Thomas F Burns

This paper is a summary of philosophy, theory, and practice arising from collective writing experiments conducted between 2016 and 2022 in the community associated with the Editors’ Collective and more than 20 scholarly journals. The main body of the paper summarises the community’s insights into the many faces of collective writing. Appendix 1 presents the workflow of the article’s development. Appendix 2 lists approximately 100 collectively written scholarly articles published between 2016 and 2022. Collective writing is a continuous struggle for meaning-making, and our research insights merely represent one milestone in this struggle. Collective writing can be designed in many different ways, and our workflow merely shows one possible design that we found useful. There are many more collectively written scholarly articles than we could gather, and our reading list merely offers sources that the co-authors could think of. While our research insights and our attempts at synthesis are inevitably incomplete, ‘Collective Writing: The Continuous Struggle for Meaning-Making’ is a tiny theoretical stepping stone and a useful overview of sources for those interested in theory and practice of collective writing.

Parker's vision of ‘adversarial cooperation’ offers a compelling framework for navigating moral disagreement in pluralistic societies, emphasising the need for bioethical expertise grounded in facilitating inclusive dialogue across difference rather than providing definitive answers. His model depends fundamentally on authentic human engagement, where moral authority emerges from demonstrated capacity to navigate complex ethical terrain through principled yet pragmatic processes that honour diverse lived experiences. However, the rapid advancement of artificial intelligence (AI) systems, particularly large language models (LLMs) and agentic AI, and rapid integration into society and academia, presents profound practical challenges to this framework that extend beyond mere technological disruption to threaten the very foundations of inclusive moral deliberation. We should seek to either align such AI systems with our deliberative frameworks or, at least, design such frameworks with such threats in mind.

Some physicians, in their care of patients at risk of misusing opioids, use machine learning (ML)-based prediction drug monitoring programmes (PDMPs) to guide their decision making in the prescription of opioids. This can cause a conflict: a PDMP Score can indicate a patient is at a high risk of opioid abuse while a patient expressly reports oppositely. The prescriber is then left to balance the credibility and trust of the patient with the PDMP Score. Pozzi1 argues that a prescriber who downgrades the credibility of a patient’s testimony based on a low PDMP Score is epistemically and morally unjustified and contributes to a form of testimonial injustice. This results in patients being silenced, excluded from decision-making processes and subjected to structural injustices. Additionally, the use of ML systems in medical practices raises concerns about perpetuating existing inequalities, overestimating their capabilities and displacing human authority. However, almost the very same critiques apply to human-based systems. Formalisation, ML systems included, should instead be viewed positively,2 and precisely as a powerful means to begin eroding these and other problems in ethically sensitive domains. In this case, the epistemic virtues of formalisation include promoting transparency, consistency and replicability in decision making. Rigorous ML systems can also help ensure that models …

The principles which can justify significantly risky nontherapeutic research on children are a combination of: (1) direct or indirect benefits to the child participants now and/or in the future (and these benefits need not necessarily be medical, they can also be socioeconomic or otherwise non-medical); (2) a high standard of informed consent that fundamentally focuses on the child participant's understanding (and capacity for understanding) of relevant features of informed consent. Researchers, parents and guardians, as well as child participants themselves, have different roles and obligations towards one another. This is not an issue of seeking to find excuses to expose children to risk, but rather an issue of seeking the least risky and most ethical way to do so if and when required by public health emergencies or to achieve directly beneficial scientific breakthroughs.