Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas

Physics is extremely good at describing simple systems with relatively few moving parts. Sadly, the world is not like that; many phenomena of interest are complex, with multiple interacting parts and interesting things happening at multiple scales of length and time. One area where the techniques of physics overlap with the multi-scale property of complex systems is in the study of phase transitions, when a composite system transitions from one phase to another. Nigel Goldenfeld has made important contributions to the study of phase transitions in their own right (and mathematical techniques for dealing with them), and has also been successful at leveraging that understanding to study biological systems, from the genetic code to the tree of life.

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Nigel Goldenfeld received his Ph.D. in physics from the University of Cambridge. He currently holds the Chancellor's Distinguished Professorship in Physics at UC San Diego. Until recently he was a Swanlund Endowed Chair and Center for Advanced Study Professor in Physics at the University of Illinois at Urbana-Champaign. Among his awards are the Xerox Award for research, the A. Nordsieck award for excellence in graduate teaching, and the American Physical Society's Leo P. Kadanoff Prize. He is the co-founder of NumeriX, a company that specializes in high-performance software for the derivatives marketplace.

• Web site
• UC San Diego web page
• University of Illinois web page
• Google Scholar publications
• Wikipedia
• Twitter
• Lectures on Phase Transitions and the Renormalization Group
• Quanta interview

There is no general theory of problem-solving, or even a reliable set of principles that will usually work. It's therefore interesting to see how our brains actually go about solving problems. Here's an interesting feature that you might not have guessed: when faced with an imperfect situation, our first move to improve it tends to involve adding new elements, rather than taking away. We are, in general, resistant to subtractive change. Leidy Klotz is an engineer and designer who has worked with psychologists and neuroscientists to study this phenomenon. We talk about how our relative blindness to subtractive possibilities manifests itself, and what lessons might be for design more generally.

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Leidy Klotz received his Ph.D. in Architectural Engineering from Penn State University. He is currently Copenhaver Associate Professor of Engineering Systems and Environment and Architecture at the University of Virginia. Before becoming a professor, he worked as a school designer, and before that was a professional soccer player for the Pittsburgh Riverhounds. His new book is Subtract: The Untapped Science of Less.

• Web site
• University of Virginia web page
• Google Scholar publications
• "People Systematically Overlook Subtractive Changes," Adams, Converse, Hales and Klotz, 2021.
• Wikipedia
• Twitter

Economies in the modern world are incredibly complex systems. But when we sit down to think about them in quantitative ways, it's natural to keep things simple at first. We look for reliable relations between small numbers of variables, seek equilibrium configurations, and so forth. But those approaches don't always work in complex systems, and sometimes we have to use methods that are specifically adapted to the challenges of complexity. That's the perspective of W. Brian Arthur, a pioneer in the field of complexity economics, according to which economies are typically not in equilibrium, not made of homogeneous agents, and are being constantly updated. We talk about the basic ideas of complexity economics, how it differs from more standard approaches, and what it teaches us about the operation of real economies.

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W. Brian Arthur received his Ph.D. in operations research from the University of California, Berkeley. He is currently an External Faculty Member at the Santa Fe Institute, IBM Faculty Fellow, and Visiting Researcher in the Intelligent Systems Lab at PARC. He was formerly the Morrison Professor of Economics and Population Studies and Professor of Biology at Stanford. He is known for developing the theory of increasing returns in economics. Among his awards are a Guggenheim Fellowship, the Schumpeter Prize in economics, and the Lagrange Prize for complexity.

• Web site
• Santa Fe web page
• Google Scholar publications
• Wikipedia
• Amazon author page

Plato and Aristotle founded much of what we think of as Western philosophy during the fourth and fifth centuries BCE. Interestingly, that historical period also witnessed the foundation of some of the major schools of Chinese philosophy, especially Confucianism and Daoism. This is a long-overdue discussion of ancient Chinese ideas, featuring philosopher and religious-studies scholar Edward Slingerland. We talk about the relationship between these two schools of thought, and their differences and similarities with Western philosophy. One of the biggest ideas is wu wei, or "effortless action" — the way that true mastery consists of doing things without too much conscious control. Today we would call it "flow" or "being in the zone," but the idea stretches back quite a ways.

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Edward Slingerland received his Ph.D. in religious studies from Stanford. He is currently Distinguished University Scholar, Professor of Philosophy, and Associate Member of the departments of Asian Studies and Psychology at the University of British Columbia. He is Director of the Database of Religious History, and co-director of the Center for the Study of Human Evolution, Cognition, and Culture. Among his books are Trying Not to Try: Ancient China, Modern Science, and the Power of Spontaneity, and a translation of Confucius's Analects. His new book is Drunk: How We Sipped, Danced, and Stumbled Our Way to Civilization.

• Web site
• UBC web page
• Google Scholar publications
• Amazon.com author page
• Wikipedia
• Twitter

Welcome to the August 2021 Ask Me Anything episode of Mindscape! These monthly excursions are funded by Patreon supporters (who are also the ones asking the questions). I take the large number of questions asked by Patreons, whittle them down to a more manageable size — based primarily on whether I have anything interesting to say about them, not whether the questions themselves are good — and sometimes group them together if they are about a similar topic. Enjoy!

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Neuroscience has given us great insights into how our brains work. But there is still room for purely humanistic disciplines to help us think through our thoughts and emotions, not to mention the meaning of our lives. Mari Ruti is a professor of English literature, with expertise in critical theory, gender studies, and psychoanalysis, especially the work of French theorist Jacques Lacan. We talk about the psychological drive that is motivated by what Lacan calls "lack," which is related to "desire." We use this as a way to think about such essential human experiences as mourning, creativity, and love. (We don't talk about love enough here on the podcast.)

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Mari Ruti received her Ph.D. in comparative literature from Harvard University. She is currently a Distinguished Professor of critical theory and gender and sexuality studies at the University of Toronto. She is the co-editor of the Psychoanalytic Horizons book series for Bloomsbury.

• U Toronto web page
• Amazon.com author page
• Semantic scholar
• Wikipedia
• Twitter

The arrow of time — all the ways in which the past differs from the future — is a fascinating subject because it connects everyday phenomena (memory, aging, cause and effect) to deep questions in physics and philosophy. At its heart is the fact that entropy increases over time, which in turn can be traced to special conditions in the early universe. David Wallace is one of the world's leading philosophers working on the foundations of physics, including space and time as well as quantum mechanics. We talk about how increasing entropy gives rise to the arrow of time, and what it is about the early universe that makes this happen. Then we cannot help but connecting this story to features of the Many-Worlds (Everett) interpretation of quantum mechanics.

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David Wallace received a D.Phil. in Physics and a D.Phil. in Philosophy from Oxford University. He is currently W.A. Mellon Professor of Philosophy of Science, with joint appointments in the Philosophy Department and the Department of History and Philosophy of Science, at the University of Pittsburgh. He is the author of The Emergent Multiverse: Quantum Theory According to the Everett Interpretation. Among his honors are the Lakatos Award for outstanding contribution to the philosophy of science. His most recent book is Philosophy of Physics: A Very Short Introduction.

• Web site
• PhilPeople profile
• Google Scholar publications
• Amazon.com author page

Natural selection has done a pretty good job at creating a wide variety of living species, but we humans can't help but wonder whether we could do better. Using existing genomes as a starting point, biologists are getting increasingly skilled at designing organisms of our own imagination. But to do that, we need a better understanding of what different genes in our DNA actually do. Elizabeth Strychalski and collaborators recently announced the construction of a synthetic microbial organism that self-reproduces just like a normal unicellular creature. This work will help us understand the roles of genes in reproduction, one step on the road to making DNA molecules and artificial cells that will perform a variety of medical and biological tasks.

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Elizabeth Strychalski received her Ph.D. in physics from Cornell University. She is the founder and current leader of the Cellular Engineering Group at the National Institute of Standards and Technology. She serves on the steering group for the Build-A-Cell collaboration.

• NIST web page
• Google Scholar publications
• Talk on Controlling Biology with Complexity
• "Genetic requirements for cell division in a genomically minimal cell," Pelletier et al.

How can data be biased? Isn't it supposed to be an objective reflection of the real world? We all know that these are somewhat naive rhetorical questions, since data can easily inherit bias from the people who collect and analyze it, just as an algorithm can make biased suggestions if it's trained on biased datasets. A better question is, how do biases creep in, and what can we do about them? Catherine D'Ignazio is an MIT professor who has studied how biases creep into our data and algorithms, and even into the expression of values that purport to protect objective analysis. We discuss examples of these processes and how to use data to make things better.

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Catherine D'Ignazio received a Master of Fine Arts from Maine College of Art and a Master of Science in Media Arts and Sciences from the MIT Media Lab. She is currently an assistant professor of Urban Science and Planning and Director of the Data+Feminism Lab at MIT. She is the co-author, with Lauren F. Klein, of the book Data Feminism.

• Web site
• MIT web page
• Google Scholar publications
• Data + Feminism Lab
• Wikipedia
• Twitter

It's not easy, figuring out the fundamental laws of physics. It's even harder when your chosen methodology is to essentially start from scratch, positing a simple underlying system and a simple set of rules for it, and hope that everything we know about the world somehow pops out. That's the project being undertaken by Stephen Wolfram and his collaborators, who are working with a kind of discrete system called "hypergraphs." We talk about what the basic ideas are, why one would choose this particular angle of attack on fundamental physics, and how ideas like quantum mechanics and general relativity might emerge from this simple framework.

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Stephen Wolfram received his Ph.D. in physics from Caltech. He is the founder and CEO of Wolfram Research, and the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. Among his awards are a MacArthur Fellowship. Among his books is A New Kind of Science. He recently launched the Wolfram Physics Project.

• Web site
• Wolfram Research
• Talk on Computation and Fundamental Physics
• Amazon.com author page
• Wikipedia
• Twitter