Daniel Kahneman: Thinking Fast and Slow, Deep Learning, and AI

Daniel Kahneman is winner of the Nobel Prize in economics for his integration of economic science with the psychology of human behavior, judgment and decision-making. He is the author of the popular book "Thinking, Fast and Slow" that summarizes in an accessible way his research of several decades, often in collaboration with Amos Tversky, on cognitive biases, prospect theory, and happiness. The central thesis of this work is a dichotomy between two modes of thought: "System 1" is fast, instinctive and emotional; "System 2" is slower, more deliberative, and more logical. The book delineates cognitive biases associated with each type of thinking.

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, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), 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 02:36 - Lessons about human behavior from WWII 08:19 - System 1 and system 2: thinking fast and slow 15:17 - Deep learning 30:01 - How hard is autonomous driving? 35:59 - Explainability in AI and humans 40:08 - Experiencing self and the remembering self 51:58 - Man's Search for Meaning by Viktor Frankl 54:46 - How much of human behavior can we study in the lab? 57:57 - Collaboration 1:01:09 - Replication crisis in psychology 1:09:28 - Disagreements and controversies in psychology 1:13:01 - Test for AGI 1:16:17 - Meaning of life https://lexfridman.com/daniel-kahneman/?utm_source=rss&utm_medium=rss&utm_campaign=daniel-kahneman

Created 2y | Jun 21, 2023, 7:35:17 PM


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