Hospital staff reveal ethical dilemmas of AI in medicine and propose governance paths

Artificial intelligence is increasingly used in clinical practice, and with that expansion come persistent ethical concerns about algorithmic opacity, accountability, informed consent and professional autonomy. A new qualitative study published in BMC Medical Ethics examines how healthcare professionals themselves perceive these dilemmas in AI-assisted practice, and what practical approaches to governance might follow from their experiences.

The research team, led by Lu-Xi Zou and colleagues, used semi-structured interviews with hospital staff to explore perceptions of ethical issues surrounding medical artificial intelligence. Interview transcripts were analysed with a deductive–inductive thematic analysis supported by charting in a framework matrix. As an exploratory, unsupervised complement, the researchers also applied latent Dirichlet allocation (LDA) topic modelling to the same material.

The thematic analysis identified six themes, while the LDA modelling identified five topics. Comparing the two outputs revealed both semantic overlap and differences in thematic boundaries and granularity. Notably, clinical practice risks emerged as a separate topic in the machine-generated modelling but not as a separate qualitative theme, whereas informed consent dilemmas and ethical governance expectations were identified as distinct qualitative themes but did not appear as separate LDA topics.

Across the interviews, participating professionals described perceived gaps in current institutional arrangements for accountability, informed consent and oversight of medical AI. The study’s background notes that existing ethical and governance frameworks provide important normative direction, but that questions remain about how their principles can be translated into operational guidance for specific medical AI technologies and frontline clinical contexts.

Building on the interview findings and existing ethical frameworks, the authors propose two complementary approaches. The first is to integrate ethical requirements across the entire medical AI lifecycle, so that ethical considerations are embedded from development through deployment rather than addressed only after problems arise. The second is to establish a multi-actor, risk-based review process involving the relevant stakeholders in oversight of these technologies.

The authors suggest these findings may inform policymakers, healthcare institutions and technology developers seeking to translate ethical principles into clinical governance. However, they are explicit that the proposed framework has not yet been implemented or evaluated, and that it requires empirical testing in future research.

The study’s methodological design matters for interpreting its results. As a qualitative interview study analysed thematically, it captures the perceptions and reported experiences of the participating hospital staff rather than measured outcomes of AI deployment. The LDA topic modelling was used as an exploratory complement, and the comparison between its five topics and the six qualitative themes is itself presented as a finding about how different analytical lenses carve up the same ethical terrain.

Published on 27 October 2026 as an open-access article, the paper appears in a version shared early for faster access to peer-reviewed, accepted research; this version remains subject to further edits before the final Version of Record replaces it. For readers tracking the governance of medical AI, the study’s central contribution is a structured account of the ethical dilemmas that frontline professionals perceive, paired with a proposed but untested governance pathway grounded in those perceptions and in existing ethical frameworks.

Subject of Research: Ethical dilemmas and governance pathways of artificial intelligence in medicine

Article Title: Research on ethical dilemmas and governance pathways of artificial intelligence in the medical field

Article References: Zou, L.-X., Qiang, Y.-Q., Khalid, H., & Sun, L. (2026). Research on ethical dilemmas and governance pathways of artificial intelligence in the medical field. BMC Medical Ethics. https://doi.org/10.1186/s12910-026-01657-3

Image Credits: AI Generated

DOI: 10.1186/s12910-026-01657-3

Keywords: medical AI, ethics, governance, informed consent, accountability, qualitative interviews, thematic analysis, topic modelling, clinical practice, healthcare professionals, Research, ethical