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| http://dx.doi.org/10.1080/15265161.2020.1820115 | DOI Listing |
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"I think all of us should have […] much better training in ethics." Ethical challenges in policy making during the COVID-19 pandemic: Results from an interview study with Swiss policy makers and scientists.
BMC Med Ethics
November 2024
Institute of Humanities in Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
Background: The COVID-19 pandemic posed many unprecedented challenges to health care systems and public health efforts worldwide. Policy making and science were deeply intertwined, in particular with regard to the justification of health policy measures. In this context, ethical considerations were often at the core of decision-making trade-offs.
View Article and Find Full Text PDFFactors affecting the feasibility of post-authorisation RCTs for conditionally authorised anticancer medicines: a multistakeholder perspective from a qualitative focus group study.
BMJ Open
November 2024
Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands
Objective: The collection of comprehensive data from post-authorisation trials for conditionally authorised anticancer medicines is frequently delayed. This raises questions about the feasibility of post-authorisation randomised controlled trials (RCTs) that aim to address remaining uncertainties. Therefore, this study explored factors that facilitate or impede the feasibility of post-authorisation RCTs from the perspective of stakeholders directly involved in the design, medical-ethical approval, and conduct of these RCTs.
View Article and Find Full Text PDFToward a responsible future: recommendations for AI-enabled clinical decision support.
J Am Med Inform Assoc
November 2024
Division of Clinical Informatics, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, United States.
Article Synopsis
- Using artificial intelligence (AI) in healthcare can help doctors make better decisions but has challenges like ensuring it’s safe and fair.
- The paper suggests making clear rules and methods to develop and test AI systems for patient safety.
- A big meeting with over 200 experts took place to find solutions on using AI in healthcare, leading to important recommendations for better AI systems.
When time is of the essence: ethical reconsideration of XAI in time-sensitive environments.
J Med Ethics
September 2024
National Center for Tumor Diseases (NCT) Heidelberg, NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Germany, Heidelberg University, Medical Faculty Heidelberg, Heidelberg University Hospital, Department of Medical Oncology, Section Translational Medical Ethics, Heidelberg, Germany.
The objective of explainable artificial intelligence systems designed for clinical decision support (XAI-CDSS) is to enhance physicians' diagnostic performance, confidence and trust through the implementation of interpretable methods, thus providing for a superior epistemic positioning, a robust foundation for critical reflection and trustworthiness in times of heightened technological dependence. However, recent studies have revealed shortcomings in achieving these goals, questioning the widespread endorsement of XAI by medical professionals, ethicists and policy-makers alike. Based on a surgical use case, this article challenges generalising calls for XAI-CDSS and emphasises the significance of time-sensitive clinical environments which frequently preclude adequate consideration of system explanations.
View Article and Find Full Text PDFChatGPT as Research Scientist: Probing GPT's capabilities as a Research Librarian, Research Ethicist, Data Generator, and Data Predictor.
Proc Natl Acad Sci U S A
August 2024
Department of Psychology, Harvard University, Cambridge, MA 02138.
How good a research scientist is ChatGPT? We systematically probed the capabilities of GPT-3.5 and GPT-4 across four central components of the scientific process: as a Research Librarian, Research Ethicist, Data Generator, and Novel Data Predictor, using psychological science as a testing field. In Study 1 (Research Librarian), unlike human researchers, GPT-3.
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