Explainable Artificial Intelligence for Human–AI Collaboration: Evaluating Trust, Transparency, and Decision-Making Effectiveness in AI-Based Systems
Keywords:
AI, Human-AI Collaboration, Trust, Transparency, Decision Making, AI-based SystemsAbstract
Explainable Artificial Intelligence (XAI) has emerged as a pivotal discipline in bridging the growinggap between complex machine learning systems and human understanding. As AI-based decision-support systems are increasingly deployed in high-stakes domains
References
Adadi, A., & Berrada, M. (2018). Peeking inside the black-box: A survey on Explainable Artificial Intelligence
(XAI). IEEE Access, 6, 52138–60.
Bansal, G., Vaughan, J. W., Wallach, H., Weld, D., & Amershi, S. (2021). Does the whole exceed its parts? The effect of AI explanations on complementary team performance. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1–16). ACM
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Published
2024-07-20
How to Cite
Varsha Negi, Sunil Kumar. (2024). Explainable Artificial Intelligence for Human–AI Collaboration: Evaluating Trust, Transparency, and Decision-Making Effectiveness in AI-Based Systems. Journal of Computational Analysis and Applications (JoCAAA), 33(07), 3685–3696. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5670
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