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Ethics of Artificial Intelligence in Health and Medicine

Guest Editors:
Nan Liu: National University of Singapore, Singapore
Kadri Simm: University of Tartu, Estonia
Honghan Wu: University College London, UK


The Editors of BMC Medical Ethics & BMC Medical Informatics and Decision Making called for submissions to our collection on ethics of artificial intelligence in the context of health and medicine. This collection welcomed studies focused on technical assessment and evaluation of AI-based medical decision making methods with regards to these ethics-relevant features, as well as more theoretical considerations on the medical use of AI-based methods. This includes but is not limited to the presentation of novel AI-based methods able to fulfill such ethical requirements and tools able to mitigate issues like bias, the elaboration of novel ethics-relevant metrics, research on attitudes and perceptions of physicians and the public on AI implementation, ethics surrounding AI-associated privacy and surveillance, and ethical challenges surrounding implementation of medical AI.

Meet the Guest Editors

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Nan Liu: National University of Singapore, Singapore

Dr Nan Liu is an Associate Professor at Duke-NUS Medicine School, National University of Singapore. His research focuses on artificial intelligence and machine learning with applications to medical informatics, health services research, emergency and critical care, cardiology, and health innovation. Specifically, Dr Liu is interested in the translation of technical solutions into clinical practice using interpretable and trustworthy artificial intelligence.

Kadri Simm: University of Tartu, Estonia

Kadri Simm is a philosopher and bioethicist from University of Tartu, Estonia. She is Chair of Practical Philosophy at Institute of Philosophy and Semiotics and a visiting research fellow at Department of Bioethics, National Institutes of Health, USA. She has published on benefit-sharing in biomedical research, biobanking, ethics of reproductive medicine and the nature of ethical decision-making. In her research she often combines theoretical and empirical methods and her most recent research focuses on the ethical and epistemic challenges of Open Science, the practice of clinical ethics consultation and the behavioural approaches in support of research integrity.

Honghan Wu: University College London, UK

Dr Honghan Wu is an Associate Professor at the Institute of Health Informatics, University College London, United Kingdom. He holds a PhD in Computing Science and is Fellow of The Alan Turing Institute, UK's national institute for data science and artificial intelligence. His current research interest is in using text technologies and Knowledge Graph techniques to analyse health data. In particular, he is interested in quantifying and mitigating AI induced health inequality in recent years.






About the collection

BMC Medical Ethics & BMC Medical Informatics and Decision Making are calling for submissions to our Collection on Ethics of Artificial Intelligence in Health and Medicine.  

Today, there is a need to bring up within the scientific and clinical community a discussion about the impact of AI on medical decision making. In particular, machine learning methods have seen an impressive expansion in the last few years, and this has not come without issues and ethical questions, notably regarding the data embedded bias and the role that AI-based methods may have in unwillingly inducing inequalities in health care.

Metrics such as fairness, accountability, lack or mitigation of bias, and explainability are major aspects that impact the perception and use of machine learning methods in ethically-sensitive fields such as medicine, and machine learning methods endowed with these features might play a significant role in overcoming mistrust, although they could not guarantee trust.

This collection welcomes studies focused on technical assessment and evaluation of AI-based medical decision making methods with regards to these ethics-relevant features, as well as more theoretical considerations on the medical use of AI-based methods. This includes but is not limited to the presentation of novel AI-based methods able to fulfill such ethical requirements and tools able to mitigate issues like bias, the elaboration of novel ethics-relevant metrics, research on attitudes and perceptions of physicians and the public on AI implementation, ethics surrounding AI-associated privacy and surveillance, and ethical challenges surrounding implementation of medical AI.



Image credit: Choys_ / Unsplash

  1. To examine the understanding of the ethical dilemmas associated with Big Data and artificial intelligence (AI) among Jordanian medical students, physicians in training, and senior practitioners.

    Authors: Abdallah Al-Ani, Abdallah Rayyan, Ahmad Maswadeh, Hala Sultan, Ahmad Alhammouri, Hadeel Asfour, Tariq Alrawajih, Sarah Al Sharie, Fahed Al Karmi, Ahmad Azzam, Asem Mansour and Maysa Al-Hussaini
    Citation: BMC Medical Ethics 2024 25:18
  2. While 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 deve...

    Authors: Laura Arbelaez Ossa, Giorgia Lorenzini, Stephen R. Milford, David Shaw, Bernice S. Elger and Michael Rost
    Citation: BMC Medical Ethics 2024 25:10
  3. Given that AI-driven decision support systems (AI-DSS) are intended to assist in medical decision making, it is essential that clinicians are willing to incorporate AI-DSS into their practice. This study takes...

    Authors: Rachel Dlugatch, Antoniya Georgieva and Angeliki Kerasidou
    Citation: BMC Medical Ethics 2024 25:6
  4. Allocation of scarce organs for transplantation is ethically challenging. Artificial intelligence (AI) has been proposed to assist in liver allocation, however the ethics of this remains unexplored and the vie...

    Authors: Max Drezga-Kleiminger, Joanna Demaree-Cotton, Julian Koplin, Julian Savulescu and Dominic Wilkinson
    Citation: BMC Medical Ethics 2023 24:102
  5. It is widely acknowledged that trust plays an important role for the acceptability of data sharing practices in research and healthcare, and for the adoption of new health technologies such as AI. Yet there is...

    Authors: Angeliki Kerasidou and Charalampia (Xaroula) Kerasidou
    Citation: BMC Medical Ethics 2023 24:51

    The Correction to this article has been published in BMC Medical Ethics 2023 24:77

  6. Healthcare providers have to make ethically complex clinical decisions which may be a source of stress. Researchers have recently introduced Artificial Intelligence (AI)-based applications to assist in clinica...

    Authors: Lasse Benzinger, Frank Ursin, Wolf-Tilo Balke, Tim Kacprowski and Sabine Salloch
    Citation: BMC Medical Ethics 2023 24:48
  7. Despite the recognition that developing artificial intelligence (AI) that is trustworthy is necessary for public acceptability and the successful implementation of AI in healthcare contexts, perspectives from ...

    Authors: Rachel Dlugatch, Antoniya Georgieva and Angeliki Kerasidou
    Citation: BMC Medical Ethics 2023 24:42
  8. Artificial intelligence (AI) is often cited as a possible solution to current issues faced by healthcare systems. This includes the freeing up of time for doctors and facilitating person-centred doctor-patient...

    Authors: Aurelia Sauerbrei, Angeliki Kerasidou, Federica Lucivero and Nina Hallowell
    Citation: BMC Medical Informatics and Decision Making 2023 23:73
  9. As the use of AI becomes more pervasive, and computerised systems are used in clinical decision-making, the role of trust in, and the trustworthiness of, AI tools will need to be addressed. Using the case of c...

    Authors: Nina Hallowell, Shirlene Badger, Aurelia Sauerbrei, Christoffer Nellåker and Angeliki Kerasidou
    Citation: BMC Medical Ethics 2022 23:112

Submission Guidelines

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This Collection welcomes submission of Research Articles. Before submitting your manuscript, please ensure you have read the submission guidelines of the journal you are submitting to (BMC Medical Ethics and BMC Medical Informatics and Decision Making). Articles for this Collection should be submitted via our submission system, Snapp (BMC Medical Ethics and BMC Medical Informatics and Decision Making). 

During the submission process you will be asked whether you are submitting to a Collection, please select "Ethics of Artificial Intelligence in Health and Medicine" from the dropdown menu.

Articles will undergo the standard peer-review process of the journal they are considered in (BMC Medical Ethics and BMC Medical Informatics and Decision Making) and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Guest Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Guest Editors have competing interests is handled by another Editorial Board Member who has no competing interests.