The application of machine learning in health care holds great promise for improving care. Indeed, our own team is collaborating with experts in machine learning and statistical modeling to bu...

The authors offer their sincere thanks to all of the commentators for taking the time to comment on our work ; one of the advantages of the AJOB format is immediate feedback,...

McCradden and colleagues' (2022) argues that machine learning in health care poses new challenges to appropriate evaluation for safe use in clinical care. It also claims that “the longstanding syst...

Machine learning heralds highly transformative approaches to the automation of numerous clinical tasks, from diagnosis to risk assessment, and from prognosis to informing treatment decisions....

In their article “A Research Ethics Framework for the Clinical Translation of Healthcare Machine Learning,” McCradden et al. highlight the various gaps that emerge when artificial intelligen...

The ethics of artificial intelligence and machine learning exemplify the conceptual struggle between applying familiar pathways of ethical analysis versus generating novel strategies. Mel...

The ethical review of research using methods of artificial intelligence and machine learning in health care contexts has become an important challenge for Research Ethics Boards (also refer...

Researchers are studying how artificial intelligence (AI) can be used to better detect, prognosticate and subgroup diseases. The idea that AI might advance medicine’s understanding of biological categories of psychiatric disorders, as well as provide better treatments, is appealing given the historical challenges with prediction, diagnosis and treatment in psychiatry. Given the power of AI to analyse vast amounts of information, some clinicians may feel obligated to align their clinical judgements with the outputs of the AI system. However, a potential (...) epistemic privileging of AI in clinical judgements may lead to unintended consequences that could negatively affect patient treatment, well-being and rights. The implications are also relevant to precision medicine, digital twin technologies and predictive analytics generally. We propose that a commitment to epistemic humility can help promote judicious clinical decision-making at the interface of big data and AI in psychiatry. (shrink)

McCradden et al. propose to close the “AI chasm” between algorithms and clinically meaningful application using the norms of evidence-based medicine and clinical research, with the rat...

McCradden and colleagues' argues that machine learning in health care poses new challenges to appropriate evaluation for safe use in clinical care. It also claims that “the longstanding syst...

The research ethics framework put forward by McCradden et al. to support systematic inquiry in the development of artificial intelligence and machine learning technologies in healt...

Artificial intelligence (AI) has garnered tremendous attention in health care, and many hope that AI can enhance our health system’s ability to care for people with chronic and degenerative conditions, including Parkinson’s Disease (PD). This paper reports the themes and lessons derived from a qualitative study with people living with PD, family caregivers, and health care providers regarding the ethical dimensions of using AI to monitor, assess, and predict PD symptoms and progression. Thematic analysis identified ethical concerns at four intersecting (...) levels: personal, interpersonal, professional/institutional, and societal levels. Reflecting on potential benefits of predictive algorithms that can continuously collect and process longitudinal data, participants expressed a desire for more timely, ongoing, and accurate information that could enhance management of day-to-day fluctuations and facilitate clinical and personal care as their disease progresses. Nonetheless, they voiced concerns about intersecting ethical questions around evolving illness identities, familial and professional care relationships, privacy, and data ownership/governance. The multi-layer analysis provides a helpful way to understand the ethics of using AI in monitoring and managing PD and other chronic/degenerative conditions. (shrink)

McCradden et al.’s article makes a distinctive contribution to the growing literature on the ethics of artificial intelligence in medicine. Not only do the authors raise important ethical is...