Scaling Theory – Details, episodes & analysis

In the very first episode of Scaling Theory, I mentioned a few scientists who have shaped my understanding of the world. At the very top of that list is today’s guest: W. Brian Arthur.

Brian was born and raised in Belfast, Northern Ireland, and went on to become one of the most important figures of complexity science. Today, he is widely known as the father of complexity economics, a field that has transformed how we think about the evolution of modern economies.

His influence is remarkable. Brian’s work has been cited more than 58,000 times according to Google Scholar. He received numerous awards and recognition, such as being the inaugural laureate of the Lagrange Prize in Complexity Science, an award that many have described as complexity’s equivalent of the Nobel Prize. Brian has been, at age 37, the youngest endowed chair holder at Stanford University. He went on to work for my institutions, including the Santa Fe Institute, as we will talk about. On a personal note, I consider Brian a friend.

Now, what makes me especially happy to have Brian on the podcast is the unique perspective he brings on how economies form and evolve. His understanding of technology, how it emerges and scales, offers a lens that none others have developed. It is a way of seeing economic life as something alive. Be ready to be blown away.

You can follow me on X (@⁠ProfSchrepel⁠) and BlueSky (@⁠ProfSchrepel⁠).

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References:

• W. Brian Arthur, Competing Technologies, Increasing Returns, and Lock-In by Historical Events (1989) https://www.rochelleterman.com/ir/sites/default/files/arthur 1989.pdf
• W. Brian Arthur, Foundations of Complexity Economics (2021) https://pmc.ncbi.nlm.nih.gov/articles/PMC7844781/pdf/42254_2020_Article_273.pdf
• W. Brian Arthur, The Nature of Technology: What It Is and How It Evolves (2009)
• W. Brian Arthur, Economics in Nouns and Verbs (2023) https://www.sciencedirect.com/science/article/pii/S0167268122003936
• Thibault Schrepel, The Evolution of Economies, Technologies, and Other Institutions: Exploring W. Brian Arthur's Insights (2024) https://www.cambridge.org/core/services/aop-cambridge-core/content/view/8809341E2E94D76B8CCAB4A4DDACBC4C/S1744137424000067a.pdf/evolution_of_economies_technologies_and_other_institutions_exploring_w_brian_arthurs_insights.pdf

This is the first solo episode of Scaling Theory, where I take a deep dive into the literature. Building on a working paper titled “Adaptive Regulation,” I explore why “future-proof” laws so often fail in the face of rapid technological change, and how complexity science can guide us toward rules that adapt to the things they regulate. Drawing on recent EU digital acts and voices from law, economics, and complexity theory, I sketch the contours of a regulatory system that scales.

You can follow me on X (@⁠⁠ProfSchrepel⁠⁠) and BlueSky (@⁠⁠ProfSchrepel⁠⁠).

References:

• Schrepel, T., Adaptive Regulation (2025) https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5416454
• Ranchordás, S., & Van‘t Schip, M. (2020). Future-Proofing Legislation for the Digital Age. In Time, Law, and Change: An Interdisciplinary Study.
• Colomo, P. I. (2022). Future-Proof Regulation against the Test of Time: The Evolution of European Telecommunications Regulation. Oxford Journal of Legal Studies, 42(4).
• Chander, A. (2017). Future-proofing law. UC Davis Law Review.
• Powell, W. W., & Snellman, K. (2004). The Knowledge Economy. Annual Review of Sociology, 30.
• Perez, C. (2009). The Double Bubble at the Turn of the Century: Technological Roots and Structural Implications. Cambridge Journal of Economics, 33(4), 779–805.
• Allen, D. W., Berg, C., & Potts, J. (2025). Institutional Acceleration: The Consequences of Technological Change in a Digital Economy. Cambridge University Press.
• Colander, D., Holt, R. P. F., & Rosser, J. B. (2004). The Changing Face of Mainstream Economics. Review of Political Economy, 16(4).
• Arthur, W. B. (2009). The Nature of Technology: What It Is and How It Evolves. New York: Free Press.

• Buchanan, J. M., & Tullock, G. (1962). The Calculus of Consent: Logical Foundations of Constitutional Democracy. University of Michigan Press.
• Sowell, T. (2007). A Conflict of Visions: Ideological Origins of Political Struggles.
• West, G. (2017). Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies. Penguin Press.

My guest today is Eric Beinhocker, Professor of Practice in Public Policy at the Blavatnik School of Government, University of Oxford, and the founder and Executive Director of the Institute for New Economic Thinking at the University’s Oxford Martin School. Eric is the author of numerous academic articles and books, including The Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics (2007).

In our conversation, Eric and I contrast traditional economics (neoclassical theory) with new economics (complexity economics). We also explore the policy implications of these differing economic theories, discussing topics ranging from aggressive growth strategies to complexity catastrophes in digital economies. I hope you enjoy our conversation.

References:

• The origin of wealth: Evolution, complexity, and the radical remaking of economics (2007) ⁠https://moldham74.github.io/AussieCAS/papers/Origins⁠ of Wealth.pdf
• Getting Big Too Fast: Strategic Dynamics with Increasing Returns and Bounded Rationality (2007) ⁠https://pubsonline.informs.org/doi/pdf/10.1287/mnsc.1060.0673⁠

• Fair Social Contracts and the Foundations of Large-Scale Collaboration (2022) ⁠https://oms-inet.files.svdcdn.com/staging/files/Fair-Social-Contracts-Beinhocker-v8-22-22.pdf⁠
• Reflexivity, complexity, and the nature of social science (2013) ⁠https://www.tandfonline.com/doi/full/10.1080/1350178X.2013.859403⁠

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 today is Rory Linkletter, a professional athlete who recently ran the Paris Olympic Marathon and the New York Marathon. Rory’s current personal best in the marathon is an impressive 2:08:01, which makes him the top Canadian marathon runner and the third-best Canadian performance ever.

This episode, as you might guess, is different from the others. I wanted to talk to Rory because he inspired me greatly when I went to Paris to watch the race. Most importantly, I am convinced that there is much we can learn from professional athletes, especially marathon runners.

In our conversation, we explore how Rory scaled his mental and physical abilities. I draw many parallels with the academic and policy worlds, delving into what we can learn from his process, the power laws he has identified, and his relationship with science.

Scaling Theory is not turning into a running podcast, but, true to its mission, it remains focused on exploring the scaling laws behind everything—be it economic, technical, or biological systems. Rory opens new doors regarding this last subject. I hope you enjoy our discussion.

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.

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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 Allison Stanger. Allison is a Middlebury Distinguished Endowed Professor; an Affiliate at the Berkman Klein Center for Internet and Society, Harvard University; the Co-Director (with Danielle Allen) of the GETTING-Plurality⁠ Research Network, Harvard University; founding member of the Digital Humanism Initiative (Vienna); and an External Professor at the Santa Fe Institute. Allison’s next book, Who Elected Big Tech? is under contract with Yale University Press.

In this conversation, Allison and I delve into the political science surrounding large tech companies. We explore their effects on consumers and democracy, the interplay between capitalism and democracy, the dangers of fragmented regulation, what the effective governance of social media entails, how to scale and measure it, potential areas of cooperation with China, and the relevance of public choice theory, complexity science, and power laws in shaping our understanding of technology. I hope you enjoy our discussion.

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References

• Stanger, Allison. "The Real Cost of Surveillance Capitalism: Digital Humanism in the United States and Europe." Perspectives on Digital Humanism (2022): 33-40. https://library.oapen.org/bitstream/handle/20.500.12657/51945/978-3-030-86144-5.pdf

• Werthner, Hannes, et al. "Digital humanism: The time is now." Computer 56.1 (2023): 138-142. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10008968
• Soros, George. "Fallibility, reflexivity, and the human uncertainty principle." Journal of Economic Methodology 20.4 (2013): 309-329. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10008968

My guest is Arvind Narayanan, a Professor of Computer Science at Princeton University, and the director of the Center for Information Technology Policy, also at Princeton. Arvind is renowned for his work on the societal impacts of digital technologies, including his textbook on fairness and machine learning, his online course on cryptocurrencies, his research on data de-anonymization, dark patterns, and more. He has already amassed over 30,000 citations on Google Scholar.

In just a few days, in late September 2024, Arvind will release a book co-authored with Sayash Kapoor titled “AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference.” Having had the privilege of reading an early version, our conversation delves into some of the book’s key arguments. We also explore what Arvind calls AI scaling myths, the reality of artificial general intelligence, how governments can scale effective AI policies, the importance of transparency, the role that antitrust can, and cannot play, the societal impacts of scaling automation, and more. I hope you enjoy our conversation.

Find me on X at @⁠⁠⁠ProfSchrepel⁠⁠⁠⁠⁠⁠. Also, be sure to subscribe.

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References:

➝ AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference (2024)

➝ AI scaling myths (2024)

➝ AI existential risk probabilities are too unreliable to inform policy (2024)

➝ Foundation Model Transparency Reports (2024)

My guest today is ⁠Sara Hooker⁠, VP of Research at Cohere, where she leads Cohere for AI, a non-profit research lab that seeks to solve complex machine learning problems with researchers from over 100 countries. Sara is the author of numerous research papers, some of which focus specifically on scaling theory in AI. She has been listed as one of AI’s top 13 innovators by Fortune.

In our conversation, we first delve into the scaling laws behind foundation models. We explore what powers the scaling of AI systems and the limits to scaling laws. We then move on to discussing openness in AI, Cohere’s business strategy, the power of ecosystems, the importance of building multilingual LLMs, and the recent change in terms of access to data in the space. I hope you enjoy our conversation.

Find me on X at @⁠⁠ProfSchrepel⁠⁠⁠⁠⁠. Also, be sure to subscribe.

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References:

➝ Sara Hooker, On the Limitations of Compute Thresholds as a Governance Strategy (2024)

➝ Sara Hooker, The Hardware Lottery (2020)

➝ Sara Hooker, Moving beyond “algorithmic bias is a data problem” (2021)➝ Longpre et al., Consent in Crisis: The Rapid Decline of the AI Data Commons (2024)

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.

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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