Game Changer - the game theory podcast

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.

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.

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.

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.

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.