ArticleBMC medical ethics2024
Integrating ethics in AI development: a qualitative study.
Article in BMC medical ethics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Ethical concerns and strategies for implementing artificial intelligence in healthcare: a review of empirical studies.BMC medical ethics · 2026Pooled it
- "First, do no harm" in the digital era: examining the practicality of the European Health Data Space proposal and ethical implications of artificial intelligence: A systematic literature review.BMC medical ethics · 2026Pooled it
- The Impact and Role of Artificial Intelligence (AI) in Healthcare: Systematic Review.Current topics in medicinal chemistry · 2025Pooled it
- Proactive vs. passive algorithmic ethics practices in healthcare: the moderating role of healthcare engagement type in patients' responses.BMC medical ethics · 2025Trial
- Principles for medical students' responsible use of generative AI: a student-partnered Delphi study.BMC medical ethics · 2026Article
- Use of Conventional Artificial Intelligence Methods in the Identification of Frailty: A Scoping Review.Journal of the American Geriatrics Society · 2026Article
- Navigating artificial intelligence in qualitative research: ethical and practical considerations from concept to publication.Frontiers in research metrics and analytics · 2026Article
- Ethical considerations and robustness of artificial neural networks in medical image analysis under data corruption.Scientific reports · 2025Article
- AI-assisted decision-making in mild traumatic brain injury.BMC emergency medicine · 2025Article
- Knowledge, attitude, and perceptions of MENA researchers towards the use of ChatGPT in research: A cross-sectional study.Heliyon · 2025Article
- Ethical and Legal Governance of Generative AI in Chinese Healthcare.Journal of multidisciplinary healthcare · 2025Article
- Regulating professional ethics in a context of technological change.BMC medical ethics · 2024Article
- Developing a Canadian artificial intelligence medical curriculum using a Delphi study.NPJ digital medicine · 2024Article
- Redesigning Nursing Curricula for Human-AI Collaboration Using a Fifth Industrial Revolution Framework: Discursive Paper.SAGE open nursingReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundWhile the theoretical benefits and harms of Artificial Intelligence (AI) have been widely discussed in academic literature, empirical evidence remains elusive regarding the practical ethical challenges of developing AI for healthcare. Bridging the gap between theory and practice is an essential step in understanding how to ethically align AI for healthcare. Therefore, this research examines the concerns and challenges perceived by experts in developing ethical AI that addresses the healthcare context and needs.
methodsWe conducted semi-structured interviews with 41 AI experts and analyzed the data using reflective thematic analysis.
resultsWe developed three themes that expressed the considerations perceived by experts as essential for ensuring AI aligns with ethical practices within healthcare. The first theme explores the ethical significance of introducing AI with a clear and purposeful objective. The second theme focuses on how experts are concerned about the tension that exists between economic incentives and the importance of prioritizing the interests of doctors and patients. The third theme illustrates the need to develop context-sensitive AI for healthcare that is informed by its underlying theoretical foundations.
conclusionsThe three themes collectively emphasized that beyond being innovative, AI must genuinely benefit healthcare and its stakeholders, meaning AI also aligns with intricate and context-specific healthcare practices. Our findings signal that instead of narrow product-specific AI guidance, ethical AI development may need a systemic, proactive perspective that includes the ethical considerations (objectives, actors, and context) and focuses on healthcare applications. Ethically developing AI involves a complex interplay between AI, ethics, healthcare, and multiple stakeholders.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.