Publications

Williams, Iwan, Ninell Oldenburg, Ruchira Dhar, Joshua Hatherley, Constanza Fierro, Nina Rajcic, Sandrine R. Schiller, Filippos Stamatiou, and Anders Søgaard. 2026. Mechanistic interpretability needs philosophy. Advances in Neural Information Processing Systems, forthcoming. [pdf]

Hatherley, Joshua, Anders Søgaard, Angela Ballantyne, and Ruben Pauwels. 2026. Federation opacity makes medical machine learning’s failures harder to detect and correct. The American Journal of Bioethics 26(11): W1-W3. [pdf]

Hatherley, Joshua, Anders Søgaard, Angela Ballantyne, and Ruben Pauwels. 2026. Federation opacity and the promise of federated learning in healthcare. The American Journal of Bioethics 26(8): 119-132. [pdf]

Hatherley, Joshua, Robert Sparrow, and Mark Howard. 2026. The virtues of interpretable medical AI. Cambridge Quarterly of Healthcare Ethics 35(3): 167-176. [pdf]

Hatherley, Joshua, Lauritz Aastrup Munch, and Jens Christian Bjerring. 2026. In defence of post-hoc explanations in medical AI. Hastings Center Report 56(1): 40-46. [pdf] • [doi]

Sparrow, Robert, Zachary Daus, Mark Howard, Joshua Hatherley, and Patrick Kwan. 2025. Continuous learning as a threat to care. Health and Technology 16(3): 381-385. [pdf] • [doi]

Hatherley, Joshua. 2025. A moving target in AI-assisted decision-making: Dataset shift, model updating, and the problem of update opacity. Ethics and Information Technology 27(2): 20. [pdf]

Hatherley, Joshua. 2025. Are clinicians ethically obligated to disclose their use of medical machine learning systems to patients? Journal of Medical Ethics 51(8): 567-573. [pdf] • [doi]

Sparrow, Robert, Joshua Hatherley, Justin Oakley, and Chris Bain. 2024. Should the use of adaptive machine learning systems be classified as research? The American Journal of Bioethics 24(10): 58-69. [pdf]

Hatherley, Joshua, Anne Kinderlerer, Jens Christian Bjerring, Lauritz Aastrup Munch, and Lynsey Threlfall. 2024. The FHJ debate: Will artificial intelligence replace clinical decision-making within our lifetimes? Future Healthcare Journal 11(3): 100178. [pdf]

Porsdam Mann, Sebastian, Brian D. Earp, Sven Nyholm, John Danaher, Nikolai Møller, Hilary Bowman-Smart, Joshua Hatherley, Julian Koplin, Monika Plozza, Daniel Rodger, Peter V. Treit, Gregory Renard, John McMillan, and Julian Savulescu. 2023. Generative AI entails a credit–blame asymmetry. Nature Machine Intelligence 5(5): 472-475. [doi]

Hatherley, Joshua and Robert Sparrow. 2023. Diachronic and synchronic variation in the performance of adaptive machine learning AI systems: The ethical challenges. Journal of the American Medical Informatics Association 30(2): 361-366. [pdf]

Koplin, Julian, Robert Sparrow, Joshua Hatherley, Nicola Rivers, and Iwan Williams. 2023. Tailoring university assessment in the age of ChatGPT. Monash Lens, May 15th. [html]

Koplin, Julian and Joshua Hatherley. 2022. It has become possible to use cutting-edge AI language models to generate convincing high school and undergraduate essays. Here’s why that matters. Practical Ethics Blog, December 19th. [html]

Hatherley, Joshua. 2021. Medically assisted dying for the psychiatrically ill: Reply to Buturovic. Journal of Medical Ethics 47(4): 259-260. [pdf] • [doi]

Hatherley, Joshua. 2020. Limits of trust in medical AI. Journal of Medical Ethics 46(7): 478-481. [pdf] • [doi]

Sparrow, Robert and Joshua Hatherley. 2020. High hopes for “Deep Medicine?” AI, economics, and the future of care. Hastings Center Report 50(1): 14-17. [pdf] • [doi]

Sparrow, Robert and Joshua Hatherley. 2019. The promise and perils of AI in medicine. International Journal of Chinese and Comparative Philosophy of Medicine 17(2): 79–109. [pdf]

Hatherley, Joshua. 2019. Is the exclusion of psychiatric patients from access to physician-assisted suicide discriminatory? Journal of Medical Ethics 45(12): 817–820. [pdf] • [doi]