Trust in artificial intelligence systems in healthcare: barriers and strategies for improvement

Abstract

This article addresses trust in artificial intelligence (AI) systems in healthcare, which remains a critical barrier to widespread adoption of advanced technologies. The relevance of this topic is highlighted by the rapid increase in the number of AI-based medical devices, both in Russia and worldwide, and the concurrent lack of trust from healthcare professionals and patients. The study uses a comprehensive analysis of contemporary scientific literature, international standards, regulatory practices, and a review of empirical data from global and Russian studies. The article focuses on the attitudes of patients and healthcare providers towards AI, examining the roots of skepticism related to algorithmic opacity, risks of error, and potential discrimination. Strategic directions for building trust are discussed, including transparency and explainability of AI decisions, independent testing and post-market monitoring, active involvement of medical professionals and patients in implementation, and quality management based on international standards. The authors conclude that developing ‘calibrated’ trust, grounded in empirically proven benefits and fairness of AI application in clinical practice, is essential. The article also outlines priorities for further research tailored to the Russian context.

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