Selecting and using information for decision support
Selecting and using information for decision support
Yoav Ben Yaakov, PhD. student at the department of Industrial Engineering
Advisor:Prof. Joachim Meyer
Abstract:
Decision support (DS), increasingly based on Artificial Intelligence (AI), is developing rapidly. Still, human decision-makers remain strongly involved in the various supported decision processes in professional and everyday tasks. This research presents a series of experimental studies that investigate the influence of key factors on users' decisions to access the information from DS systems and to use it in their decisions. We study how the DS cost, reliability, information redundancy, display format, and uncertainty influence users’ willingness to seek assistance, their trust in the system, task performance, decision time, and cognitive workload. Through controlled experiments (N=792) simulating medical and geological classification tasks, we analyze how DS access relates to performance and uncover systematic biases in human decision-making. Our findings highlight the influence of prior experience with both the task and the system, emphasize the role of unique information in guiding decisions, and show how different information formats impact cognitive workload. This research contributes to a deeper understanding of human-DS interaction and offers actionable insights for designing more effective and user-friendly support systems.
Bio:
Yoav Ben Yaakov is a PhD candidate in the Department of Industrial Engineering at Tel Aviv University, advised by Prof. Joachim Meyer. His research focuses on decision-making in Human-Computer Interaction tasks. He holds a B.Sc. and M.Sc. in Industrial Engineering from Tel Aviv University.
