
Sign up to save your podcasts
Or


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
Part I — The scaling of human networks
Part II — The scaling of AI agents
By Thibault Schrepel4.8
55 ratings
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
Part I — The scaling of human networks
Part II — The scaling of AI agents

16,174 Listeners

4,270 Listeners

2,342 Listeners

289 Listeners

208 Listeners

84 Listeners

10,254 Listeners

475 Listeners

19 Listeners