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The Impact of Imperfect XAI on Human-AI Decision-Making

Title data

Morrison, Katelyn ; Spitzer, Philipp ; Turri, Violet ; Feng, Michelle ; Kühl, Niklas ; Perer, Adam:
The Impact of Imperfect XAI on Human-AI Decision-Making.
In: Proceedings of the ACM on Human-Computer Interaction. (2024) .
ISSN 2573-0142

Abstract in another language

Explainability techniques are rapidly being developed to improve human-AI decision-making across various cooperative work settings. Consequently, previous research has evaluated how decision-makers collaborate with imperfect AI by investigating appropriate reliance and task performance with the aim of designing more human-centered computer-supported collaborative tools. Several human-centered explainable AI (XAI) techniques have been proposed in hopes of improving decision-makers' collaboration with AI; however, these techniques are grounded in findings from previous studies that primarily focus on the impact of incorrect AI advice. Few studies acknowledge the possibility for the explanations to be incorrect even if the AI advice is correct. Thus, it is crucial to understand how imperfect XAI affects human-AI decision-making. In this work, we contribute a robust, mixed-methods user study with 136 participants to evaluate how incorrect explanations influence humans' decision-making behavior in a bird species identification task taking into account their level of expertise and an explanation's level of assertiveness. Our findings reveal the influence of imperfect XAI and humans' level of expertise on their reliance on AI and human-AI team performance. We also discuss how explanations can deceive decision-makers during human-AI collaboration. Hence, we shed light on the impacts of imperfect XAI in the field of computer-supported cooperative work and provide guidelines for designers of human-AI collaboration systems.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Human-AI Collaboration; Explainable AI; XAI for Computer Vision
Subject classification: Human-centered computing → Empirical studies in HCI; Computing methodologies → Artificial intelligence; Computer vision tasks
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Information Systems Management > Chair Information Systems Management - Univ.-Prof. Dr.-Ing. Niklas Kühl
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 07 Dec 2023 06:46
Last Modified: 07 Dec 2023 06:46
URI: https://eref.uni-bayreuth.de/id/eprint/87994