Human Response to Decision Support in Face Matching: The Influence of Task Difficulty and Machine Accuracy
Marina Est\'evez-Almenzar, Ricardo Baeza-Yates, Carlos Castillo

TL;DR
This study investigates how task difficulty and AI system accuracy influence human decision-making in face matching, revealing that increased difficulty reduces both accuracy and awareness of system reliability, impacting decision support design.
Contribution
It provides empirical evidence on the effects of task difficulty and system accuracy on human-AI decision-making in face matching tasks, highlighting the importance of context and perception.
Findings
Task difficulty decreases human accuracy in face matching.
Humans struggle to assess AI support reliability under high difficulty.
System accuracy influences human decision confidence.
Abstract
Decision support systems enhanced by Artificial Intelligence (AI) are increasingly being used in high-stakes scenarios where errors or biased outcomes can have significant consequences. In this work, we explore the conditions under which AI-based decision support systems affect the decision accuracy of humans involved in face matching tasks. Previous work suggests that this largely depends on various factors, such as the specific nature of the task and how users perceive the quality of the decision support, among others. Hence, we conduct extensive experiments to examine how both task difficulty and the precision of the system influence human outcomes. Our results show a strong influence of task difficulty, which not only makes humans less precise but also less capable of determining whether the decision support system is yielding accurate suggestions or not. This has implications for…
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Taxonomy
TopicsFace Recognition and Perception · Face recognition and analysis · Evolutionary Psychology and Human Behavior
