Prof. Dr. Kevin Bauer: Knowing (not) to know: XAI, task delegation, and human metaknowledge

Humans and artificial intelligence (AI) often possess complementary capabilities that can lead to substantial efficiency gains through collaboration. A potentially effective strategy to leverage these complementary capabilities involves humans allocating tasks between themselves and AI. Echoing Adam Smith's principles of efficient labor division, synergies emerge when humans assign tasks to AI where it has a higher likelihood of success and retain other tasks for themselves. However, previous studies indicate that human task allocation to AI is frequently suboptimal, thus forgoing potential gains in efficiency. A primary obstacle is humans' inadequate understanding of the scope and limits of their own task-relevant knowledge, i.e., a lack of metaknowledge. In his talk, Kevin Bauer presents the findings of a paper that explores whether Explainable AI can improve human metaknowledge and thereby enhance delegation efficiency in human-AI collaborations. We devise a formal model and empirically validate its theoretical predictions through an incentivized field experiment with professional real estate experts in Germany. In a field study, experts decide whether to evaluate apartments themselves or to delegate tasks to an AI. After task allocation, both agents and AI independently assess assigned apartments. We exogenously vary whether the AI is a black box or features explanations about its learned logic of how apartment characteristics determine prices. Our findings reveal that explanations of the AI's pricing logic substantially increase both the frequency and quality of delegation decisions, fostering more effective human-AI collaboration and task performance. We show that improvement in delegation quality is largely due to an improved understanding of the scope and limits of their own task-relevant knowledge. Our results indicate that explainability can be a crucial catalyst to enhance not only humans' understanding of the AI's capabilities but also their own, leading to better delegation. Our findings have implications for the design of AI systems in collaborative delegation settings.

Kevin Bauer is Assistant Professor of E-Business and E-Government at the University of Mannheim, and starting in 2025, he will be Professor for Game-Theoretic and Causal AI in Business and Economics at Goethe University Frankfurt. His research bridges economics and computer science, focusing on explainable AI, algorithmic transparency, causal machine learning, and human information processing. His work is published in top-tier journals such as Information