Explainable AI does not provide the explanations end-users are asking for

• URL: http://arxiv.org/abs/2302.11577v2
• Date: Tue, 21 Mar 2023 14:16:06 GMT
• Title: Explainable AI does not provide the explanations end-users are asking for
• Authors: Savio Rozario and George \v{C}evora
• Abstract summary: We discuss XAI's limitations in deployment and conclude that transparency alongside with rigorous validation are better suited to gaining trust in AI systems. XAI techniques are frequently required by users in many AI systems with the goal of understanding complex models, their associated predictions, and gaining trust.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Explainable Artificial Intelligence (XAI) techniques are frequently required by users in many AI systems with the goal of understanding complex models, their associated predictions, and gaining trust. While suitable for some specific tasks during development, their adoption by organisations to enhance trust in machine learning systems has unintended consequences. In this paper we discuss XAI's limitations in deployment and conclude that transparency alongside with rigorous validation are better suited to gaining trust in AI systems.

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