The Effect of Explainable AI-based Decision Support on Human Task Performance: A Meta-Analysis

Fuente: arXiv
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Main Author: Haag, Felix
Format: Preprint
Published: 2025
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author Haag, Felix
author_facet Haag, Felix
contents The desirable properties of explanations in information systems have fueled the demands for transparency in artificial intelligence (AI) outputs. To address these demands, the field of explainable AI (XAI) has put forth methods that can support human decision-making by explaining AI outputs. However, current empirical works present inconsistent findings on whether such explanations help to improve users' task performance in decision support systems (DSS). In this paper, we conduct a meta-analysis to explore how XAI affects human performance in classification tasks. Our results show an improvement in task performance through XAI-based decision support, though explanations themselves are not the decisive driver for this improvement. The analysis reveals that the studies' risk of bias moderates the effect of explanations in AI, while the explanation type appears to play only a negligible role. Our findings contribute to the human computer interaction field by enhancing the understanding of human-XAI collaboration in DSS.
format Preprint
id arxiv_https___arxiv_org_abs_2504_13858
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Effect of Explainable AI-based Decision Support on Human Task Performance: A Meta-Analysis
Haag, Felix
Human-Computer Interaction
Artificial Intelligence
The desirable properties of explanations in information systems have fueled the demands for transparency in artificial intelligence (AI) outputs. To address these demands, the field of explainable AI (XAI) has put forth methods that can support human decision-making by explaining AI outputs. However, current empirical works present inconsistent findings on whether such explanations help to improve users' task performance in decision support systems (DSS). In this paper, we conduct a meta-analysis to explore how XAI affects human performance in classification tasks. Our results show an improvement in task performance through XAI-based decision support, though explanations themselves are not the decisive driver for this improvement. The analysis reveals that the studies' risk of bias moderates the effect of explanations in AI, while the explanation type appears to play only a negligible role. Our findings contribute to the human computer interaction field by enhancing the understanding of human-XAI collaboration in DSS.
title The Effect of Explainable AI-based Decision Support on Human Task Performance: A Meta-Analysis
topic Human-Computer Interaction
Artificial Intelligence
url https://arxiv.org/abs/2504.13858