Enhancing Clinical Trust: The Role of AI Explainability in Transforming Healthcare

Abstract

In this paper, the tensions between technological progress and societal apprehension are explored, especially in the context of Generative AI and its clinical applications. The authors emphasize the critical role of Explainable AI in addressing these challenges. xAI aims to make AI decision-making processes more transparent, thereby fostering trust and aligning AI systems with human values. However, the lack of consensus on the desirable properties and evaluation metrics of xAI poses significant obstacles. The authors argue that by simplifying and refining existing metrics, the scientific community can enhance the transparency and accountability of AI in healthcare, ultimately ensuring that these technologies fulfill their promise of improving patient outcomes while adhering to ethical standards. The findings advocate for a collaborative approach to the responsible development of clinical AI, balancing innovation with the necessary safeguards.

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