Zum Auftakt des Real:labor Festivals gewährt uns Dr. Ksenia Keplinger Einblick in ihr Projekt über Facial Recognition Systems.

Human-in-the-loop (HITL) systems, which combine human intelligence with artificial intelligence (AI), have become integral to various tasks and decision-making processes in modern organizations. However, the factors that contribute to enhancing the performance of HITL in the workplace still remain unclear. This research aims to explore the interplay between AI advice and human expertise within HITL systems, with a specific focus on assessing their efficiency. By applying signaling theory to the HITL context, the study delves into how various signals influence the performance of HITL systems. By incorporating facial recognition systems as a novel context into organizational research, this study explores unique high-stakes scenarios in the complex and uncertain work environment. The findings, derived from three experimental studies with approximately 900 participants, reveal a significant positive impact of providing an option for employees to solicit AI advice. When AI signals are chosen by employees rather than forced upon them, participants are more likely to implement AI advice, thus enhancing the overall efficiency of HITL systems in the workplace. This research advances theoretical and empirical understanding of human-machine interaction in the workplace by expanding signaling theory to the HITL context and offering valuable recommendations for designing HITL systems that strike an optimal balance between human judgment and AI assistance.

Die Veranstaltung findet in englischer Sprache statt.