The Joy of Why

People may think of soil as just dirt, but it is anything but inert. Beneath your feet, a vast network of mycorrhizal fungi is hard at work, trading minerals with plant roots. This trading system helps enrich the soil, and it sequesters 13 billion tons of atmospheric carbon dioxide each year — roughly equivalent to one-third of the world’s fossil-fuel emissions. Scientists know that these fungi form partnerships with 80% of all plant species on Earth, a relationship that evolved some 450 million years ago. What they have not understood is how organisms with no brain or central nervous system can decide whom to trade with, and on what terms.

Toby Kiers, an evolutionary biologist at Vrije Universiteit Amsterdam, has spent much of her career making this hidden world visible. Drawing on economics and game theory, and using tools that range from fluorescent quantum dots to imaging robots, her lab is probing how fungi and plants conduct their trade. The work raises new questions about soil, carbon, and even what counts as an individual organism. In this episode, Kiers tells co-host Steven Strogatz how these brainless, decentralized organisms can behave strategically — discriminating between better and worse partners and shifting resources across the network to wherever a plant will “pay” more for it — and how she has built a worldwide community of researchers 

We know all about how things exist in the three dimensions of length, width, and height. Physicists often talk about time as a fourth dimension, but what if there were a fourth spatial dimension — another direction entirely? How on earth would we picture that?

Mathematicians use topology to visualize abstract spaces in higher dimensions. Maggie Miller at the University of Texas at Austin explores what happens when knots encounter an extra dimension. Familiar tangled loops behave in unexpectedly complex and counterintuitive ways in 4D: Knots can always come undone, while ordinary surfaces like spheres can — surprisingly — become knotted in ways that can’t be undone.

In this episode, Miller explains to co-host Janna Levin why 4D is the lowest dimension that mathematicians still don’t fully understand, how she and her collaborators resolved a question about knotted surfaces first posed by mathematician Charles Livingston in 1982, and how her interest in art has helped her develop the visual techniques she uses to picture 4D spaces. 

Quantum mechanics may be one of the most precisely tested paradigms in science, but there’s still no universally accepted interpretation of what it tells us about reality. How do we get from the wave-like behavior of quantum systems to the solid, macroscopic world of objects and the universe at large?

Jonathan Halliwell, a professor of theoretical physics at Imperial College London, has spent his career probing the foundations of quantum theory. In this episode, he tells Steven Strogatz why decoherence — the process by which fragile quantum behavior becomes dispersed through interactions with the surrounding environment — is key to the transition from quantum to classical behavior, and he describes the “histories” approach that he uses to understand this. Along the way, Halliwell tackles some of the field’s deepest paradoxes. He explains why the quantum-to-classical transition doesn’t require a conscious observer, and he explores Einstein’s famous question of whether the moon is really there when no one looks. The conversation ends with Halliwell explaining how yoga and meditation help him sit with the mystery of competing perspectives in science.

Mathematicians are witnessing a profound shift in their field. AI systems are now producing proofs, spotting connections between distant fields, and, in a few cases, solving problems that had stumped mathematicians for decades. The pace of progress over the past several months has raised challenging questions: What can AI systems actually do? And what happens to the more human, creative aspects of the field once machines can match – or exceed – people at problem-solving?

In this special live episode of The Joy of Why, recorded at the International Congress of Mathematicians in Philadelphia on July 26, 2026, hosts Janna Levin and Steven Strogatz are joined by three mathematicians responding to the rise of AI in math: Akshay Venkatesh at the Institute for Advanced Study; Ravi Vakil at Stanford University and president of the American Mathematical Society; and Alex Kontorovich at Rutgers University. Together they discuss what recent AI-generated proofs really demonstrate, what will be gained and lost as mathematics becomes more machine-assisted at the frontier, and what this means for the next generation of mathematicians. The conversation turns to a deeper question: What do mathematicians value about doing mathematics in the first place? The answer involves grappling with what proof and understanding really mean, and with the surprising importance of storytelling.

When an LLM answers a question, is it reasoning like humans, or just producing text that looks like reasoning? The distinction isn’t just philosophical, this determines what we can trust AI to do, how closely we need to supervise it, and ultimately what its real-world impact will turn out to be.

Melanie Mitchell at the Santa Fe Institute argues that we lack adequate methods for measuring machine cognition, and that AI is a form of “alien intelligence” that operates through non-human cognitive mechanisms. In this episode of The Joy of Why, Mitchell tells Steven Strogatz how methods that psychologists use to study cognition in other kinds of “alien intelligence” — babies and animals — can be adapted to probe AI, and she lays out six principles for better assessing machine cognition. Their conversation ranges from the challenge of interpreting what’s happening inside these systems, to recent AI-assisted breakthroughs in mathematics, to why a math-performing horse from the early 1900s offers a cautionary tale for how we assess intelligence.

Pain and pleasure seem like simple facts of life, but they are far from it. Neuroscientists still cannot say why physical pain differs from psychological pain, for instance, nor why a loved one’s touch soothes while a stranger’s touch repels.

To explore the science behind these sensations, Janna Levin talked to Ishmail Abdus-Saboor, a neuroscientist at Columbia University’s Zuckerman Institute. Their conversation covers how pain serves an evolutionary purpose, how researchers measure pain and pleasure in the lab despite the absence of any objective biomarker, and how touch functions as a social and emotional signal, not just a sensory one. Abdus-Saboor also describes his work with naked mole rats — a species that barely feels pain, shows no signs of aging, and lives in colonies built almost entirely on touch — and the ethical trade-offs when studying sensations in animals that cannot describe what they feel.

One of the biggest mysteries in cosmology seems to keep getting bigger. Astronomers have known since the 1930s that the universe is expanding, but in the 1990s, the discovery that this expansion is accelerating rather than slowing down came as a huge shock to the field. Something had to be driving that acceleration, and dark energy was proposed as the cause. What began as a seismic shock in cosmology eventually led to a Nobel prize.

But this story has a sequel, and it comes with another major plot twist. The two main methods for estimating the universe's present-day expansion rate are producing significantly different answers. As a result, how fast the universe is really expanding has become a matter of considerable debate — with no small amount of angst — and the discrepancy has become known as the Hubble tension. Perhaps most surprising of all is that one of the loudest voices raising concern is Adam Riess, the astrophysicist whose Nobel Prize-winning work helped ignite the acceleration debate in the first place.

Riess joined co-host Steven Strogatz on The Joy of Why to explain how we got to this point, what the Hubble tension might be telling us, and what may happen next.

Does intelligent life exist elsewhere in the universe? The question has captivated us for centuries, but despite decades of searching it remains frustratingly unanswered. Every so often a curious signal appears — fossilized structures in a meteorite, say, or an unusual gas in an exoplanet’s atmosphere — and for a moment it seems possible that we are not alone before the excitement gives way to a more mundane explanation. 

So what would it actually take to find life in the cosmos — and how would we know when we saw it?

David Kipping, an astronomer at Columbia University, has spent his career finding better ways to answer these questions. His approach is statistical: rather than chasing individual detections, he develops mathematical frameworks for reasoning about where habitable worlds are likely to exist and how confidently we can interpret the signals they produce. In this episode of The Joy of Why, Kipping joins co-host Janna Levin to discuss efforts to frame one of humanity’s oldest existential questions as a tractable scientific problem, why biosignatures have proved so difficult to interpret, and why he believes exomoons may be an overlooked place to search for life.

What links certain mathematical models of traffic flow, shallow-water waves, and quantum particle scattering? The surprising answer lies in a corner of the algebraic combinatorics world that goes by the name of positive Grassmannian. In simple terms, the positive Grassmannian is a shape that classifies other shapes. Remarkably, pieces of the positive Grassmannian can be reassembled in forms that reveal shared structures in these and many other seemingly unrelated mathematical systems.

That we know the positive Grassmannian crops up in many real-world settings is largely down to the theoretical work of Lauren Williams at Harvard University. In this latest episode of The Joy of Why, Williams talks to co-host Steven Strogatz about her work, how she realized the surprising pervasiveness of the positive Grassmannian, and how she has made a career of finding connections among fields that don’t at first sight seem connected. The conversation then switches to another project Williams is working on, called First Proof, which is trying to measure objectively how good AI systems are at coming up with proofs of research-level mathematical statements, and which leads to an exploration of whether AI may or may not take over mathematics.

Note: Since this conversation was recorded, results from the First Proof Second Batch project were released on June 10, 2026.

One of the most surprising and remarkable discoveries in recent scientific history has been CRISPR. Short for Clustered Regularly Interspaced Short Palindromic Repeats, CRISPR is a form of immune system that evolved in bacteria more than a billion years ago to defend against persistent viral threats. Under attack, bacteria can snip a small fragment of a virus’s DNA, store it in the CRISPR region of their genome, and then use it to recognize and destroy the same virus if it returns. The CRISPR-Cas9 system, to give it its longer name, consists of a short strand of guide RNA that identifies where to cut the DNA and a protein that acts as the molecular scissors.

What made this system truly revolutionary was the demonstration in 2012 that it could be reprogrammed with different pieces of guide RNA to edit virtually any genome in any species, and at a level of precision and ease that far surpassed existing gene-editing tools. Since then, the editing capability of CRISPR has been tested on everything from developing disease treatments to engineering drought-resistant crops to resurrecting genes of extinct species. The possibilities have expanded so rapidly that researchers, ethicists, and regulators have found themselves struggling to keep up.

One person acutely aware of the power of CRISPR is Jennifer Doudna, co-developer of the technology. Doudna, who received the Nobel Prize in Chemistry in 2020 with Emmanuelle Charpentier for this pioneering work, has been a prominent voice not only for its vast potential but also for its responsible and ethical use. In this episode of The Joy of Why, Doudna tells co-host Janna Levin how her early, “rebellious,” decision to study RNA led her on a serendipitous path to one of biology’s most transformative discoveries. They also discuss the breakthroughs, barriers, and frontiers that will define CRISPR’s true impact.