In their thoughtful and well-supported target article, Andrew Garland, Stephanie Morain, Jeremy Sugarman (2023) argue that clinicians have a duty to participate in pragmatic clinical trials. This d...

We applaud Sedlakova and Trachsel’s work and their description of conversational artificial intelligence (CAI) as possessing a hybrid nature with features of both a tool and an agent (Sedlakova and...

Can machine intelligence do clinical ethics? And if so, would applying it to actual medical cases be desirable? In a recent target article (Meier et al. 2022), we described the piloting of our advisory algorithm METHAD. Here, we reply to commentaries published in response to our project. The commentaries fall into two broad categories: concrete criticism that concerns the development of METHAD; and the more general question as to whether one should employ decision-support systems of this kind—the debate we set (...) out to ignite with our target article. (shrink)

BackgroundHealthcare providers have to make ethically complex clinical decisions which may be a source of stress. Researchers have recently introduced Artificial Intelligence (AI)-based applications to assist in clinical ethical decision-making. However, the use of such tools is controversial. This review aims to provide a comprehensive overview of the reasons given in the academic literature for and against their use.MethodsPubMed, Web of Science, Philpapers.org and Google Scholar were searched for all relevant publications. The resulting set of publications was title and abstract (...) screened according to defined inclusion and exclusion criteria, resulting in 44 papers whose full texts were analysed using the Kuckartz method of qualitative text analysis.ResultsArtificial Intelligence might increase patient autonomy by improving the accuracy of predictions and allowing patients to receive their preferred treatment. It is thought to increase beneficence by providing reliable information, thereby, supporting surrogate decision-making. Some authors fear that reducing ethical decision-making to statistical correlations may limit autonomy. Others argue that AI may not be able to replicate the process of ethical deliberation because it lacks human characteristics. Concerns have been raised about issues of justice, as AI may replicate existing biases in the decision-making process.ConclusionsThe prospective benefits of using AI in clinical ethical decision-making are manifold, but its development and use should be undertaken carefully to avoid ethical pitfalls. Several issues that are central to the discussion of Clinical Decision Support Systems, such as justice, explicability or human–machine interaction, have been neglected in the debate on AI for clinical ethics so far.Trial registrationThis review is registered at Open Science Framework (https://osf.io/wvcs9). (shrink)

Chat Generative Pre-Trained Transformer (ChatGPT) has been a growing point of interest in medical education yet has not been assessed in the field of bioethics. This study evaluated the accuracy of ChatGPT-3.5 (April 2023 version) in answering text-based, multiple choice bioethics questions at the level of US third-year and fourth-year medical students. A total of 114 bioethical questions were identified from the widely utilised question banks UWorld and AMBOSS. Accuracy, bioethical categories, difficulty levels, specialty data, error analysis and character count (...) were analysed. We found that ChatGPT had an accuracy of 59.6%, with greater accuracy in topics surrounding death and patient–physician relationships and performed poorly on questions pertaining to informed consent. Of all the specialties, it performed best in paediatrics. Yet, certain specialties and bioethical categories were under-represented. Among the errors made, it tended towards content errors and application errors. There were no significant associations between character count and accuracy. Nevertheless, this investigation contributes to the ongoing dialogue on artificial intelligence’s (AI) role in healthcare and medical education, advocating for further research to fully understand AI systems’ capabilities and constraints in the nuanced field of medical bioethics. (shrink)