Lorina Buhr

Institute for Ethics and History of Medicine, University Medical Centre Göttingen

Background: Antimicrobial resistance (AMR) is a key problem in healthcare. According to the latest report from the World Health Organisation, one in six laboratory-confirmed bacterial infections in 2023 was resistant to antibiotics. The spread of AMR therefore has a significant impact on patients both now and in the future. The strategic approach to tackling resistance focuses on three areas of action: (i) containment through more targeted and reduced use of antibiotics in human medicine, (ii) strictly regulated use of antibiotics in veterinary medicine and agriculture, (iii) exploration of new classes of antibiotics. Recent developments in medical AI are fuelling hopes that AI can be used to support efforts in all these areas of action.

The ethical debate to date. The ethical debate on AMR centres not only on discussions regarding intra- and intergenerational distributive justice in access to antibiotics, but also, amongst other things, on the proposal to regard antibiotics as a resource for treatment that is limited in quantity and time. At the level of medical decision-making, stakeholders and doctors are called upon to weigh up the choice of antibiotic therapy against its side effects and long-term consequences for the body and the environment, taking into account aspects of medical and environmental sustainability. However, there has so far been little ethical reflection on the development and use of AI to combat AMR (AMR-AI).

Ethical analysis: This paper addresses this research gap by examining the scenarios for the use of AI in terms of ethical implications and dilemmas. Particular focus is placed on those AI models designed to discover and design antimicrobial peptides. It is argued that, in these cases, ethical reflection must go beyond the discussion of distributive justice. It is proposed that ethical reflection be supplemented by a critical analysis of (i) the underlying temporal and economic logics and incentives driving the development of AMR-AI, (ii) the sustainability implications of AI, (iii) the ethical conflicts relating to the medicalisation of society and animal health. The paper thus presents an innovative framework for technological reflection in the light of sustainability and One Health.