The pandemic significantly raised the stakes for the translation of bioethics insights into policy. The novelty, range and sheer quantity of the ethical problems that needed to be addressed urgently within public policy were unprecedented and required high‐bandwidth two‐way transfer of insights between academic bioethics and policy. Countries such as the United Kingdom, which do not have a National Ethics Committee, faced particular challenges in how to facilitate this. This paper takes as a case study the brief career of the (...) Ethics Advisory Board (EAB) for the NHS Covid‐19 App, which shows both the difficulty and the political complexity of policy‐relevant bioethics in a pandemic and how this was exacerbated by the transience and informality of the structures through which ethics advice was delivered. It analyses how and why, after EAB's demise, the Westminster government increasingly sought to either take its ethics advice in private or to evade ethical scrutiny of its policies altogether. In reflecting on EAB, and these later ethics advice contexts, the article provides a novel framework for analysing ethics advice within democracies, defining four idealised stances: the pure ethicist, the advocate, the ethics arbiter and the critical friend. (shrink)

Many researchers have documented how AI and data driven technologies have the potential to have profound effects on our lives—in ways that make these technologies stand out from those that went before. Around the world, we are seeing a significant growth in interest and investment in AI in healthcare. This has been coupled with rising concerns about the ethical implications of these technologies and an array of ethical guidelines for the use of AI and data in healthcare has arisen. Nevertheless, (...) the question of if and how AI and data technologies can be ethical remains open to debate. This paper aims to contribute to this debate by considering the wide range of implications that have been attributed to these technologies and asking whether current ethical guidelines take these factors into account. In particular, the paper argues that while current ethics guidelines for AI in healthcare effectively account for the four key issues identified in the ethics literature (transparency; fairness; responsibility and privacy), they have largely neglected wider issues relating to the way in which these technologies shape institutional and social arrangements. This, I argue, has given current ethics guidelines a strong focus on evaluating the impact of these technologies on the individual, while not accounting for the powerful social shaping effects of these technologies. To address this, the paper proposes a Multiscale Ethics Framework, which aims to help technology developers and ethical evaluations to consider the wider implications of these technologies. (shrink)