The Role of AI and Human–AI Ensembles in Strategic Decision Making

In this research stream, we study how artificial intelligence (AI) changes the nature and quality of strategic decision making, with a particular focus on Human–AI ensembles – settings in which humans and AI systems are jointly involved with decision making.

We conduct a series of studies combining field and laboratory experiments. In our field experiments, we examine how different types of AI systems – such as those varying in functionality, or those tailored to human preferences and information-processing styles – affect the adoption of AI, the willingness to collaborate with AI, and ultimately, performance outcomes in strategic contexts.

In our laboratory experiments, we take a closer look at the dynamics within Human–AI ensembles. Here, we explore whether and how humans can effectively deal with typical problems associated with AI, such as various forms of model drift. We also study how increases in noise, often observed in recent large language models (LLMs), influence the quality of strategic decision making when humans and AI collaborate.

The research on this topic is primarily conducted by Johannes Luger, Robert Janjic, and international coauthors.