Scaling Theory

Welcome back to Scaling Theory. Today, we are taking on a surprising but deeply relevant topic: religion. We are not entering the realm of theology, but rather looking at religion the way an economist might look at a multinational corporation or a digital platform. Think of it this way: in the U.S. alone, faith-based organizations generate more annual revenue than Apple and Microsoft combined. So when we ask how religions scale, we are really asking how some of the world’s most enduring (and powerful) institutions grow, adapt, and persist.Our guest is Paul Seabright, Professor of Economics at the Toulouse School of Economics and author of The Divine Economy: How Religions Compete for Wealth, Power, and People.Paul and I talk about how religions scale, why rituals, doctrines, and compelling narratives matter for growth. We explore how religions act as multi-sided platforms, how they build robust networks that resist churn, and how technologies like the printing press and social media can reshape their reach. Toward the end, we explore whether new movements in the Silicon Valley function like new religions, and what their chances of success might be in today’s competitive market for belief. I hope you enjoy our discussion.You can follow me on X (@⁠ProfSchrepel⁠) and BlueSky (@⁠ProfSchrepel⁠) to receive regular updates.

My guest today is Eric von Hippel, Professor of Technological Innovation at the MIT Sloan School of Management. Eric is the author of numerous academic articles and books, including Free Innovation, Democratizing Innovation, and The Sources of Innovation, all published by MIT Press and available for free. Eric has accumulated over 90,000 citations on Google Scholar and has received many awards, including the Schumpeter School Prize (2017)—a particularly interesting recognition given his work on non-Schumpeterian innovation.In our conversation, Eric and I explore the role of free innovation in today’s economy. Eric highlights some of his favorite examples of free innovation and discusses how, despite being developed at personal cost, it is scaling at an impressive rate. We explore the mechanisms that best enable this scaling—whether through recognition, institutional support, IP protections, or alternative incentives. By the end of this talk, you will understand what free innovation is, how it develops, and how it interacts with producer innovation.You can follow me on X (@⁠ProfSchrepel⁠) and BlueSky (@⁠ProfSchrepel⁠) to receive regular updates.References:Sources of Innovation (1988) https://web.mit.edu/evhippel/www-old/books/sources/SofI.pdfDemocratizing Innovation (2005) https://direct.mit.edu/books/book-pdf/2425023/book_9780262285636.pdfFree Innovation (2016) https://library.oapen.org/bitstream/handle/20.500.12657/26044/1004041.pdf

My guest today is Larry Lessig, Professor of Law and Leadership at Harvard Law School. Larry is the author of numerous influential books and articles, including Code 2.0 (2006), which we discuss at length in this episode. If you have been listening to Scaling Theory since the very beginning, you probably remember that I cited a couple of books that changed my perception of everything in the first episode. Code 2.0 is one of these books. Larry Lessig develops what he calls the “pathetic dot theory,” in which he explains that all things are influenced by four constraints: the law, economic forces, norms, and architecture. In this conversation, Larry and I talk about the importance of these four constraints in the digital economy and assess which ones have scaled the most in recent years. We also explore how complexity science can contribute to Larry’s theory by seeing the dots and their constraints as a complex network. We then steer our conversation toward open source in AI, examine how regulation at the hardware layer could solve software issues, and consider whether we can trust our institutions and current regulations to do so, or if we need to scale other institutions for that purpose. I hope you enjoy our discussion. References: Code 2.0 (2006) https://lessig.org/product/codev2/ Code (1999) https://lessig.org/product/code/ You can follow me on X (@ProfSchrepel) and BlueSky (@profschrepel) to receive regular updates.

My guest today is Kevin Kelly, the author of 14 books, a public speaker who has delivered TED talks with tens of millions of views, and a technology expert. In 1983, Kevin was hired by Whole Earth founder Stewart Brand to edit several later editions of the Whole Earth Catalog, the Whole Earth Review, and Signal. He later on served as the founding executive editor of the magazine Wired. In our conversation, Kevin and I talk about the scaling laws behind all technologies, but also how these laws intersect with biology, society, and policy. We explore themes from What Technology Wants, we focus on the 'Triad of Evolution' and the concept of convergence, and connect these ideas to antitrust and innovation policy. I also touch on his earlier work, including New Rules for the New Economy, where we discuss the dynamics of trust in network economies and its implications for technology adoption. Finally, we delve into the inevitability of technological evolution, its accelerating diffusion, and what happens when technology becomes ubiquitous in society. These questions feel increasingly urgent as we approach 2025, a pivotal moment for revisiting these ideas in light of modern developments. I hope you enjoy our discussion. Find me on X (@ProfSchrepel) and BlueSky (@profschrepel.bsky.social). References Kevin Kelly, What Technology Wants (2010) Kevin Kelly, New Rules for the New Economy (1998) Rishi Bommasani et al., Considerations for Governing Open Foundation Models (2023) https://hai.stanford.edu/issue-brief-considerations-governing-open-foundation-models

My guest is Stefan Thurner, A Professor of theoretical physics, and the President of the Complexity Science Hub in Vienna. Stefan has published over 240 scientific articles and he was elected Austrian Scientist of the Year 2017. He is also an external professor at the Santa Fe Institute. In our conversation, we first delve into the scaling laws of everything. We explore social, financial, biological, and economic dynamics—for example, how to make the economy more resilient by targeting some unique companies, how social bubbles form, the strength of networks of friends and foes in social contexts, and how the methodology of physics can help us understand other fields, etc. I hope you enjoy our discussion. Find me on X at @⁠⁠⁠⁠ProfSchrepel⁠⁠⁠⁠⁠⁠⁠. Also, be sure to subscribe. *** References: ➝ Measuring social dynamics in a massive multiplayer online game (2010) ➝ How women organize social networks different from men (2013) ➝ Multirelational Organization of Large-Scale Social Networks in an Online World (2010) ➝ What is the minimal systemic risk in financial exposure networks? (2020) ➝ Scaling laws and persistence in human brain activity (2003) ➝ New Forms of Collaboration Between the Social and Natural Sciences Could Become Necessary for Understanding Rapid Collective (2024) ➝ Quantifying firm‐level economic systemic risk from nation‐wide supply networks (2022) ➝ Fitting Power-laws in Empirical Data with Estimators that Work for All Exponents (2017) ➝ Complex Systems: Physics Beyond Physics (2017) ➝ Systemic Financial Risk: Agent-based Models to Understand the Leverage Cycle on National Scales and its Consequences (2011) ➝ Peer-review in a world with rational scientists: Toward selection of the average (2010)

My guest today is Michael Mauboussin (@mjmauboussin), one of the world’s leading experts in finance. Michael serves as Head of Consilient Research at Counterpoint Global, Morgan Stanley. He has authored three books and regularly appears in the Wall Street Journal, Financial Times, New York Times, and other publications. Since 1993, Michael has been an adjunct professor of finance at Columbia Business School and is also the chairman emeritus of the board of trustees at the Santa Fe Institute. In our conversation, we delve into the dynamics of markets, discuss all sorts of increasing returns, and explore topics such as Charles Darwin, policymaking, AI and Web3, and the Santa Fe Institute. I hope you enjoy our discussion. Find me on X at @⁠ProfSchrepel⁠⁠⁠⁠. Also, be sure to subscribe to the Scaling Theory podcast. ** References: Michael J. Mauboussin & Dan Callahan, "Increasing Returns: Identifying Forms of Increasing Returns and What Drives Them" (2024) https://perma.cc/Y3DN-LNMY Michael J. Mauboussin & Dan Callahan, "Stock Market Concentration: How Much Is Too Much?" (2024) https://perma.cc/7EEX-ZY9T Charles Darwin, The Autobiography of Charles Darwin: 1809-1882 https://www.amazon.com/Autobiography-Charles-Darwin-1809-1882/dp/0393310698 David Warsh, Knowledge and the Wealth of Nations: A Story of Economic Discovery (2007) https://www.amazon.com/Knowledge-Wealth-Nations-Economic-Discovery/dp/0393329887 James Bessen, The New Goliaths: How Corporations Use Software to Dominate Industries, Kill Innovation, and Undermine Regulation (2022) https://www.amazon.nl/-/en/James-Bessen/dp/0300255047 Chris Dixon, Read Write Own: Building the Next Era of the Internet (2023) https://readwriteown.com Anu Bradford, Digital Empires: The Global Battle to Regulate Technology (2023) https://global.oup.com/academic/product/digital-empires-9780197649268 Kenneth J. Arrow, "The Economic Implications of Learning by Doing" (1962) https://www.jstor.org/stable/2295952 J. Doyne Farmer, Making Sense of Chaos (2024) https://www.penguin.co.uk/books/284357/making-sense-of-chaos-by-farmer-j-doyne/9780241201978