Breaking Math Podcast

By Autumn Phaneuf & Noah GiansiracusaScience Natural Sciences Mathematics

Breaking Math Podcast episodes

June 02 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
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45 min
May 29 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
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48 min
May 23 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
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30 min
May 21 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
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51 min
May 14 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
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48 min
May 05 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
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42 min
April 28 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
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57 min
April 26 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
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36 min
April 15 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
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51 min
April 07 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
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39 min

About Breaking Math Podcast

From the publisher's feed

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: [email protected]