AI Institute Seminar: “Algorithmic Institutions” by Dr Alicia von Schenk

Abstract:
Institutions aim to promote and stabilize cooperation in groups, including detection and punishment of misconduct. When a human leader can punish, such regimes successfully establish cooperation and are ultimately preferred over sanction-free institutions. Yet, the role of algorithm-led institutions as a potentially unbiased alternative to human-managed institutions is unexplored. Can an algorithmic institution with adaptive punishment promote cooperation in groups more efficiently? Would people voluntarily opt into a social contract granting an algorithmic institution monopoly on punishment? First, participants in an online experiment interact in a public goods game with either a human manager or an algorithmic manager trained with participants’ previous behaviour using reinforcement learning.  Second, we let participants select into several institutions with either human or algorithmic monopoly on power.
 
Suggested readings:
Gürerk, Özgür, Bernd Irlenbusch, and Bettina Rockenbach. "The competitive advantage of sanctioning institutions." Science 312.5770 (2006): 108-111.
 
Speaker Short Bio:
Alicia von Schenk is a postdoctoral researcher at the Center for Humans and Machines of the Max Planck Institute for Human Development, Berlin. She received her PhD in economics from Goethe University Frankfurt in May 2021. Her thesis on “Organizational Behavior and Economic and Ethical Implications of Artificial Intelligence” addresses inefficiencies in human decision-making and takes a microeconomic perspective on the potential of new technologies for satisfactory work environments. Before joining the PhD program at the Graduate School for Economics, Finance, and Management at Goethe University Frankfurt, she completed her BSc and MSc in Mathematics and her BSc and MSc in (Quantitative) Economics. Alicia's main research interests are the economic and ethical aspects of AI, and organizational and behavioral economics.