Cybernetics: The Science Economics Should Have Become

Cybernetics: The Science Economics Should Have Become

Dan Davies — economist, FT contributor, former investment bank analyst, and author of The Unaccountability Machine and Lying for Money — joins Danny Buerkli to make the case that management cybernetics is the science economics should have turned into. Hayek and Coase settled the economics of information in the 1930s, before Shannon and Turing gave the field a rigorous concept of information to build on. They also discuss why the optimal amount of fraud is not zero, what actually killed Credit Suisse, why LLMs only buy organizations a few years against growing complexity, who answers for decisions no human made, and how to spot a doomed project by drawing up an information balance sheet. Dan's books: The Unaccountability Machine [https://profilebooks.com/work/the-unaccountability-machine/] and Lying for Money [https://www.simonandschuster.com/books/Lying-for-Money/Dan-Davies/9781982114947]. The Niskanen working paper, which is a preview of his upcoming book: The Problem Factory [https://www.niskanencenter.org/the-problem-factory-preemptive-risk-aversion-in-infrastructure-planning-and-the-role-of-professional-services/].

Wardley Maps: How to Cheat at Predicting the Future – with Simon Wardley

Simon Wardley — former CEO and creator of Wardley Mapping — joins Danny Buerkli to talk about how he went from feeling like a "fake CEO" to finding one of the most useful ways of thinking about strategy. Simon also explains how he "cheats" at prediction, calling cloud, serverless, vibe coding, and the rise of intelligent agents years — sometimes decades — before they arrived. They also talk about why data centers are heading to space, what "SpimeScript" will do to every supply chain on Earth, why he thinks China will win the AI race, and how large language models are a non-kinetic form of warfare. Simon's book can be found here [https://github.com/HiredThought/wardley-maps-ebook/raw/main/bin/Wardley%20Maps%20-%20Simon%20Wardley.pdf]. One of the most useful brief introductions to Wardley Mapping and strategy, by Dave Hora, is here [https://www.davesresearch.com/wardley-mapping/].

AI Strategy for Middle Powers – with Anton Leicht

If you don't have a frontier AI lab within your borders, as a country, what exactly is your plan? Anton Leicht — visiting scholar at the Carnegie Endowment for International Peace and author of the "Threading the Needle" Substack — joins Danny Buerkli to talk through the strategic options available to middle powers. They discuss why the UK seems more situationally aware than others, what leverage the Netherlands truly has (or not) thanks to ASML, and why the window to act may be measured in low single-digit years rather than decades.

The Quest for the Perfect Weapon – with Jeff Stern

Jeff Stern — reporter and author of The Warhead — joins Danny Buerkli to talk about the long quest to build the “perfect weapon.” They discuss how a company mostly known for calculators revolutionized warfare, the paradox of precision-guided munitions, what disappears behind the language of “surgical” force, and how covering conflict changed Jeff’s understanding of his own role as a reporter.

Intelligence Saturation and the Economics of AI – with Ioana Marinescu

Ioana Marinescu — associate professor at the University of Pennsylvania, research associate at the NBER, and member of Anthropic's Economic Advisory Council — joins Danny Buerkli to discuss her "intelligence saturation" paper, which divides the economy into an intelligence sector and a physical sector to model what happens as AI automates cognitive work. They discuss why a recent scenario piece that moved markets gets the economics wrong, what parameters to watch to understand where we're headed, why being first to AGI may matter less than people think, her policy proposals for AI Adjustment Insurance and a Digital Dividend, what UBI experiments do and don't tell us about a world without work, Ioana's favorite theory of divorce, and what it feels like to be an intelligence worker watching AI get better at your job.