Complementarity in human-AI collaboration: concept, sources, and evidence

Niklas Kuehl

Abstract:

Atificial intelligence (AI) has the potential to significantly enhance human performance across
various domains. Ideally, collaboration between humans and AI should result in complemen-
tary team performance (CTP)—a level of performance that neither of them can attain indivi-
dually. So far, however, CTP has rarely been observed, suggesting an insufficient understanding
of the principle and the application of complementarity. Therefore, we develop a general
concept of complementarity and formalize its theoretical potential as well as the actual realized
effect in decision-making situations. Moreover, we identify information and capability asym-
metry as the two key sources of complementarity. Finally, we illustrate the impact of each
source on complementarity potential and effect in two empirical studies. Our work provides
researchers with a comprehensive theoretical foundation of human-AI complementarity in
decision-making and demonstrates that leveraging these sources constitutes a viable pathway
towards designing effective human-AI collaboration, i.e., the realization of CTP