AI, Big Data and Public Health
Within the dynamic landscape of "AI, Big Data, and Public Health," our research delves into the profound societal transformations engendered by these technological advancements. We critically examine the imperative for explainability in algorithmic decision-making, striving for transparency that fosters trust and accountability. Our work rigorously addresses the multifaceted dimensions of fairness, aiming to mitigate biases embedded within datasets and algorithms to ensure equitable health outcomes. Recognizing the transformative potential of big data in research, we explore its ethical and methodological implications, advocating for responsible data practices. A central tenet of our inquiry lies in the development of robust oversight mechanisms and adaptive policies and regulations, including comprehensive roadmap development and meticulous regulation mapping, to navigate the evolving terrain. We further investigate the crucial aspects of governance frameworks necessary to steer the responsible innovation and deployment of these technologies. Ultimately, our research seeks to chart a course for digital health that is both transformative and ethically sound, ensuring that the integration of AI and big data serves the public good in a just and equitable manner.
Project Team:
Effy Vayena
Alessandro Blasimme
Kelly Ormond
Sara Kijewksi
Joanna Sleigh
Former lab researchers:
Agata Ferretti
Julia Amann
Anna Jobin
Constantin Landers
Shannon Hubbs
Felix Gille
Afua Adjekum
Marta Fadda
Manuel Schneider
Marcello Ienca
Hoche M, Mineeva O, Rätsch G, Vayena E, Blasimme A (2025) What makes clinical machine learning fair? A practical ethics framework. PLOS Digital Health 4(3): e0000728. external page https://doi.org/10.1371/journal.pdig.0000728
Vayena, E. (2024). Machina non deus: being in charge of AI. The Lancet, 403(10427), 606-607. external page https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(24)00263-0/fulltext
Aboy, M., Minssen, T., & Vayena, E. (2024). Navigating the EU AI Act: implications for regulated digital medical products. npj Digital Medicine, 7(1), 237. external page https://doi.org/10.1038/s41746-024-01232-3
Shaw, J., Ali, J., Atuire, C. A., Cheah, P. Y., Español, A. G., Gichoya, J. W., ... & Vayena, E. (2024). Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research. BMC Medical Ethics, 25(1), 46. external page https://doi.org/10.1186/s12910-024-01044-w
Kijewski, S., Ronchi, E., & Vayena, E. (2024). The rise of checkbox AI ethics: a review. AI and Ethics, 1-10. external page https://doi.org/10.1007/s43681-024-00563-x
Kijewski, S., Ronchi, E., & Vayena, E. (2024). International organisations and the global governance of AI in health. Research Handbook on Health, AI and the Law, 254-272. external page https://doi.org/10.4337/9781802205657.ch15
Sleigh, J., Hubbs, S., Blasimme, A., & Vayena, E. (2024). Can digital tools foster ethical deliberation?. Humanities and Social Sciences Communications, 11(1), 1-10. external page https://doi.org/10.1057/s41599-024-02629-x
Andreoletti, M., Haller, L., Vayena, E., & Blasimme, A. (2024). Mapping the ethical landscape of digital biomarkers: A scoping review. PLOS Digital Health, 3(5), e0000519. external page https://doi.org/10.1371/journal.pdig.0000519
Landers, C., Blasimme, A. & Vayena, E. Sync fast and solve things—best practices for responsible digital health. npj Digit. Med. 7, 113 (2024). external page https://doi.org/10.1038/s41746-024-01105-9
Hoche, M., Mineeva, O., Burger, M., Blasimme, A., & Rätsch, G. (2024). FAMEWS: a Fairness Auditing tool for Medical Early-Warning Systems. medRxiv, 2024-02. external page https://doi.org/10.1101/2024.02.08.24302458
Canali, S., Ferretti, A., Schiaffonati, V., & Blasimme, A. (2024). Wearable technologies for healthy ageing: Prospects, challenges, and ethical considerations. The Journal of Frailty & Aging, 13(2), 149-156. external page https://doi.org/10.14283/jfa.2024.19
Goldberg, C. B., Adams, L., Blumenthal, D., Brennan, P. F., Brown, N., Butte, A. J., Vayena, E.,... & Kohane, I. S. (2024). To do no harm—and the most good—with AI in health care. Nejm Ai, 1(3), external page AIp2400036.
Amann, J., Vayena, E., Ormond, K. E., Frey, D., Madai, V. I., & Blasimme, A. (2023). Expectations and attitudes towards medical artificial intelligence: a qualitative study in the field of stroke. PLoS One, 18(1), e0279088. external page https://doi.org/10.1371/journal.pone.0279088
Blasimme, A., Nittas, V., Ormond, K., & Vayena, E. (2023). Realizing the promise of machine learning in precision oncology: expert perspectives on opportunities and challenges. Research Square. https://www.research-collection.ethz.ch/handle/20.500.11850/646003
Minssen, T., Vayena, E., & Cohen, I. G. (2023). The challenges for regulating medical use of ChatGPT and other large language models. Jama, 330(4), 315-316. doi:external page 10.1001/jama.2023.9651
Ferretti, A., Vayena, E., & Blasimme, A. (2023). Unlock digital health promotion in LMICs to benefit the youth. PLOS Digital Health, 2(8), e0000315. external page https://doi.org/10.1371/journal.pdig.0000315
Landers, C., Vayena, E., Amann, J., & Blasimme, A. (2023). Stuck in translation: Stakeholder perspectives on impediments to responsible digital health. Frontiers in Digital Health, 5, 1069410. external page https://doi.org/10.3389/fdgth.2023.1069410
Landers, C., Blasimme, A., Ormond, K., Vayena, E. (2023) Talking ethics early in health data public private partnerships. Journal of Business Ethics. external page https://doi.org/10.1007/s10551-023-05425-w.
Ormond, K. E., Blasimme, A., & Vayena, E. (2023). Ethical aspects of pediatric genetic care: testing and treatment. Pediatric Clinics, 70(5), 1029-1046.external page https://doi.org/10.1016/S2589-7500(23)00052-3
Vayena, E., Blasimme, A., Sugarman, J. (2023). Decentralised clinical trials: ethical opportunities and challenges. The Lancet Digital Health. DOI: external page https://doi.org/10.1016/S2589-7500(23)00052-3
Nittas, V., Daniore, P., Landers, C., Gille, F., Amann, J., Hubbs, S., ... & Blasimme, A. (2023). Beyond high hopes: A scoping review of the 2019–2021 scientific discourse on machine learning in medical imaging. PLOS Digital Health, 2(1), e0000189. external page https://doi.org/10.1371/journal.pdig.0000189
Blasimme, A., & Sugarman, J. (2023). Human stem cell-derived embryo models: Toward ethically appropriate regulations and policies. Cell Stem Cell, 30(8), 1008-1012. external page https://doi.org/10.1016/j.stem.2023.06.007
Vayena, E., & Blasimme, A. (2022). A systemic approach to the oversight of machine learning clinical translation. The American Journal of Bioethics, 22(5), 23-25. external page https://doi.org/10.1080/15265161.2022.2055216
Hutler, B., Blasimme, A., Gur-Arie, R., Ali, J., Barnhill, A., Hood, A., ... & Vayena, E. (2022). Assessing the Governance of Digital Contact Tracing in Response to COVID-19: Results of a Multi-National Study. Journal of Law, Medicine & Ethics, 50(4), 791-804. external page https://doi.org/10.1017/jme.2023.20
Vayena, E., & Feretti, A. (2021). Big Data and Artificial Intelligence for Global Health: Ethical Challenges and Opportunities. In S. Benatar & G. Brock (Eds.), Global Health: Ethical Challenges (pp. 429-439). Cambridge: Cambridge University Press. external page doi:10.1017/9781108692137.036
Vayena, E. (2021). Value from health data: European opportunity to catalyse progress in digital health. The Lancet, 397(10275), 652-653. external page https://doi.org/10.1016/S0140-6736(21)00203-8
Vayena, E., & Blasimme, A. (2021). Towards Adaptive Governance in Big Data Health Research: Implementing Regulatory Principles. The Cambridge Handbook of Health Research Regulation, 257-265. external page https://doi.org/10.1017/9781108620024.032
Vayena, E., Ferretti, A., Benatar, S., & Brock, G. (2021). Big data and artificial intelligence for global health. Global Health: Ethical Challenges, 429.
Blasimme, A., Ferretti, A., & Vayena, E. (2021). Digital contact tracing against COVID-19 in Europe: current features and ongoing developments. Frontiers in Digital Health, 3, 660823. external page https://doi.org/10.3389/fdgth.2021.660823
Ferretti, A., Ienca, M., Sheehan, M., Blasimme, A., Dove, E. S., Farsides, B., ... & Vayena, E. (2021). Ethics review of big data research: What should stay and what should be reformed?. BMC medical ethics, 22(1), 51. external page https://doi.org/10.1186/s12910-021-00616-4
Amann, J., Blasimme, A., Vayena, E., Frey, D., Madai, V. I., & Precise4Q Consortium. (2020). Explainability for artificial intelligence in healthcare: a multidisciplinary perspective. BMC medical informatics and decision making, 20, 1-9. external page https://doi.org/10.1186/s12911-020-01332-6
Goodman, K., Zandi, D., Reis, A., & Vayena, E. (2020). Balancing risks and benefits of artificial intelligence in the health sector. Bulletin of the World Health Organization, 98(4), 230. doi: external page http://dx.doi.org/10.2471/BLT.20.253823
Blasimme, A., & Vayena, E. (2020). What's next for COVID-19 apps? Governance and oversight. Science, 370(6518), 760-762. external page https://www.science.org/doi/10.1126/science.abd9006
Gille, F., Vayena, E., & Blasimme, A. (2020). Future-proofing biobanks’ governance. European Journal of Human Genetics, 28(8), 989-996. external page https://doi.org/10.1038/s41431-020-0646-4
Blasimme A. and Vayena E. (2020). The Ethics of AI in Biomedical research, patient care and public health. In Dubber M., Pasquale F. and Das S. (eds.), Oxford Handbook of Ethics of Artificial Intelligence, Oxford University Press, Oxford, UK. ISBN 9780190067397. external page http://dx.doi.org/10.2139/ssrn.3368756
Gille, F., Axler, R., & Blasimme, A. (2021). Transparency about governance contributes to biobanks' Trustworthiness: call for action. Biopreservation and biobanking, 19(1), 83-85. external page DOI: 10.1089/bio.2020.0057
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature machine intelligence, 1(9), 389-399. external page https://doi.org/10.1038/s42256-019-0088-2
Blasimme, A., & Vayena, E. (2019). The ethics of AI in biomedical research, patient care and public health. Patient Care and Public Health (April 9, 2019). Oxford Handbook of Ethics of Artificial Intelligence. external page https://ssrn.com/abstract=3368756
Zandi, D., Reis, A., Vayena, E., & Goodman, K. (2019). New ethical challenges of digital technologies, machine learning and artificial intelligence in public health: a call for papers. Bulletin of the World Health Organization, 97(1), 2. doi: external page http://dx.doi.org/10.2471/BLT.18.227686
Blasimme A., Vayena E., van Hoyweghen I. (2019). Big data, precision medicine and private insurance: a delicate balancing act. Big Data & Society 2019/3:6(1). external page https://doi.org/10.1177/205395171983011
Vayena, E., & Blasimme, A. (2018). Health research with big data: time for systemic oversight. The journal of law, medicine & ethics, 46(1), 119-129. external page https://doi.org/10.1177/1073110518766026
Vayena, E., Blasimme, A., & Cohen, I. G. (2018). Machine learning in medicine: addressing ethical challenges. PLoS medicine, 15(11), e1002689. external page https://doi.org/10.1371/journal.pmed.1002689
Haeusermann, T., Fadda, M., Blasimme, A., Tzovaras, B. G., & Vayena, E. (2018). Genes wide open: Data sharing and the social gradient of genomic privacy. AJOB Empirical Bioethics, 9(4), 207-221. external page https://doi.org/10.1080/23294515.2018.1550123
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., ... & Vayena, E. (2018). AI4People—an ethical framework for a good AI society: opportunities, risks, principles, and recommendations. Minds and machines, 28, 689-707. external page https://doi.org/10.1007/s11023-018-9482-5
Vayena, E., Haeusermann, T., Adjekum, A., & Blasimme, A. (2018). Digital health: meeting the ethical and policy challenges. Swiss medical weekly, 148, w14571. external page https://doi.org/10.4414/smw.2018.14571
Adjekum, A., Blasimme, A., & Vayena, E. (2018). Elements of trust in digital health systems: scoping review. Journal of medical Internet research, 20(12), e11254. external page https://doi.org/10.2196/11254
Vayena, E., & Tasioulas, J. (2016). The dynamics of big data and human rights: The case of scientific research. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2083), 20160129. external page https://doi.org/10.1098/rsta.2016.0129
Responsible Digital Health Innovation Roadmap.
Swiss National Science Foundation (SNSF).
Link: https://digitalhealthroadmap.ethz.ch/
Ethics and governance of artificial intelligence for health: Guidance on large multi-modal models.
World Health Organization (WHO).
Link: external page https://www.who.int/publications/i/item/9789240084759
Ethics and Governance of Artificial Intelligence for Health: WHO Guidance.
World Health Organization (WHO).
Link: external page https://www.who.int/publications/i/item/9789240029200