#453 — AI and the New Face of Antisemitism
Sam Harris speaks with Judea Pearl about causality, AI, and antisemitism. They discuss why LLMs won't spawn AGI, alignment concerns in the race for AGI, Pearl's public life after the murder of his son Daniel, the post-October 7th shift toward open anti-Zionism, the overlap between anti-Zionism and antisemitism, the misuse of "Islamophobia," Israel's fracture under Netanyahu, confronting anti-Zionism in universities, and other topics.
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How The American Workforce Got Hooked on Adderall
Over the last few years, users of the popular ADHD drug Adderall have been frustrated by regular shortages in getting their prescriptions filled. Various regulatory and supply chain factors have contributed to the inability of producers to keep up with demand. But this raises the question: why is there so much demand in the first place? How did a significant chunk of the labor force -- from tech workers to Wall Streeters -- begin using the drug as an aid for their work and everyday lives? On this episode of the podcast, we speak with Danielle Carr, an assistant professor at the Institute for Society and Genetics at UCLA, who studies the history of politics of neuroscience and psychology. We discuss the history of this medicine and related medicines, what it does for the people who take it, and how market forces opened the drug up to almost anyone.
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547: How Genes Influence Behavior — with Prof. Jonathan Flint
In this episode, Dr. Jonathan Flint, Professor of Psychiatry and Biobehavioral Sciences at the University of California Los Angeles, joins us to discuss how he uses data science and machine learning to explore the link between genetics and depression.
In this episode you will learn:
Johnathan's background [2:53]
How we know that genetics plays a role in complex human behaviors including psychiatric disorders like anxiety, depression, and schizophrenia [8:00]
The role that data science and ML play in modern genetics research [15:08]
About Jonathan book "How Genes Influence Behavior" [19:45]
The day-to-day life of a world-class medical sciences researcher [32:24]
The open-source software libraries that Jonathan uses for data modeling [40:33]
A single question you can ask to prevent a severely depressed person from committing suicide [52:00]
LinkedIn Q&A [54:41]
The future of psychiatric treatments [1:05:35]
Additional materials: www.superdatascience.com/547
Judea Pearl: Causal Reasoning, Counterfactuals, Bayesian Networks, and the Path to AGI
Judea Pearl is a professor at UCLA and a winner of the Turing Award, that’s generally recognized as the Nobel Prize of computing. He is one of the seminal figures in the field of artificial intelligence, computer science, and statistics. He has developed and championed probabilistic approaches to AI, including Bayesian Networks and profound ideas in causality in general. These ideas are important not just for AI, but to our understanding and practice of science. But in the field of AI, the idea of causality, cause and effect, to many, lies at the core of what is currently missing and what must be developed in order to build truly intelligent systems. For this reason, and many others, his work is worth returning to often.
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 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
03:18 – Descartes and analytic geometry
06:25 – Good way to teach math
07:10 – From math to engineering
09:14 – Does God play dice?
10:47 – Free will
11:59 – Probability
22:21 – Machine learning
23:13 – Causal Networks
27:48 – Intelligent systems that reason with causation
29:29 – Do(x) operator
36:57 – Counterfactuals
44:12 – Reasoning by Metaphor
51:15 – Machine learning and causal reasoning
53:28 – Temporal aspect of causation
56:21 – Machine learning (continued)
59:15 – Human-level artificial intelligence
1:04:08 – Consciousness
1:04:31 – Concerns about AGI
1:09:53 – Religion and robotics
1:12:07 – Daniel Pearl
1:19:09 – Advice for students
1:21:00 – Legacy
#164 — Cause & Effect
Sam Harris speaks with Judea Pearl about his work on the mathematics of causality and artificial intelligence. They discuss how science has generally failed to understand causation, different levels of causal inference, counterfactuals, the foundations of knowledge, the nature of possibility, the illusion of free will, artificial intelligence, the nature of consciousness, and other topics.
If the Making Sense podcast logo in your player is BLACK, you can SUBSCRIBE to gain access to all full-length episodes at samharris.org/subscribe.
52: What Math Models of Herding Cows Can Teach Us About Markets
Investors are often said to exhibit herding behavior when they follow each other into crowded positions — creating market bubbles that are susceptible to sudden pops when everyone begins stampeding for the exit. This week we take the analogy literally and speak to three professors who have created a mathematical model to examine why cows synchronize their behavior and — crucially — why they stop. Jie Sun, Erik Bollt, and Mason Porter, the authors of "A Mathematical Model for the Dynamics and Synchronization of Cows," extrapolate their findings to humans and modern markets. This episode is co-hosted by our resident bovine expert, Lorcan Roche-Kelly.
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