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View a transcript of this episode here.How do traditions preserve inherited knowledge while continuing to grow? Moshe Koppel brings ideas from mathematics and computer science to questions about meaning, creativity, and religious life. We start with sophistication, a mathematical concept he developed to distinguish underlying structure from randomness, and discuss how he uses it as an analogy for creativity and the continuing development of Jewish law. We then turn to his book, Judaism Straight Up, and his account of how religious communities cooperate and survive. Why might societies need loyalty and restraint alongside fairness? How can seemingly arbitrary rituals build trust, and when do their costs become excessive? We discuss how much belief religious commitment requires, how traditions evolve through the interaction of texts, communal practice, and recognized authorities, and whether survival is enough to tell us that a society is doing well.From there, Moshe explains his research on identifying the authors of texts, uncovering forgeries, and analyzing stylistic divisions in the Torah. We discuss what these computational methods can establish, what they leave open, and how he thinks about the theological questions they raise.We finish with AI and human purpose: why Moshe is optimistic about the progress of language models, why he worries about people outsourcing their thinking, and where meaning might come from in a world with less need for human labor. He and describes how his lab, Dicta, is designing AI tools to guide people through Jewish sources while encouraging them to think and interpret for themselves.Guest: Moshe Koppel is professor emeritus of computer science at Bar-Ilan University. His research spans complexity theory, authorship attribution, and social choice. He is the founder of Dicta, which develops AI tools for studying Jewish texts, and the author of Meta-Halakhah and Judaism Straight Up.

Get the episode transcript on Zappable. Spencer Greenberg and clinical psychologist Jeremy Stevenson set out to answer one question: what are all the psychological strategies you can use to improve your life? They read over a hundred self-improvement books, surveyed more than 20 types of therapy, and found that everything collapsed into twelve high-level strategies - the basis of their new book, The 12 Levers.We start with Spencer's life philosophy, valuism: figure out what you intrinsically value, then take effective actions to create it. That turns out to be harder than it sounds, because our brains don't cleanly separate what we truly value from what we want as a means to something else. It also leads to a surprising finding from his research about the kinds of values that people have. We discuss additional questions about valuism, and Spencer also includes an analogy to a cheese-fetching robot. We then dive into a discussion of his book, starting with how it's organized. From there: a worry technique most people have never heard of, why behavior change usually fails for a different reason than you'd guess, how you build a rigorous book on a field that went through a replication crisis, why he reads the Dodo Bird verdict differently than most people do, what today's chatbots get wrong about therapy, and why almost none of this is taught in school.Guest: Spencer Greenberg has a PhD in applied math from NYU and co-founded one of the first financial firms to use machine learning. He left finance to start Spark Wave, which runs psychology research and builds products from it, including ClearerThinking.org, ⁠Ten Conditions for Change⁠ and One Helpful Idea. He hosts the podcast Clearer Thinking with Spencer Greenberg, and he's the co-author, with clinical psychologist Jeremy Stevenson, of The 12 Levers: The Complete Psychological Toolkit for Improving Your Life.Books mentioned (paid links):⁠The 12 Levers ⁠⁠Feeling Good ⁠⁠Atomic Habits ⁠Timestamps00:00 Introduction00:55 Focus and Follow-Through03:45 Intrinsic Values and Valuism06:22 Should Values be Taken As-Is11:46 Spencer's Intrinsic Values15:18 How to Have Better Conversations17:15 The Twelve Levers Framework20:16 Worry Time and Rumination24:35 What's Missing from the Book29:03 Evaluating Psychological Evidence34:07 Turning Ideas Into Action37:17 Self-Help, Coaching and Therapy43:01 The Dodo Bird Verdict46:11 AI and Self-Improvement51:20 Life Skills and the Education System54:32 Recommended Books and Closing

Get the transcript here. Dr. Shaanan Cohney is a computer scientist and legal scholar, and he draws on all his areas of expertise in this discussion of AI. We talk about what draws him to both music and code and whether AI-generated music counts as the real thing. He explains what lockpicking teaches about how systems really fail, and what your front door lock is actually for, and how this relates to software security. Next we discuss how generative AI has upended teaching computer science, and the purpose of a CS education today. We dig into what the research actually says about social media and teenagers, including Shaanan's own work on Australia's under-16 ban, and whether there's a better way to regulate.The second half covers AI risk: what today's models can and can't do to find security vulnerabilities, how governments and labs are responding, the risks of using agentic AI, the general risks of being online today, and whether the defenders or the scammers win in the long run.Guest: Dr. Shaanan Cohney has a Ph.D. in Computer & Information Science and a Master in Law from the University of Pennsylvania. He's a senior lecturer at the University of Melbourne and has advised the FTC and the US Senate on tech policy. Find Shaanan on Google Scholar, on X @shaananc, and on YouTube. Timestamps00:27 Music and Computer Science07:47 Exploring Security: Physical vs. Software15:23 The Impact of AI on Computer Science Education31:46 Social Media and Its Effects on Youth48:37 Anthropic & the Risk of Powerful AI01:05:01 Agentic AI: Risks and User Protections01:12:32 Addressing Scams in the Age of AI

⁠Read an abridged transcript here.Bryan Caplan argues that roughly 80% of schooling is wasted time, and that the primary value of a degree comes from signaling - demonstrating intelligence, conscientiousness, and conformity to employers rather than building useful skills. In this conversation, we discuss the evidence behind that claim, what "conformity" really means, why the system is so resistant to change, what Bryan would do if he was in charge, and whether AI will change the equilibrium. Some questions we discuss:How much does education actually increase abilities or intelligence?The Flynn effect points to an increase in IQ scores over time. Do schools get any credit ? Bryan has argued that a college degree is important for signaling conformity and skipping it demonstrates non-conformity. But if conformity just means "professionalism" - can you demonstrate it without a degree? Classes are no longer entirely in-person, and tech will change education even more. Will people still need a four-year degree from a brick-and-mortar institution? What happens to universities once AI can do most intellectual work?Guest: Bryan Caplan, Economics professor at George Mason University and author of The Case Against Education. Check out his Substack and YouTube Channel.Timestamps00:00 How Much of School is a Waste?04:39 The Flynn Effect08:29 The Importance of Literacy & Numeracy12:35 Signaling and Conformity in Education18:57 The Practicality of College Education20:41 Will Online Education Become Accepted?25:28 AI's Impact on Education29:50 Will AI Asymptote32:11 Reimagining the Education System35:27 Curiosity and Tailored Learning37:12 Talented STEM Students40:16 Libertarian Perspectives on Education

Ariel speaks with Mike Todasco about practical AI usage strategies and broader implications of AI adoption. Mike shares his "Borg Chart" framework for organizing AI tools, explains how he uses multiple AI subscriptions, and discusses his recent research on LLMs and prediction markets. The conversation covers where to draw the line with AI assistance, the risks of over-reliance on AI companions, how education needs to adapt, and how solopreneurs are now empowered with AI. GuestMichael (Mike) Todasco is a Visiting Fellow at San Diego State University’s AI Center and the former Senior Director of Innovation at Paypal. Find him online at todasco.com. Chapters00:00 Introduction to AI and Personal Journey03:12 AI Borg Chart05:01 Human Touch vs. AI Automation07:52 Exploring Multiple AI Tools11:57 Recognizing AI Errors & Limitations15:32 Using Deep Research19:09 AI Betting & Confidence24:38 The Risks of AI28:20 AI in Education32:23 The Purpose of Learning37:51 AI Alignment and Corporate Alignment44:18 The GDPVal Metric