Diachronic and synchronic variation in the performance of adaptive machine learning systems: the ethical challenges. - Joshua Hatherley; Robert Sparrow (J. Am. Medical Informatics Assoc., 2023)

Generative AI entails a credit-blame asymmetry. - Sebastian Porsdam Mann; Brian D. Earp; Sven Nyholm; John Danaher 001; Nikolaj Møller; Hilary Bowman-Smart; Joshua Hatherley; Julian Koplin; Monika Plozza; Daniel Rodger; Peter V. Treit; Gregory Renard; et al. (Nat. Mac. Intell., 2023)

Limits of trust in medical AI. - Joshua Hatherley (CoRR, 2025)

Are clinicians ethically obligated to disclose their use of medical machine learning systems to patients? - Joshua Hatherley (CoRR, 2025)

Data over dialogue: Why artificial intelligence is unlikely to humanise medicine. - Joshua Hatherley (CoRR, 2025)

Federated learning, ethics, and the double black box problem in medical AI. - Joshua Hatherley; Anders Søgaard; Angela Ballantyne; Ruben Pauwels (CoRR, 2025)

In defence of post-hoc explanations in medical AI. - Joshua Hatherley; Lauritz Aastrup Munch; Jens Christian Bjerring (CoRR, 2025)

The promise and perils of AI in medicine. - Robert Sparrow; Joshua Hatherley (CoRR, 2025)

Mechanistic Interpretability Needs Philosophy. - Iwan Williams; Ninell Oldenburg; Ruchira Dhar; Joshua Hatherley; Constanza Fierro; Nina Rajcic; Sandrine R. Schiller; Filippos Stamatiou; Anders Søgaard (CoRR, 2025)

A moving target in AI-assisted decision-making: dataset shift, model updating, and the problem of update opacity. - Joshua Hatherley (Ethics Inf. Technol., 2025)

High hopes for "Deep Medicine"? AI, economics, and the future of care. - Robert Sparrow; Joshua Hatherley (CoRR, 2025)