TRUST, PRIVACY, AND LIABILITY: EXPLORING PATIENT ATTITUDES TOWARD ARTIFICIAL INTELLIGENCE IN HEALTHCARE

Abstract

Background: The aim of this study was to evaluate the level of trust and social acceptance regarding the use of artificial intelligence (AI) in medical self-diagnosis, and to identify patients' primary concerns related to the implementation of AI algorithms in the healthcare system. Materials and Methods: The research was carried out in July 2026 via a cross-sectional survey design utilizing an anonymous online questionnaire (the CAWI technique). The study cohort comprised 274 participants. The analysis evaluated digital health information-seeking behaviors, the acceptance of artificial intelligence in clinical and diagnostic workflows, and patients' perceptions of responsibility for medical errors caused by AI systems. Results: Nearly all participants (96%) reported verifying their medical symptoms online. Patients demonstrated moderate acceptance of AI as a supportive tool in analyzing medical imaging; however, they strongly rejected (80% of respondents) the concept of fully automated treatment processes without physician supervision. Significant concerns regarding the privacy of medical data were identified, particularly within the 36–50 age demographic. The analysis of liability for AI-generated errors revealed that patients tend to attribute responsibility to themselves, highlighting a discrepancy between their moral intuition and current legal and ethical frameworks. Conclusions: Public acceptance of AI in healthcare is strictly dependent on preserving the "human-in-the-loop" paradigm. There is a critical need to enhance health education regarding cybersecurity and to establish clear regulatory frameworks for AI-related errors, all while maintaining the physician's overriding authority in the therapeutic process.