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Breaking Math Podcast

Autumn Phaneuf & Noah Giansiracusa

Breaking Math is a deep-dive science, technology, engineering, AI, and mathematics podcast that explores the world through the lens of logic, patterns, and critical thinking. Hosted by Autumn Phaneuf, an expert in industrial engineering, operations research, and applied mathematics, and Noah Giansiracusa, a mathematician and leading voice in algorithmic literacy and technology ethics, the show is dedicated to uncovering the mathematical structures behind science, technology, and the systems shaping our future.

What began as a conversation about math as a pure and elegant discipline has evolved into a platform for bold, interdisciplinary dialogue. Each episode of Breaking Math takes listeners on an intellectual journey—into the strange beauty of chaos theory, the ethical dilemmas of AI and algorithms, the hidden math of biology and evolution, or the physics governing black holes and the cosmos. Along the way, Autumn and Noah speak with working scientists, researchers, and thinkers across fields: computer scientists, physicists, chemists, engineers, economists, philosophers, and more.

But this isn’t just a podcast about equations. It’s a show about how mathematics shapes the way we think, decide, build, and understand the world. Breaking Math pushes back against the idea that STEM belongs behind a paywall or an academic podium. It’s for the curious, the critical, and the creative—for anyone who believes that ideas should be rigorous, accessible, and infused with wonder.

If you’ve ever wondered:

  • What’s the math behind machine learning and modern algorithms?
  • How do we quantify uncertainty in climate and economic models?
  • Can intelligence or consciousness be meaningfully described in AI?
  • Why does beauty matter in an equation?

You’re in the right place.

At its heart, Breaking Math is about building bridges—between disciplines, between experts and the public, and between abstract mathematics and the messy, magnificent reality we live in. With humor, clarity, and deep respect for complexity, Autumn and Noah invite you to rethink what math can be—and how it can help us shape a better future.

Listen wherever you get your podcasts.

Website: https://breakingmath.io

Linktree: https://linktr.ee/breakingmathmedia

Email: breakingmathpodcast@gmail.com

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  • 23 episodes
  • Avg 40 min
  • English

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  • September 9 · 43 min

    Forecasting Explained: How Prediction Markets Beat Experts

    Professional forecaster Molly Hickman breaks down what it really means to assign a probability to the future — and why she believes generalists often out-forecast subject-matter experts. This episode explores the art and science of forecasting, from techniques to ethical considerations, and how AI and prediction markets are shaping our understanding of the future. Key Topics The definition of forecasting and its importance Techniques for starting in forecasting The role of AI and large language models in forecasting How to interpret probabilities and conditional forecasts Forecasting in complex systems like climate and geopolitics Ethical boundaries and red lines in prediction markets The impact of AI bots on forecasting accuracy and decision making Chapters 03:06 Getting Started with Forecasting: Tools and Techniques 06:15 Beginning Forecasting as a Beginner 07:31 Gut Feelings vs Market Wisdom 08:33 The Delphi Loop and Group Forecasting 09:39 Measuring Forecast Accuracy and Skill 11:17 Forecasting Long-Term and Uncertain Events 12:40 Extrapolating Trends and Model Limitations 14:19 AI Bots in Forecasting and Their Performance 18:16 Prediction Markets as Collective Wisdom 19:19 The Future of Prediction Markets and Society 24:06 The Meaning of Probabilities and Risk Assessment 27:20 Dealing with Chaos and Unpredictability 32:52 Combining Models and Expert Opinions 36:31 Forecasting and Expertise in Science and Policy 39:01 Forecasting AI Risks and Ethical Boundaries Follow Molly Hickman on X (https://x.com/celloMolly) Follow Breaking Math on Substack (https://breakingmath.substack.com/) X (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) X (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • August 19 · 48 min

    What Actually Makes Something Alive? with Melanie Challenger

    What does it mean to be alive? In this episode of Breaking Math, Autumn and Noah speak with Melanie Challenger, author of Alive, about one of the most profound questions in science and philosophy: how do we define life? Challenger argues that life is not simply a machine-like process or a bundle of genetic instructions. Living beings are embodied, purposeful agents. From single-celled organisms to sequoia seeds, from animals to human beings, life is marked by an astonishing capacity to work to keep itself alive. Chapters 08:12 The concept of purpose in living beings 09:14 The scientific view of purpose and agency 11:52 The importance of purpose and meaning in life 13:19 The danger of ignoring organism agency in science 14:34 Living beings as purposeful agents 15:35 Comparing purpose in a Roomba and a single-celled organism 18:03 Autopoetic vs allopoetic systems 20:03 Free will, agency, and the universe 23:24 The physical basis of life and energy 28:38 Aristotle's concept of psyche and purpose 33:46 The importance of understanding what life truly is 37:56 Material integration and the difference between machines and living beings 38:15 The concept of self and embodiment in life 41:09 The whole body as the agent, not just the brain Follow Melanie Challenger on her website: (https://www.melaniechallenger.com/) Subscribe for more on math, AI, technology, and the systems running the world. Follow Breaking Math on Substack (https://breakingmath.substack.com/) X (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) X (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • August 6 · 43 min

    Why Uncertainty Is Science's Greatest Strength with Stuart Firestein

    Neuroscientist Stuart Firestein (Columbia University) joins Breaking Math to make an extravagant claim: uncertainty isn't a weakness in science — it's the defining feature that makes progress possible. In this episode, we break down why the "one right answer" myth is one of the most damaging ideas in science, why real experts are often the most uncertain people in the room, and why authority and expertise pull in opposite directions, covering two fundamentally different kinds of probability, why Darwin never erased a 300-year-old classification system built on an assumption he disproved, why AI is exceptional at prediction but not built for causation, and why pseudoscience always has a confident answer while real science rarely does — plus the philosophical difference between hope and optimism, and why Voltaire had to invent the word "optimism" in 1759 to describe it. Chapters 03:00 Predictability and the sea of uncertainties 04:08 Science as a search for probabilities and multiple solutions 06:16 Biological classification and the dynamic nature of species 09:10 The optimistic view of a branching universe 12:41 Probability as the language of optimism 16:48 Two types of probability and their roles 17:50 AI, probabilistic models, and the future of certainty 21:40 Science and the creation of better ignorance 23:21 The importance of asking questions over giving answers 27:21 Authority versus knowledge in science 30:04 Pluralism and multiple solutions in science 32:46 Science in the gray area of uncertainty 35:39 The brain and randomness in thought 39:44 Science as a source of hope and optimism Follow Breaking Math on Substack (https://breakingmath.substack.com/) X (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) X (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • July 25 · 59 min

    Robot Proof: Why Better AI Starts With Better People with Vivienne Ming

    Neuroscientist, entrepreneur, and author Dr. Vivienne Ming joins Autumn and Noah to make the case that if we want better AI, we need to build better people first. We get into why AI tutors that hand students answers make learning worse, not better; what her research on "hybrid intelligence" reveals about the human traits — not the AI model — that predict elite human-AI collaboration; a wild experiment running Dungeons & Dragons with Claude and Gemini as dungeon masters to expose the gap between knowing and understanding; her case for "fiduciary AI," legal duty-of-care standards for tutors, hiring tools, and diagnostic models; and the real story of a hiring algorithm that learned to discriminate against women after every explicit gender marker was stripped out. Chapters 02:20 Why build this book now? The importance of human qualities 04:16 AI in education and the concept of robot-proofing 06:37 The median student and AI personalization 09:31 The limitations of AI understanding and theory of mind 11:30 Building better people with AI and human interaction 14:23 Hybrid intelligence and the role of human-AI collaboration 23:56 Case study: AI in Dungeons & Dragons 30:42 AI's strengths and limitations in understanding and cognition 37:34 The science of purpose and its impact on life and society 44:44 The collective intelligence of humans versus AI 46:54 Key takeaway: Build better people for better Follow Vivienne Ming on X (https://x.com/neuraltheory) Get Vivienne's book, Robot Proof: (https://amzn.to/3Tz21aP) Follow Breaking Math on Substack (https://breakingmath.substack.com/) X (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) X (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • July 10 · 44 min

    Why Nothing Works: Robber Barons, Algorithms & Governing AI

    In this episode, Historian and author Marc Dunkelman to explain why the 19th-century fight over railroad power is the exact fight we're about to have over algorithms and AI. Drawing on his acclaimed book Why Nothing Works: Who Killed Progress — and How to Bring It Back (a Best Book of the Year in the Financial Times and The Economist), Marc unpacks the two competing tools America has always used against concentrated power — antitrust vs. regulation — and why our government's "endemic diffusion of authority" now means nobody can decide anything, from congestion pricing to clean-energy transmission lines to AI safety. CHAPTERS 04:52 — When private projects come back to the public: Warp Speed, DARPA, CHIPS 08:55 — Two ways to fight concentrated power: break them up vs. regulate 10:52 — Railroads, island communities & the birth of regulation 12:29 — The railroad = algorithm parallel 20:33 — Why nothing gets built: the diffusion of authority 27:30 — "A voice without a veto" and the AI moment 32:53 — Where should government draw the line on new tech? 37:20 — Dunkelman the pragmatist: there is no simple answer 38:21 — Where math and AI can genuinely help public policy 40:46 — The lesson we keep overlooking Follow Marc on X [https://x.com/MarcDunkelman] Get Marc's book, Why Nothing Works: https://amzn.to/4pbFvAB] Substack (https://breakingmath.substack.com/) X (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) X (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • July 2 · 52 min

    Can Math Save Journalism?: Julia Angwin on Proof, Power, and Amazon's Algorithm

    In this conversation we chat with Julia Angwin — Pulitzer Prize-winning journalist, founder of Proof News, and former Wall Street Journal and ProPublica reporter — to make the case that journalism should function more like mathematical proof than anecdote. We cover how Angwin's team at The Markup used a decision-tree model to prove Amazon was favoring its own products in search results by an 8-to-1 margin — a finding the House Antitrust Committee later cited when referring Amazon to the DOJ for possible perjury. We dig into her "ingredients label" approach to reporting at Proof News (hypothesis, sample size, techniques, limitations), the difference between mathematical proof and the scientific method, and why she thinks control over algorithmic media is now the central battleground for authoritarian power. She also unpacks her new book on resisting authoritarianism, built from interviews with dissidents worldwide, including the "Swiss cheese" model of personal security and why perfectionism is dangerous in a crisis. Chapters 09:50 Proof News: A New Era in Journalism 19:56 Data-Driven Investigations: A Case Study 30:02 The Future of Journalism and AI 32:53 The Evolution of Search Rankings 35:06 The Role of Algorithms in Information Access 36:41 Fighting Authoritarianism Through Journalism 44:52 Community Resistance Against Authoritarianism 48:33 The Dangers of Perfectionism in Resistance 51:26 Declaring a Position in Journalism 56:25 The Importance of Math in Modern Society Julia Angwin's book, “On Courage” (https://amzn.to/448G8kY) Follow Julia Angwin on X (https://x.com/JuliaAngwin/) Bluesky (https://bsky.app/profile/juliaangwin.com) Proof News (https://www.proofnews.org/) Follow Breaking Math on Substack (https://breakingmath.substack.com/) X (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) X (https://x.com/ProfNoahGian) Follow Autumn on X (https://x.com/1autumn_leaf) Instagram (https://www.instagram.com/1autumnleaf/) email: breakingmathpodcast@gmail.com

  • June 24 · 45 min

    The Proof in the Code: How Lean Is Quietly Rewriting Trust in Math (w/ Kevin Hartnett)

    In this episode, Autumn and Noah talk with Kevin Hartnett about why mathematicians are willing to spend years reducing an idea to a level of detail a machine can check, whether formal verification can catch an AI that's technically correct but fundamentally misaligned, the cold-start problem that kept earlier theorem-provers niche, and what it means for the future of mathematical trust once AI can generate proofs faster than any human community can read them. Timeline: 00:00 Introduction to Lean and Its Significance 03:18 The Journey of Writing the Book 05:13 Human Element in Mathematical Formalization 06:57 Understanding Formal Proofs in Mathematics 11:21 The Origins of Lean and Its Purpose 13:03 Misalignment in Software Specifications 14:39 Building Mathematical Libraries in Lean 17:23 Ensuring Accuracy in Mathematical Foundations 22:00 Overcoming the Cold Start Problem in Lean Adoption 24:36 The Future of Mathematical Proofs 30:26 AI's Role in Mathematics 38:29 Expanding Beyond Mathematics 41:40 The Long-Term Impact of Lean The Proof in the Code is out now from Quanta Books. (https://amzn.to/3SuNlJm) Follow Kevin Hartnett on X (https://x.com/KSHartnett) Bluesky (https://bsky.app/profile/kevinhartnett.bsky.social) Follow Breaking Math on Substack (https://breakingmath.substack.com/) X (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) X (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • June 10 · 40 min

    How Data Science Exposes Injustice: Chad Topaz on Unlocking Justice

    What happens when the evidence of injustice is buried in messy, redacted, or inaccessible data? Mathematician and data scientist Chad Topaz joins Breaking Math to discuss his book Unlocking Justice. Together, we explore policing, sentencing, public records, Rikers Island, algorithmic risk, and the limits of quantifying human lives. This is a conversation about math, power, transparency, and the small acts of hope that can change systems. Chapters 00:00 Introduction and Context of the Conversation 01:11 Chad's Journey from Mathematics to Social Justice 03:50 The Personal Nature of Chad's Book 04:40 Challenges in Data Collection and Access 08:03 The Impact of Data on Policing and Surveillance 09:51 Humorous Yet Tragic Data Collection Experiences 12:55 The Importance of Data Preparation and Cleaning 14:40 Navigating Imperfect Data and Its Consequences 17:48 The Balance Between Quantification and Human Stories 22:25 Incarceration and Public Health: The Rikers Island Case Study 31:36 Mathematics and Social Justice: Secrets of the Elite 39:03 Hope and Action: A Personal Journey in Data for Justice Follow Chad Topaz on Bluesky(https://bsky.app/profile/chadtopaz.bsky.social) Book (https://amzn.to/3S21pKb) Follow Breaking Math on Substack (https://breakingmath.substack.com/) X (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) X (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • June 2 · 44 min

    Rise of the Robots: Is AI Coming for Your Job?

    This conversation explores the profound impact of AI and automation on the future of work, economy, and society. Featuring Martin Ford, author of 'Rise of the Robots,' the discussion covers technological progress, economic implications, policy ideas like universal basic income, and the evolving nature of jobs in an AI-driven world. Key Topics Impact of AI on employment and economy Potential of universal basic income as a solution Differences between past technological revolutions and AI The evolution from physical robots to AI software agents Jobs most vulnerable to automation and AI Chapters 04:14 The Impact of Technological Revolutions on Employment 10:40 The Shift from Physical to Intellectual Automation 12:16 The Debate: Replacement vs. Augmentation of Jobs 18:01 Economic Implications of Job Displacement 21:00 Exploring Solutions: Universal Basic Income and Beyond 24:08 The Awakening of Economists 25:12 Historical Perspectives on Automation 28:27 Navigating the Future Job Market 32:57 The Role of Skilled Trades in an AI World 38:13 The Alien Thought Experiment 42:17 The Future of AI and Its Implications 44:14 The Rise of Automation and Its Impact 45:14 AI as a Digital Workforce 45:38 The Shifting Landscape of Work 46:08 Questioning the Future of Automation and AI Follow Martin Ford on X (https://x.com/MFordFuture) Book (https://amzn.to/4vluX3N) Follow Breaking Math on Substack (https://breakingmath.substack.com/) X (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) X (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • May 29 · 47 min

    The Echoing Universe: How Radio Waves, AI, and Math Could Help Us Find Aliens with Emma Chapman

    Dr. Emma Chapman explains radio astronomy using the fruit bowl metaphor, explores the emotional and scientific aspects of space exploration, and discusses future technologies like the Square Kilometre Array and lunar radio telescopes. The conversation highlights the poetic beauty of the universe, the importance of connection, and the role of math and AI in understanding the cosmos with her book the Echoing Universe. Chapters 03:17 Understanding Radio Astronomy 08:12 The Intimacy of the Solar System 09:10 Tidal Locking and the Moon 13:36 The Emotional Lives of Astronauts' Families 17:53 The Shared Experience of Space Exploration 21:58 The Emotional Resonance of Celestial Events 26:41 Facing the Universe: Overcoming Fear through Cosmology 28:16 Cultural Perspectives: How Civilizations Understand the Cosmos 30:52 Astronomy's Historical Impact: Control and Awe in Civilizations 31:05 The Unlikely Scientist: James Stanley Hay's Discovery 40:31 AI in Astronomy: Harnessing Data for Discovery 45:14 The Next Frontier: Radio Telescopes on the Moon 47:38 A New Perspective: The Space Between Stars Follow Dr. Emma Chapman Bluesky (https://bsky.app/profile/dreochapman.bsky.social) Instagram (https://www.instagram.com/dremmachapman/) Book (https://amzn.to/4u0GCnC) Follow Breaking Math on Substack (https://breakingmath.substack.com/) X (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) X (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • May 23 · 29 min

    AI Solves 80-Year-Old Math Conjecture: What It Means for the Future of Mathematics

    This episode explores how AI, specifically OpenAI's recent breakthrough in solving an 80-year-old math conjecture, is transforming the field of mathematics. Featuring insights from Professor Daniel Litt, the discussion covers the implications of AI in mathematical research, the value of human verification, and the future of mathematical practice. Key topics AI solving long-standing mathematical problems The role of human verification in AI-generated proofs Implications of AI breakthroughs in discrete geometry The future of mathematical research with AI Number theory and algebraic constructions in AI discoveries Chapters 00:00 Introduction to the Conjecture and Its Significance 01:15 Understanding the Erdős Problem 04:34 The Role of AI in Solving Mathematical Problems 09:17 The Implications of AI in Mathematics 10:32 AI vs Human Mathematicians: A Comparative Analysis 17:20 Standards for AI-Generated Proofs 21:10 Corporate Interests in Mathematical Research 24:42 The Future of Mathematics and AI 27:50 Final Thoughts on AI and Mathematics 31:37 Revolutionizing Mathematics: AI's Breakthrough in Discrete Geometry 37:37 Exploring the Implications: AI and the Future of Mathematics 38:03 The Role of AI in Mathematics 39:23 Human Value in the Age of AI Follow Daniel Litt on X (https://x.com/maiasz) Website (https://daniellitt.com) Follow Breaking Math on Substack (https://breakingmath.substack.com/) X (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) X (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • May 21 · 50 min

    The Science of Addiction: Dopamine, Social Media, and the Myth of Willpower with Maia Szalavitz

    In this episode with award-winning journalist and author Maia Szalavitz challenges the idea that addiction is simply about pleasure or willpower. Instead, she explains addiction as compulsive behavior that continues despite negative consequences — and shows why withdrawal, dependence, and addiction are not the same thing. The conversation explores “wanting” versus “liking,” why dopamine is misunderstood, how social media and AI can exploit reward systems, and why punishment often fails. Ultimately, Szalavitz argues that recovery depends less on tough love and more on connection, purpose, safety, and care. Chapters 00:00 Understanding Addiction: Definitions and Mechanisms 10:43 The Role of Dopamine in Addiction 14:18 Addiction as a Learning Disorder 16:22 Substance vs. Experience: The Nature of Addiction 20:13 Evidence-Based Methods for Overcoming Addiction 25:20 Finding Meaning and Purpose Beyond Addiction 33:30 The Pursuit of Meaningful Experiences 34:15 Understanding Dopamine and Pleasure 39:10 The Complexity of Addiction 43:00 Social Media and Addiction Dynamics 50:42 Generational Perspectives on Technology and Addiction 57:53 Lessons Learned in Addiction Science 01:02:03 Rethinking Addiction: A New Perspective 01:03:54 The Compulsive Nature of Addiction 01:04:14 Understanding Addiction Beyond Pleasure 01:05:27 The Importance of Connection and Compassion Follow Maia Szalavitz on X (https://x.com/maiasz) Follow Breaking Math on Substack (https://breakingmath.substack.com/) X (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) X (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • May 14 · 47 min

    Are We Being Misled by Data? Ron Wasserstein on AI, Bias, and Statistical Truth

    In this episode of Breaking Math, Autumn and Noah speak with Ron Wasserstein, Executive Director of the American Statistical Association, about what statistics means in a world increasingly shaped by AI, misinformation, and fragile public trust. Wasserstein argues that statistics is not merely a “bag of tools,” but a way of thinking: asking where data comes from, what it leaves out, how uncertainty should be communicated, and when numbers are being used to illuminate rather than manipulate. Chapters 00:00 The Golden Age of Statistics 02:36 AI's Impact on Statistics 08:16 Data as Fuel for AI 10:55 Bias in AI and Statistics 14:01 Preparing Future Statisticians 16:58 Bridging the Gap: Academia and Industry 22:58 The Misconception of Statistics 23:08 The Role of Statistics in Public Discourse 26:20 The American Statistical Association's Mission 32:18 Statistics and Politics: A Historical Perspective 36:02 Addressing Misinformation and Misuse of Data 39:51 The Importance of Statistical Literacy 44:01 Misconceptions About Statistics and Expertise 46:57 The Essence of Statistics 47:22 Statistics as a Way of Thinking Follow Ron Wasserstein LinkedIn (https://www.linkedin.com/in/ron-wasserstein/) Follow Breaking Math on Substack (https://breakingmath.substack.com/) Twitter (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) Twitter (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on Twitter (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • May 5 · 41 min

    How Ransomware Became a Global Industry with Anja Shortland on Dark Screens

    What if ransomware did not begin with criminals, but with curiosity? In this episode of Breaking Math, Autumn and Noah talk with Anja Shortland, professor of political economy at King’s College London and author of Dark Screens. This conversation explores how playful hacking evolved into professionalized cybercrime, why ransomware gangs operate like morally questionable internet startups, how cryptocurrency made ransomware scalable, and why hospitals, governments, universities, and critical infrastructure remain especially vulnerable. We also dig into the mathematics behind encryption, asymmetric cryptography, game theory, negotiation, cyber insurance, and the uncomfortable trade-offs between freedom, privacy, and regulation. Chapters 00:00 The origins of ransomware and early hacker culture 02:13 The evolution of ransomware attacks since 2013 03:14 The paradox of cybercriminals as entrepreneurs 06:19 Early hackers: Steve Jobs and Wozniak as pioneers 12:34 The moral and legal landscape of hacking and cybercrime 13:39 The importance of cybersecurity awareness for individuals 15:03 The arms race: attackers vs defenders and the role of math 16:02 The technological innovations behind ransomware 19:21 Asymmetric encryption and cryptocurrency in ransomware 20:53 Bitcoin and the dark web: enabling cybercrime 22:45 The impact of AI on future cyber threats and defenses 34:07 The future of ransomware and cybersecurity challenges Follow Anja Shortland on LinkedIn (https://uk.linkedin.com/in/anja-shortland-53133b231) Book (https://amzn.to/4d6pB4X) Follow Breaking Math on Substack (https://breakingmath.substack.com/) Twitter (https://x.com/breakingmathpod) X (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) Twitter (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • April 28 · 56 min

    Explaining Huge Numbers with Richard Elwes

    What does it actually mean for a number to be “big”? In this episode of Breaking Math, Autumn chats with mathematician Richard Elwes to explore how huge numbers reveal the limits of human intuition, language, and even mathematics itself. The discussion moves from exponential growth in pandemics and finance to numbers larger than the universe itself, emerging in games like chess and abstract possibility spaces. Finally, it reaches one of the most profound ideas in modern mathematics: that there are true statements about numbers that can never be proven. This episode challenges how we think about scale, complexity, and the systems we rely on to make sense of reality. Key Topics Limits of ancient numeral systems like Roman numerals Mathematical logic and the concept of huge numbers Evolution of number notation from Roman to Hindu-Arabic systems The significance of place value in expressing large numbers The Mayan long count and its implications for understanding time scales Chapters 00:00 Introduction and Inspiration for the Book 01:39 Redefining Big Numbers 01:55 Limits of Numerical Systems 05:33 Evolution of Number Sense 10:02 Language and Numerical Understanding 11:53 Cultural Influences on Numerical Systems 14:18 Hacks in Ancient Number Systems 16:55 Archimedes and the Concept of Infinity 22:01 The Importance of Place Value 25:45 Mayan Cosmology and Time Scales 31:55 Exponential Growth and Its Dangers 32:20 Understanding Exponential Growth 36:14 The Dangers of Exponential Growth 37:23 Limits of Exponential Growth in the Physical World 39:42 Exploring Possibility Space 45:38 Goodstein's Theorem and Mathematical Logic Connect with Breaking Math Follow Richard Elwes on X (https://x.com/RichardElwes/ ) Instagram (https://www.instagram.com/richardelwes/) His Book(https://amzn.to/48rk5s9) Follow Breaking Math on Substack (https://breakingmath.substack.com/) Twitter (https://x.com/breakingmathpod) X (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) Follow Autumn on X (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • April 26 · 35 min

    AI Isn’t Replacing You—It’s Changing the Rules with Sheamus McGovern

    In this episode we sit down with Sheamus McGovern, founder of the Open Data Science Conference (ODSC AI), to unpack what AI actually looks like. Sheamus shares what’s really happening behind the scenes of the AI boom and why the biggest shift isn’t job loss, but a complete transformation of skills. From explaining why AI is reshaping—not replacing—jobs, to breaking down the gap between hype and real-world applications, this conversation explores how early algorithmic trading foreshadowed today’s AI revolution, why open-source tools like TensorFlow and PyTorch changed everything, what the “AI Skill Flip” means for your career, and why even data scientists are questioning their future. Along the way, the biggest mistake people make when trying to learn AI, and why the smartest approach isn’t to learn everything—but to start intentionally and build from there. Timestamps 00:00 – The biggest misconception about AI 02:00 – Algorithmic trading and the origins of AI in finance 05:00 – The birth of ODSC AI and the data science movement 09:30 – Breakthrough moments in AI 16:30 – Democratization of AI and open-source tools 19:00 –The AI Skill Flip 24:00 – The truth about AI replacing jobs 27:00 – Real-world AI success stories 32:30 – How to actually start learning AI today Follow Sheamus McGovern on LinkedIn (https://www.linkedin.com/in/sheamus/) ODSC Website (https://odsc.ai/) Follow Breaking Math on Substack (https://breakingmath.substack.com/) Twitter (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) Twitter (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on Twitter (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • April 15 · 50 min

    Math and Magic with Matt Baker

    In this episode, mathematician and award-winning magician Matt Baker explores the fascinating intersection of mathematics and magic, revealing how mathematical principles, intuition, and storytelling create unforgettable illusions. From a mind-reading trick based on the classic concept of “casting out nines” to his groundbreaking research on the Riemann–Roch theorem for graphs, Baker demonstrates how creativity and pattern recognition drive both mathematical discovery and magical performance. Chapters 00:00 The Interplay of Math and Magic 04:58 Aesthetic Connections in Math and Magic 08:57 Balancing Family, Math, and Magic 12:34 The Impact of Magic on Mathematical Thinking 16:32 The Art of Clarity in Communication 16:44 A Live Magic Demonstration 25:14 Intuition and Pattern Recognition in Math 30:03 The Riemann-Roch Theorem for Graphs 41:42 The Role of AI in Mathematics and Magic 50:21 The Art of Communicating Mathematics 50:47 The Magic of Math and Performance Follow Matt Baker on Facebook (https://www.facebook.com/mbakermath) Academic (https://sites.google.com/view/mattbakermath/home/) Magic (http://mattbakermagic.com/) Follow Breaking Math on Substack (https://breakingmath.substack.com/) Twitter (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) Twitter (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on Twitter (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • April 7 · 38 min

    Credibility Crisis in Science with Thomas Plümper and Eric Neumayer

    In this episode, Thomas Plümper and Eric Neumayer explore the hidden challenges in modern science, from outright fraud to the subtler practice of “tweaking” data that distorts results. They examine why the self-correcting nature of science often falls short, how incentives and academic pressure drive misconduct, and the double-edged role of AI in both enabling and detecting fraud. The conversation also tackles debates around p-values and statistical reasoning, shares cautionary case studies, and proposes solutions like greater data transparency and stronger verification standards. Chapters 00:00 Introduction to Fraud in Research 06:21 The Nature of Fraud Detection 08:56 Incentives and Motivations for Fraud 10:43 Self-Correction in Science 12:13 Understanding Statistical Significance 13:04 The Role of Replication in Research 14:32 Bayesian vs Frequentist Approaches 23:09 Understanding Bayesian Statistics and Its Implications 26:24 The Humility of Empirical Science 27:16 Concrete Examples of Scientific Fraud 32:52 Proposed Solutions to Scientific Fraud 34:50 The Reality of Scientific Fraud and Human Nature Guest Links You can purchase their book here (https://amzn.to/3Ole3lY) Follow Eric Neumayer on LinkedIn - (https://linkedin.com/in/ericneumayer) Follow Breaking Math on Substack (https://breakingmath.substack.com/) Twitter (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) Twitter (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on Twitter (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) email: breakingmathpodcast@gmail.com

  • March 27 · 8 min

    Denied, Then Unstoppable: The Story of Mary T. Washington Wylie

    This Women in History Mini-Series episode with Dr. Victoria Bateman explores the inspiring story of Mary T. Washington Wylie, the first African-American woman CPA, her challenges, achievements, and legacy in breaking racial and gender barriers in the early 20th century. Mathematics is supposed to be objective—but access to it has never been equal. Chapters 00:00 Introduction to Mary T. Washington Wylie 00:48 Early Life and Challenges 02:58 Breaking Barriers in Accountancy 05:25 Pioneering a Path for Others 07:21 Legacy and Impact Follow Breaking Math on Substack (https://breakingmath.substack.com/) Twitter (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Victoria on Website (http://www.vnbateman.com/) Instagram (https://www.instagram.com/women.wealth.power/) Twitter (https://x.com/vnbateman) Bluesky (https://bsky.app/profile/vnbateman.bsky.social) Follow Autumn on Twitter (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) Substack (https://substack.com/@1autumnleaf) TikTok (https://www.tiktok.com/@1autumn_leaf_)

  • March 24 · 40 min

    The Power of Connection in Math: Insights from Hortensia Soto

    In this episode of Breaking Math, we sit down with Dr. Hortensia Soto, former president of the Mathematical Association of America, to explore the role of mathematics in a world shaped by AI, education, and access. We discuss how debates in math are often really about opportunity and inclusion, how educators can navigate the rapid pace of AI, and why communication and human connection matter more than ever. The conversation also highlights the importance of financial literacy, embodied learning, and collaboration, reframing mathematics not as a set of answers, but as a way of thinking grounded in curiosity, effort, and relationships. Chapters 00:00 Introduction to Hortensia Soto and the Math Community 02:48 The Role of AI in Mathematics 05:17 Access to Mathematics and Its Political Nature 07:34 The Importance of Financial Literacy in Math Education 10:19 Communication Skills for Mathematicians 13:06 The Culture of the Mathematical Association of America 15:29 Reflections on Leadership in the Math Community 25:01 Innovative Approaches to Mathematics Education 25:50 Recognizing Math Identity in Students 27:02 Nurturing Student Potential 35:31 The Role of AI in Learning 38:26 The Human Element in Mathematics 39:51 Mathematics Beyond Symbols and Procedures Follow Hortensia Soto on LinkedIn (https://www.linkedin.com/in/hortensia-soto-41230188/) Follow Breaking Math on Substack (https://breakingmath.substack.com/) Twitter (https://x.com/breakingmathpod) Instagram (https://www.instagram.com/breakingmathmedia/) Bluesky (https://bsky.app/profile/breakingmath.bsky.social) Website (https://www.breakingmath.io/) YouTube (https://www.youtube.com/@BreakingMathPod) Follow Noah on Instagram (https://www.instagram.com/profnoahgian/) Twitter (https://x.com/ProfNoahGian) Bluesky (https://bsky.app/profile/profnoahgian.bsky.social) Follow Autumn on Twitter (https://x.com/1autumn_leaf) Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social) Instagram (https://www.instagram.com/1autumnleaf/) email: breakingmathpodcast@gmail.com

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