55:11 – International trade 59:08 – Writing in a time of radicalization and Twitter mobs
Transcript
9,374 words · 3 speakers
Speaker names marked are inferred from speaking time and the show’s known hosts — they are not voice-verified.
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