Welcome back to Scaling Theory. In this episode, I speak with Matthew O. Jackson, the William D. Eberle Professor of Economics at Stanford University and an external faculty member at the Santa Fe Institute. Matthew is one of the founders of the modern economics of networks and the author of The Human Network and Social and Economic Networks.

We talk about the friendship paradox, why homophily slows how fast a society learns the truth but helps niche ideas catch fire, and the gossip study where villagers in southern India proved remarkably good at naming the most central spreaders in their community. We then turn to AI agents as a different species: Turing tests on LLMs, the steerability of agent personas through system prompts, and what to make of Moltbook, the social network for AI agents.

By the end, you will know why telling students how much their peers actually drink reduces binge drinking more than warning them about the dangers of alcohol, why the same network can spread a virus quickly and a belief slowly, and why AI agents change their behavior when asked to explain it.

Papers and works referenced in the conversation

Books

1. The Human Network: How Your Social Position Determines Your Power, Beliefs, and Behaviors — Matthew O. Jackson (Pantheon, 2019). https://web.stanford.edu/~jacksonm/books.html
2. Social and Economic Networks — Matthew O. Jackson (Princeton University Press, 2008). https://web.stanford.edu/~jacksonm/books.html

Part I — The scaling of human networks

1. "Diffusion and Contagion in Networks with Heterogeneous Agents and Homophily" — Matthew O. Jackson and Dunia López-Pintado, Network Science 1(1), 2013. https://arxiv.org/abs/1111.0073
2. "How Homophily Affects the Speed of Learning and Best-Response Dynamics" — Benjamin Golub and Matthew O. Jackson, Quarterly Journal of Economics 127(3), 2012. https://web.stanford.edu/~jacksonm/homophily.pdf
3. "Using Gossips to Spread Information: Theory and Evidence from Two Randomized Controlled Trials" — Abhijit Banerjee, Arun G. Chandrasekhar, Esther Duflo, and Matthew O. Jackson, Review of Economic Studies 86(6), 2019. https://academic.oup.com/restud/article/86/6/2453/5345571
4. "Empathy and Well-Being Correlate with Centrality in Different Social Networks" — Sylvia A. Morelli, Desmond C. Ong, Rucha Makati, Matthew O. Jackson, and Jamil Zaki, PNAS 114(37), 2017. https://www.pnas.org/doi/10.1073/pnas.1702155114

Part II — The scaling of AI agents

1. "Inequality's Economic and Social Roots: The Role of Social Networks and Homophily" — Matthew O. Jackson, in Advances in Economics and Econometrics: Twelfth World Congress of the Econometric Society (Cambridge University Press, 2025). https://arxiv.org/abs/2506.13016
2. "AI Behavioral Science" — Jackson, Mei, Wang, Xie, Yuan, Benzell, Brynjolfsson, Camerer, Evans, Jabarian, Kleinberg, Meng, Mullainathan, Ozdaglar, Pfeiffer, Tennenholtz, Willer, Yang, and Ye, arXiv 2509.13323, 2025. https://arxiv.org/abs/2509.13323
3. "A Turing Test of Whether AI Chatbots Are Behaviorally Similar to Humans" — Qiaozhu Mei, Yutong Xie, Walter Yuan, and Matthew O. Jackson, PNAS 121(9), 2024. https://www.pnas.org/doi/10.1073/pnas.2313925121

Welcome back to Scaling Theory. My guest today is Albert-László Barabási, Professor of Network Science at Northeastern University and one of the most cited scientists alive with over 320 000 citations. His books include Linked, The Formula, and Network Science.

In 1999, Albert-László Barabási published a paper that changed how we understand networks. The finding was this: real-world networks are not random. They are dominated by hubs. A few nodes collect most of the links, and they do so because they already have them. In this episode, he explains the details of what he actually found. We then move to the scaling of networks, and the temptation to control them. We conclude with a discussion about art, ballet dancers, architecture, and what mapping careers across disciplines reveals about how networks really work.

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

References:

➝ Papers

Barabási, A.-L. & Albert, R. "Emergence of Scaling in Random Networks." Science 286, no. 5439 (1999): 509–512. https://doi.org/10.1126/science.286.5439.509

Albert, R., Jeong, H. & Barabási, A.-L. "Diameter of the World-Wide Web." Nature 401 (1999): 130–131. https://doi.org/10.1038/43601

Watts, D.J. & Strogatz, S.H. "Collective Dynamics of 'Small-World' Networks." Nature 393 (1998): 440–442. https://doi.org/10.1038/30918

Erdős, P. & Rényi, A. "On Random Graphs." Publicationes Mathematicae 6 (1959): 290–297. https://snap.stanford.edu/class/cs224w-readings/erdos59random.pdf

➝ Books

Barabási, A.-L. Linked: The New Science of Networks. Cambridge, MA: Perseus Publishing, 2002. https://en.wikipedia.org/wiki/Linked:_The_New_Science_of_Networks

Barabási, A.-L. Network Science. Cambridge: Cambridge University Press, 2016. https://networksciencebook.com (open access)

Barabási, A.-L. The Formula: The Universal Laws of Success. New York: Little, Brown and Company, 2018. https://www.hachettebookgroup.com/titles/albert-laszlo-barabasi/the-formula/9780316505499

Welcome back to scaling theory. My guest today is ⁠Scott E. Page⁠, Distinguished University Professor of Complexity, Social Science, and Management at the University of Michigan, and an external faculty member at the Santa Fe Institute. He is an elected member of the National Academy of Sciences and the American Academy of Arts and Sciences, and a recipient of the Guggenheim Fellowship. His books include The Difference, Diversity and Complexity, The Diversity Bonus, and The Model Thinker.

In this episode of Scaling Theory, Scott walks us through what complexity actually is. He unpacks the difference between complicated and genuinely complex systems, explains why cognitively diverse teams systematically outperform homogeneous ones on complex tasks, and what that means for how organizations scale. We also take up path dependence, the spillover effects of overlapping games across platform ecosystems, and where complexity tools have changed real decisions in practice. We close on the single open problem whose resolution would most reshape our understanding of social systems. As you will hear, Scott’s thinking is exceptionally clear. It is always a pleasure to talk with him and to listen to his insights. I hope you enjoy our discussion.

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

**

Books

• Page, S.E. (2007). The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies. Princeton University Press.
• Page, S.E. (2011). Diversity and Complexity. Princeton University Press (Primers in Complex Systems).
• Page, S.E. (2018). The Model Thinker: What You Need to Know to Make Data Work for You. Basic Books.
• Miller, J.H. and Page, S.E. (2007). Complex Adaptive Social Systems: An Introduction to Computational Models of Social Life. Princeton University Press.

Peer-reviewed articles

• Hong, L. and Page, S.E. (2004). "Groups of diverse problem solvers can outperform groups of high-ability problem solvers." Proceedings of the National Academy of Sciences, 101(46): 16385–16389.
• Page, S.E. (2006). "Path Dependence." Quarterly Journal of Political Science, 1(1): 87–115.
• Page, S.E. (2007). "Type Interactions and the Rule of Six." Economic Theory, 30(2): 223–241.
• Bednar, J. and Page, S.E. (2007). "Can Game(s) Theory Explain Culture? The Emergence of Cultural Behavior Within Multiple Games." Rationality and Society, 19(1): 65–97.
• Bednar, J., Bramson, A., Jones-Rooy, A. and Page, S.E. (2010). "Emergent Cultural Signatures and Persistent Diversity: A Model of Conformity and Consistency." Rationality and Society, 22(4): 407–444.

My guest today is Cass R. Sunstein, University Professor at Harvard and one of the most influential legal and political thinkers of our time. A prolific author of dozens of books and hundreds of academic articles, Cass has shaped debates in constitutional law, administrative law, behavioral economics, and public policy. He is regularly ranked amongst the very top of the most cited legal scholars alive. Cass also served as Administrator of the White House Office of Information and Regulatory Affairs under President Obama. He has advised governments and international organizations around the world, and was awarded the Holberg Prize, the equivalent of a Nobel in law and the humanities.

His latest book, On Liberalism: In Defense of Freedom, is a systematic defense of the liberal tradition at a moment when it is, as he shows, under unprecedented pressure. Our conversation is centered around his book. We begin with the urgency at the heart of the book: how liberalism confronts critiques from moral conservatives and egalitarian progressives alike, what it means to defend the liberal framework in an era of fragmentation, etc. We then turn to questions of scaling: does liberalism have internal patterns or institutional mechanisms that allow it to scale across diverse societies. We grapple with how the liberal tradition’s “big tent” of thinkers (from Mill and Hayek to Roosevelt’s Second Bill of Rights) impact liberalism ability to scale. We also explore how liberalism navigates technological change, expertise versus public accountability, and the pretence of knowledge. I hope you enjoy our discussion.

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

**

References:

• On Liberalism (MIT Press, 2025) https://mitpress.mit.edu/9780262049771/on-liberalism/

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).

**

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

Welcome back to Scaling Theory. My guest today is Cristina Bicchieri, Professor of Social Thought and Comparative Ethics at the University of Pennsylvania, Director of the Center for Social Norms and Behavioral Dynamics, and one of the most influential scholars working on norm formation and collective behaviour. Her work is widely cited and, as we will talk about, has led to many field experiments and changes across the world.

In our conversation, Cristina and I talk about how norms emerge, scale, and sometimes collapse. We look at tipping signals, self-reinforcing equilibria, and why some norms spread through a population while others fail beyond small groups.

We then move to applied dimensions. Cristina takes us through the field experiments she has conducted and the patterns she has observed. Her work shows how norms and legal rules evolve together, which offers a fresh perspective on the forces that regulate and constrain much of what we do. We also talk about the challenges that appear when behaviours on digital platforms and AI ecosystems evolve faster than regulation. Finally, Cristina offers concrete guidance for policymakers and firms that want to design interventions grounded in norm theory.

I hope you will enjoy the conversation. Keep scaling, keep skating on thin ice.

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

Welcome back to Scaling Theory. My guest today is Robin Hanson, Associate Professor of economics at George Mason University. Robin has long been one of the most original thinkers on institutional design, collective intelligence, as explored in his books The Age of Em and The Elephant in the Brain. Across his career, he has pushed the boundaries of how societies can aggregate knowledge and make collective decisions when complexity scales faster than comprehension.

In this episode, Robin and I discuss how futarchy could scale that logic across our societies? As societies grow larger, representation, information, and incentives all begin to break down, and futarchy is one possible way to rebuild them. Robin and I talk about where this idea has been tested so far, what a real-world implementation might look like in a city or company, and why, despite its promise, futarchy hasn’t yet scaled.

Finally, we explore how new technologies like blockchain and AI might change the picture, whether they’ll make futarchy more viable, or perhaps even replace parts of it. And we look ahead to Robin’s vision from The Age of Em. When societies become unimaginably fast and complex, which human institutions survive, and which ones don’t?

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

Welcome back to Scaling Theory. My guest today is Robin Hanson, Associate Professor of economics at George Mason University. Robin has long been one of the most original thinkers on institutional design, collective intelligence, as explored in his books The Age of Em and The Elephant in the Brain. Across his career, he has pushed the boundaries of how societies can aggregate knowledge and make collective decisions when complexity scales faster than comprehension.

In this episode, Robin and I discuss how futarchy could scale that logic across our societies? As societies grow larger, representation, information, and incentives all begin to break down, and futarchy is one possible way to rebuild them. Robin and I talk about where this idea has been tested so far, what a real-world implementation might look like in a city or company, and why, despite its promise, futarchy hasn’t yet scaled.

Finally, we explore how new technologies like blockchain and AI might change the picture, whether they’ll make futarchy more viable, or perhaps even replace parts of it. And we look ahead to Robin’s vision from The Age of Em. When societies become unimaginably fast and complex, which human institutions survive, and which ones don’t?

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

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 Vinton G. Cerf, widely regarded as a “father of the Internet.” In the 1970s, Vint co-developed the TCP/IP protocols that define how data is formatted, transmitted, and received across devices. In essence, his work enabled networks to communicate, thus laying the foundation for the Internet as a unified global system. He has received honorary degrees and awards that include the National Medal of Technology, the Turing Award, the Presidential Medal of Freedom, the Marconi Prize, and membership in the National Academy of Engineering. He is currently Chief Internet Evangelist at Google.

In this episode, Vint reflects on the Internet’s path from ARPANET and TCP/IP to the scaling choices that made global connectivity possible. He explains why decentralization was key, and how fiber optics and data centers underwrote explosive growth. Vint also addresses today’s policy anxieties (fragmentation, sovereignty walls, and fragile infrastructures…) before looking upward to the interplanetary Internet now linking spacecraft. Finally, we turn to AI: how LLMs are reshaping learning and software, and why the next leap may be systems that question us back. I hope you enjoy our discussion.

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