AI for Decision Support: Balancing Accuracy, Transparency, and Trust Across Sectors

This study seeks to understand the key success factors that underpin efficiency, transparency, and user trust in automated decision support systems (DSS) that leverage AI technologies across industries. The aim of this study is to facilitate more accurate decision-making with such AI-based DSS, as well as build trust through the need for visibility and explainability by increasing user acceptance. This study primarily examines the nature of AI-based DSS adoption and the challenges of maintaining system transparency and improving accuracy. The results provide practical guidance for professionals and decision-makers to develop AI-driven decision support systems that are not only effective but also trusted by users. The results are also important to gain insight into how artificial intelligence fits into and combines with decision-making, which can be derived from research when thinking about embedding systems in ethical standards.

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Publication Details

Journal
Information
Published
2024-11-11
DOI
https://doi.org/10.3390/info15110725
Citations
43
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
14.94
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article

AI for Decision Support: Balancing Accuracy, Transparency, and Trust Across Sectors

Attila Kővári
43 citations
Information
Explainable Artificial Intelligence (XAI)
14.94
article

AI for Decision Support: Balancing Accuracy, Transparency, and Trust Across Sectors

Attila Kővári
article en
43 citations

Abstract

This study seeks to understand the key success factors that underpin efficiency, transparency, and user trust in automated decision support systems (DSS) that leverage AI technologies across industries. The aim of this study is to facilitate more accurate decision-making with such AI-based DSS, as well as build trust through the need for visibility and explainability by increasing user acceptance. This study primarily examines the nature of AI-based DSS adoption and the challenges of maintaining system transparency and improving accuracy. The results provide practical guidance for professionals and decision-makers to develop AI-driven decision support systems that are not only effective but also trusted by users. The results are also important to gain insight into how artificial intelligence fits into and combines with decision-making, which can be derived from research when thinking about embedding systems in ethical standards.

InformationVol. 15(11)
Obuda University (HU), Eszterhazy Karoly Catholic University (HU), John von Neumann University (HU), University of Dunaújváros (HU)
Peace, Justice and strong institutions
Openalex Percentile: Top 1%
Explainable Artificial Intelligence (XAI)
14.94
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