Physicians Retain Moral Responsibility but Endorse Institutional Co-Responsibility in AI-Assisted Decisions: An Exploratory Vignette Study

Background: Artificial intelligence (AI) systems, including large language models, are increasingly used in clinical practice, whether consulted informally by clinicians or introduced by employers into decision workflows. It remains unclear how physicians attribute moral responsibility when a decision follows an AI recommendation and whether that attribution varies with the type of decision at stake. Methods: We conducted a cross-sectional, within-subject vignette survey of physicians in Romania. Each respondent rated the same three scenarios—urgent clinical, elective clinical, and administrative—in which a physician followed an AI recommendation under two extenuating institutional constraints. Five-point Likert items addressed the mitigation of blame by circumstances, physician responsibility despite the AI recommendation, and institutional co-responsibility. Analyses were non-parametric, with corrections for multiple testing. Results: Among 72 physicians from 17 specialties, respondents endorsed full personal responsibility in every scenario, including the administrative one, with no significant difference between scenarios. They rejected extenuating circumstances as mitigating in both clinical scenarios but were divided about them in the administrative scenario, which had the largest effect. Institutional co-responsibility was endorsed alongside personal responsibility rather than in place of it, and the two attributions were largely uncorrelated. No demographic association survived correction, although the study was not powered to detect small-effect sizes. Conclusions: Physicians treated AI as an instrument rather than a bearer of responsibility, which is unsurprising. The substantive findings lie elsewhere: personal responsibility was retained across all decision contexts, while what varied was the admissibility of institutional constraints as excuses and the emphasis placed on the institution’s share. Because respondents did not treat responsibility as a fixed quantity to be divided, the pattern is consistent with distributed-responsibility accounts rather than with a responsibility gap, though attitudinal data cannot adjudicate between normative accounts. The findings are exploratory and require confirmation in larger, more representative samples.