In this episode, we explore the challenges of multi-party negotiations and why reaching agreement becomes exponentially harder as more stakeholders enter the room. Our guest Lawrence Susskind explains the principles of the Mutual Gains Approach and we discuss applications ranging from local disputes over renewable energy projects to the intricacies of building data centres and setting up other large-scale infrastructure investments. Along the way, we examine why organisations often underestimate stakeholder concerns and what they can do to build durable agreements. Lawrence Susskind is the Ford Professor of Urban and Environmental Planning at MIT and co-founder of the Program on Negotiation at Harvard Law School.
Erschienen: 03.07.2026
Dauer: 36:18
In this episode, we explore what it really means to make a "good" prediction. Starting with something as ordinary as a weather forecast, we discuss why forecasting poses deep economic and game theoretic questions. Together with our guest Rakesh Vohra, we unpack the concept of calibration, examine how forecasts can be evaluated, and revisit the surprising insight that even someone without meteorological expertise can produce calibrated weather predictions. Rakesh Vohra is the George A. Weiss and Lydia Bravo Weiss University Professor of Economics at University of Pennsylvania. You can find his paper co-authored with Dean Foster on calibration here.
Erschienen: 22.06.2026
Dauer: 19:38
In this episode, we explore how digital platforms transformed markets by dramatically reducing search costs and information asymmetries. Together with Sarah Auster, we dive into the "digital paradox" of endless choice, the unintended consequences of frictionless search, and what this means for the future design of platforms like Netflix and Amazon. Along the way, we uncover the broader economic story behind the evolution of the internet economy and the game-theoretic forces shaping digital markets today. Sarah Auster is a Professor of Economics at University of Bonn. You can find the papers relevant to this episode here: Simultaneous Search and Adverse Selection and Pandora's Box Reopened: Robust Search and Choice Overload.
Erschienen: 08.06.2026
Dauer: 20:03
In this episode, we discuss zero-sum games and zero-sum thinking with our guest, Nageeb Ali. We begin by looking at the broader picture of how zero-sum thinking has become increasingly prominent in today's public debate and how it relates to Akerlof's classic "lemons" problem. Drawing on ideas from economics and game theory, Nageeb shares research connecting zero-sum thinking to questions in political economy and organizations. He explains how zero-sum thinking can emerge even when policies are not objectively zero-sum: when individuals have different information and different interests, support for a policy by others may itself become a signal that the policy is bad for you. Later in the episode, Nageeb discusses how one-sided asymmetric information in organisational settings can lead to adverse selection and how these dynamics relate to zero-sum thinking more broadly. Nageeb Ali is a Professor of Economics at Penn State University.
Erschienen: 25.05.2026
Dauer: 30:12
In this episode, we speak with Thilo Klein about daycare allocation in Germany – a problem that is still mostly run by uncoordinated offers, even though it is well understood in matching theory. The gap isn't theory; it's the missing layer that turns academic mechanisms into systems municipalities can actually run. Thilo Klein traces how that layer is now being built – through years of research, an open-source experiment that taught hard lessons, and a spin-out. A conversation about market design where it lands. Thilo Klein is Professor of Quantitative Economics at Pforzheim Business School and a senior researcher at ZEW – Leibniz Centre for European Economic Research. He is also the co-founder of MatchingTools, a company that develops software for real-world matching problems, including KitaMatch, a platform for daycare allocation. Learn more at https://matchingtools.de.
Erschienen: 13.05.2026
Dauer: 21:40
In this episode, we speak with Rosemarie Nagel about the Beauty Contest, a classic game in economics. She introduces the setup, its origins, and the early research behind it. We then take a deeper look at the key insights from the Beauty Contest, in particular the concept of level-k reasoning and what it reveals about strategic thinking. Furthermore, Rosemarie shares how findings from these experimental studies have been linked to research on brain activity, offering a unique perspective on decision-making and the functioning of our brains. Finally, she offers a connection to real-world problems involving strategic reasoning. Rosemarie Nagel is an ICREA Research Professor at Universitat Pompeu Fabra (UPF) and the Barcelona School of Economics (BSE). As an experimental economist, her research builds bridges between economic theory and behavioral evidence through cognitive models informed by game theory, psychology, neuroscientific methods, and both laboratory and field experiments. Find two papers on the beauty contest game played with newspaper readers and with neuroscientific tools.
Erschienen: 20.04.2026
Dauer: 25:22
Europe's energy crisis has exposed deep structural flaws in how electricity markets work. But according to economist Natalia Fabra, much of the current debate is focused on the wrong problem. In this episode, we unpack why high prices are not simply a result of market design choices like uniform pricing – and why the real issue runs deeper. From the role of gas in price formation to the fundamental mismatch between short-term markets and long-term investment needs, this conversation reframes how we should think about the energy transition. Natalia Fabra is Professor of Economics at the CEMFI Madrid and one of Europe's leading experts on energy markets and regulation. Her research focuses on market design, competition, and the transition to low-carbon energy systems.
Erschienen: 30.03.2026
Dauer: 26:17
In this episode, we explore how game theory and economics can inform the use of AI. Our guest, Annie Liang, introduces the concept of AI clones, systems designed to imitate specific humans, and discusses their potential applications, for example in recruiting. We examine the trade-off between the efficiency gains the clones can provide and the costs that arise when AI cannot perfectly create such clones without error. The conversation then turns to creative ownership, focusing not only on content but also on the ownership of creative style as AI becomes increasingly capable of reproducing it. Finally, we discuss how insights from information design can contribute to the broader debate on AI. Annie Liang is an associate professor of economics and (by courtesy) of computer science at Northwestern University.
Erschienen: 17.03.2026
Dauer: 22:43
Can we trust lab experiments to predict real-world behaviour? In this episode, we explore the question of external validity together with Jan Stoop. From classic dictator games in the lab to misdelivered envelopes with real cash in private homes, we discuss whether people act differently when they are being observed - and what happens when established lab findings meet reality. We also talk about rich versus poor behaviour, financial stress, and why small "hassle costs" can create large inequalities in outcomes. Jan Stoop is Associate Professor at Tilburg University and Erasmus University Rotterdam. His research focuses on behavioural and experimental economics, with a particular emphasis on pro-social and unethical behaviour, financial stress, and inequality. He is known for creative field experiments that rigorously test whether laboratory results hold in real-world settings.
Erschienen: 04.03.2026
Dauer: 32:03
What happens when an AI system faithfully follows a flawed goal? In this episode, we explore how even well-designed algorithms can produce dangerous outcomes — from amplifying hate speech to mismanaging infrastructure — simply by optimising a reward function which, like all reward functions, fails to encode all that matters. We discuss the hidden risks of reinforcement learning, why over-optimisation can backfire, and how game theory helps us rethink what it means for AI to act "rationally" in complex, real-world environments. Jobst Heitzig is a mathematician at the Potsdam Institute for Climate Impact Research and an expert in AI safety and decision design.
Erschienen: 17.02.2026
Dauer: 26:45
