Article
Ethics
Soogeun Samuel Lee
Summary: The essay evaluates the conceptualization of trust within the UK Government's Code of Conduct for data-driven health and care technologies, focusing on AI-driven technologies. It discusses the principles of rationally justified trust and value-based trust, arguing that the latter is more feasible when it comes to trusting AI due to its complexity and inexplicability. The author suggests that the Code of Conduct should explicitly emphasize the principle of value-based trust.
JOURNAL OF MEDICAL ETHICS
(2022)
Article
Psychology, Multidisciplinary
Hsiu-Ping Yueh, Ching-Yin Huang, Weijane Lin
Summary: Information and communication technology has a significant impact on contemporary society and people's lives, and deserves more research attention. This study aims to explore the key factors influencing the decision-making behaviors of information professionals when faced with information ethics issues. The results validate the hierarchy and criteria of professional information ethics and provide valuable information for the cultivation of professionals in different fields.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Ethics
Charalampia (Xaroula) Kerasidou, Angeliki Kerasidou, Monika Buscher, Stephen Wilkinson
Summary: Artificial intelligence is transforming healthcare and raising questions about public trust. Instead of focusing on building trust, efforts should be directed towards establishing reliance through strong legal and regulatory frameworks, continuously addressing issues and power imbalances. Trust should be seen as a result of an ongoing ethical relationship, not just a means to an end.
JOURNAL OF MEDICAL ETHICS
(2022)
Article
Medicine, General & Internal
Chenxi Wu, Huiqiong Xu, Dingxi Bai, Xinyu Chen, Jing Gao, Xiaolian Jiang
Summary: An analysis of the public's understanding of the application of medical artificial intelligence (AI) reveals that the public recognizes the unique advantages and convenience of medical AI, but also expresses concerns about ethical and legal issues. Therefore, it is crucial to apply and regulate medical AI in a standardized manner to ensure its effective utilization.
Article
Ethics
Florian Funer, Wenke Liedtke, Sara Tinnemeyer, Andrea Diana Klausen, Diana Schneider, Helena U. Zacharias, Martin Langanke, Sabine Salloch
Summary: Machine learning-driven clinical decision support systems (ML-CDSSs) show great promise in future routine and emergency care, but their clinical implementation raises numerous ethical challenges. This study examines the ethical implications of ML-CDSS on healthcare professionals' responsibility and decision-making authority, and provides concrete suggestions for ethically sound clinical implementation.
JOURNAL OF MEDICAL ETHICS
(2023)
Review
Pediatrics
Clare Delany, Bryanna Moore, Neera Bhatia, Elise Burn, Neil Wimalasundera, Anne Preisz
Summary: The accessibility of the internet has allowed people to gather information about child health and disease, which in turn has influenced clinical decisions and garnered support for treatment. As a result, pediatric clinicians must navigate multiple voices and opinions while prioritizing the needs of the child. This article proposes ethical principles and explores questions to assist clinicians in engaging ethically with the crowd, emphasizing the importance of practical interactional skills training.
ARCHIVES OF DISEASE IN CHILDHOOD
(2023)
Article
Ethics
Helen Smith, John Downer, Jonathan Ives
Summary: With the introduction of AI in healthcare, there is a need for professional guidance to support its use. Reports from National Health Service AI Lab & Health Education England focus on understanding and confidence in AI clinical decision support systems (AI-CDDSs), but lack specific guidance for clinical users. This paper argues that without addressing this deficit, clinical, professional, and reputational safety will be at risk.
JOURNAL OF MEDICAL ETHICS
(2023)
Article
Ethics
Thomas William Hoffman, Joseph Frederick Baker
Summary: Ransomware attacks on healthcare systems are increasingly common globally. A major attack in May 2021 crippled the information technology system of the Waikato District Health Board in New Zealand, posing numerous challenges for the Department of Orthopaedic Surgery in patient assessment, deferred elective surgeries, communication, and patient confidentiality. This article explores these issues through the lens of the four key principles of medical ethics, aiming to provide guidance to future departments that may face similar attacks.
JOURNAL OF MEDICAL ETHICS
(2023)
News Item
Multidisciplinary Sciences
Liam Drew
Summary: Researchers state that devices capable of recording and altering brain activity will present privacy concerns that question current human rights laws.
Article
Ethics
Charalampia (Xaroula) Kerasidou, Maeve Malone, Angela Daly, Francesco Tava
Summary: The digitalization of health and the use of health data in artificial intelligence and machine learning are prominent in the healthcare systems and policies of the UK and other countries. Obtaining reliable data for machine learning development is crucial, and UK health data sets are highly desirable for this purpose. However, maintaining public interest, benefit, and privacy poses challenges.
JOURNAL OF MEDICAL ETHICS
(2023)
Article
Computer Science, Artificial Intelligence
Florian Grond, Rossio Motta-Ochoa, Natalie Miyake, Tamar Tembeck, Melissa Park, Stefanie Blain-Moraes
Summary: The paper presents a framework for fostering genuine engagement from stakeholders through the case example of biomusic, analyzing emergent themes related to ethical issues in emotion-oriented systems design and proposing a design framework consisting of a technological, a human-centered, and an ecological lens for addressing these complex issues.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2022)
Article
Ethics
Lidia Flores, Seungjun Kim, Sean D. Young
Summary: Components of artificial intelligence (AI) like natural language processing (NLP) algorithms have improved the timely and robust analysis of social big data in healthcare. However, AI-based decisions may contain biases that could lead to inaccurate healthcare outcomes and exacerbate health disparities. Researchers must consider when and how bias may arise and explore algorithmic biases as a result of data collection, labeling, and modeling of NLP algorithms to reduce bias and improve health surveillance.
JOURNAL OF MEDICAL ETHICS
(2023)
Review
Medicine, General & Internal
Christian Ohmann, David Moher, Maximilian Siebert, Edith Motschall, Florian Naudet
Summary: The study found that while there is a high willingness to share IPD data from clinical trials, the actual data-sharing rates are suboptimal, and journals have poor to moderate enforcement of data-sharing policies. When data is requested, it is more often for secondary analysis and meta-analysis, rather than re-analysis. Studies on the real impact of data-sharing are rare and often use surrogate metrics like citation metrics.
Article
Ethics
Manuel Schneider, Effy Vayena, Alessandro Blasimme
Summary: The online space has become a digital public square where individuals interact and share ideas on a wide range of topics, including controversial ethical issues in science and technology. New disciplines like computational social science and social data science have expanded the scope of social science research by collecting and analyzing data in innovative ways. Integrating digital methods into bioethics research can help investigate novel digital phenomena and track the development of bioethical issues online, aligning with the aims of empirical bioethics and offering ways to tackle the increasing complexity of ethical issues in science and technology. This new domain of research can be termed digital bioethics.
JOURNAL OF MEDICAL ETHICS
(2021)
Article
Health Care Sciences & Services
Laura Kooij, Wim H. van Harten
Summary: The aim of this viewpoint is to inform the development of evidence for using standalone or interoperable systems in hospital practice. There is a gap between mHealth research and its widespread uptake in clinical practice. Standalone systems are suitable for assessing usability and feasibility, while interoperable systems are more sustainable and reflect the real hospital care setting.
Editorial Material
Ethics
Nikola Biller-Andorno, Andrea Ferrario, Sophie Gloeckler
AMERICAN JOURNAL OF BIOETHICS
(2022)
Article
Psychology
Steven M. Weisberg, Victor R. Schinazi, Andrea Ferrario, Nora S. Newcombe
Summary: Relying on shared tasks and stimuli enhances replicability of findings by allowing researchers to collect large data sets. In spatial navigation experiments, the use of unfamiliar virtual environments can pose challenges. This study discusses the discovery of a software bug in Virtual Silcton, a platform used for studying spatial navigation. The bug affected the accuracy of pointing tasks and had varying effects on participants.
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-LEARNING MEMORY AND COGNITION
(2023)
Article
Ethics
Andrea Ferrario, Sophie Gloeckler, Nikola Biller-Andorno
Summary: This paper discusses the application of artificial intelligence systems in healthcare and clinical decision-making, focusing on decision-making based on incapacitated patients' values and goals of care. The authors propose viewing preference predicting AI as sociotechnical systems with distinct life-cycles and explore the challenges and strategies for their resolution at different stages of development.
JOURNAL OF MEDICAL ETHICS
(2023)
Editorial Material
Ethics
Andrea Ferrario, Sophie Gloeckler, Nikola Biller-Andorno
JOURNAL OF MEDICAL ETHICS
(2023)
Article
Health Care Sciences & Services
Jasmine Kerr, Mara Naegelin, Michaela Benk, Florian Wangenheim, Erika Meins, Eleonora Vigano, Andrea Ferrario
Summary: This study used the value sensitive design (VSD) framework to identify relevant values of a digital stress management intervention (dSMI) at the workplace and assess users' comprehension of these values and derive specific design requirements informed by ethics. Results showed that while most employees were willing to use dSMI, there were significant concerns regarding its effectiveness and perpetuation of problems. Privacy and accountability concerns must be well addressed, especially when incorporating a machine learning-based monitoring component. The findings of this study will contribute to future VSD-based interventions and the integration of ethics in digital health.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Article
Psychology, Multidisciplinary
Raphael P. Weibel, Jasmine I. Kerr, Mara Naegelin, Andrea Ferrario, Victor R. Schinazi, Roberto La Marca, Christoph Hoelscher, Urs M. Nater, Florian von Wangenheim
Summary: Heart rate variability biofeedback (HRV-BF) is commonly used for stress management. This study explored the effects of different technologies and breathing techniques on HRV-BF. The results showed that practicing HRV-BF using a head-mounted display (HMD) led to greater improvements in HRV and cardiac coherence compared to standardised paced breathing on a screen. Immersing oneself in virtual reality with an HMD for HRV-BF also enhanced user experience. Further research is needed to validate the long-term effects of this mode of delivery.
COMPUTERS IN HUMAN BEHAVIOR
(2023)
Article
Philosophy
Michele Loi, Francesco Nappo, Eleonora Vigano
Summary: The use of algorithms for prediction-based decisions necessitates a consideration of what constitutes discrimination. We propose a counterfactual condition, building upon previous work, as a necessary requirement. By examining existing definitions of discrimination, we demonstrate the limitations of these definitions and showcase the significance of our proposed condition. This defense of the counterfactual condition helps establish the conceptual boundaries for claims about discriminatory acts or practices in society, which has practical implications for the ethics of algorithmic decision-making.
RES PUBLICA-A JOURNAL OF MORAL LEGAL AND POLITICAL PHILOSOPHY
(2023)
Article
History & Philosophy Of Science
Michele Loi, Andrea Ferrario, Eleonora Vigano
Summary: This article introduces a theory of trust and monitoring, which utilizes mathematical models based on two classes of functions to quantify trust and relate it to monitoring costs. Unlike other accounts of trust that focus on identifying specific factors, this theory characterizes trust as a quantifiable property of reliance relations. It is applicable to both human-human and human-artificial agent interactions and provides a rigorous methodology for measuring trust in empirical studies.
Article
Economics
Michele Loi, Anders Herlitz, Hoda Heidari
Summary: This article presents a fairness principle for evaluating decision-making based on predictions, which states that a decision rule is unfair if individuals directly impacted by the decisions, who are equal in terms of features justifying inequalities in outcomes, do not have equal statistical prospects of being benefited or harmed by them. The principle can be used to evaluate prediction-based decision-making from various perspectives of justice in outcome distributions.
ECONOMICS AND PHILOSOPHY
(2023)
Article
Political Science
Michele Loi, Paul-Olivier Dehaye, Ernst Hafen
Summary: This paper discusses the role of personal data platform cooperatives in realizing a just social system and applies Rawls's political philosophy to analyze the relationship between the institutional forms of a just society and the economic power derived from aggregating personal data. It argues that a society involving a significant number of personal data platform cooperatives is more suitable for realizing Rawls's principle of fair equality of opportunity.
CRITICAL REVIEW OF INTERNATIONAL SOCIAL AND POLITICAL PHILOSOPHY
(2023)
Article
Computer Science, Information Systems
Andrea Ferrario, Michele Loi
Summary: This paper introduces counterfactual explanations as a prominent interpretable artificial intelligence method and shows that retraining machine learning models over time may invalidate the counterfactual explanations. The authors propose a method called counterfactual data augmentation to improve the robustness of counterfactual explanations over time.
Article
Geriatrics & Gerontology
Andrea Ferrario, Minxia Luo, Angelina J. Polsinelli, Suzanne A. Moseley, Matthias R. Mehl, Kristina Yordanova, Mike Martin, Burcu Demiray
Summary: Machine learning and natural language processing (NLP) techniques can be used to predict working memory in older adults. Linguistic measures, part-of-speech (POS) tags, and social context information improve the performance of prediction models, which is important for designing an early warning system for detecting cognitive decline.
Article
Business
Michele Loi, Christian Hauser, Markus Christen
Summary: Clients may feel coerced into sharing personal data with insurance companies, which violates their autonomy. This choice to accept digital surveillance also threatens the client's autonomy. The adoption of digital surveillance by insurers creates further threats against autonomy. More moral and empirical research is needed on this issue.
JOURNAL OF BUSINESS ETHICS
(2022)
