Multidisciplinary considerations of fairness in medical AI: A scoping review.

Artificial Intelligence (AI) technology has been developed significantly in recent years. The fairness of medical AI is of great concern due to its direct relation to human life and health. This review aims to analyze the existing research literature on fairness in medical AI from the perspectives of computer science, medical science, and social science (including law and ethics). The objective of the review is to examine the similarities and differences in the understanding of fairness, explore influencing factors, and investigate potential measures to implement fairness in medical AI across English and Chinese literature. This study employed a scoping review methodology and selected the following databases: Web of Science, MEDLINE, Pubmed, OVID, CNKI, WANFANG Data, etc., for the fairness issues in medical AI through February 2023. The search was conducted using various keywords such as "artificial intelligence," "machine learning," "medical," "algorithm," "fairness," "decision-making," and "bias." The collected data were charted, synthesized, and subjected to descriptive and thematic analysis. After reviewing 468 English papers and 356 Chinese papers, 53 and 42 were included in the final analysis. Our results show the three different disciplines all show significant differences in the research on the core issues. Data is the foundation that affects medical AI fairness in addition to algorithmic bias and human bias. Legal, ethical, and technological measures all promote the implementation of medical AI fairness. Our review indicates a consensus regarding the importance of data fairness as the foundation for achieving fairness in medical AI across multidisciplinary perspectives. However, there are substantial discrepancies in core aspects such as the concept, influencing factors, and implementation measures of fairness in medical AI. Consequently, future research should facilitate interdisciplinary discussions to bridge the cognitive gaps between different fields and enhance the practical implementation of fairness in medical AI.

Wang Y ，Song Y ，Ma Z ，Han X ... -  《-》

Erratum: Eyestalk Ablation to Increase Ovarian Maturation in Mud Crabs.

《Jove-Journal of Visualized Experiments》

Ethics of Procuring and Using Organs or Tissue from Infants and Newborns for Transplantation, Research, or Commercial Purposes: Protocol for a Bioethics Scoping Review.

Since the inception of transplantation, it has been crucial to ensure that organ or tissue donations are made with valid informed consent to avoid concerns about coercion or exploitation. This issue is particularly challenging when it comes to infants and younger children, insofar as they are unable to provide consent. Despite their vulnerability, infants' organs and tissues are considered valuable for biomedical purposes due to their size and unique properties. This raises questions about the conditions under which it is permissible to remove and use these body parts for transplantation, research, or commercial purposes. The aim of this protocol is to establish a foundation for a scoping review that will identify, clarify, and categorise the main ethical arguments regarding the permissibility of removing and using organs or tissues from infants. The scoping review will follow the methodology outlined by the Joanna Briggs Institute (JBI), consisting of five stages: (1) identifying the research question, (2) developing the search strategy, (3) setting inclusion criteria, (4) extracting data, and (5) presenting and analysing the results. We will include both published and unpublished materials that explicitly discuss the ethical arguments related to the procurement and use of infant organs or tissues in the biomedical context. The search will cover various databases, including the National Library of Medicine, Web of Science, EBSCO, and others, as well as grey literature sources. Two raters will independently assess the eligibility of articles, and data from eligible studies will be extracted using a standardised form. The extracted data will then be analysed descriptively through qualitative content analysis. There has been debate about how to respect the rights and interests of organ and tissue donors since the beginning of transplantation practice, given the moral risks involved in procuring parts of their bodies and using them for transplantation or research. A major concern has been to ensure that, at a minimum, donation of organs or other bodily tissues for transplantation or research is done under conditions of valid informed consent, so as to avoid coercion or exploitation among other moral harms. In the case of infants and younger children, however, this concern poses special difficulties insofar as infants and younger children are deemed incapable of providing valid consent. Due to their diminutive size and other distinctive properties, infants' organs and tissues are seen as valuable for biomedical purposes. Yet, the heightened vulnerability of infants raises questions about when and whether it is ever permissible to remove these body parts or use them in research or for other purposes. The aim of this protocol is to form the basis of a systematic scoping review to identify, clarify, and systematise the main ethical arguments for and against the permissibility of removing and using infant or newborn (hereafter, "infant") organs or tissues in the biomedical context (i.e. for transplantation, research, or commercial purposes). Our scoping review will broadly follow the well-established methodology outlined by the Joanna Briggs Institute ( Peters et al., 2020). We will follow a five-stage review process: (1) identification of the research question, (2) development of the search strategy, (3) inclusion criteria, (4) data extraction, and (5) presentation and analysis of the results. Published and unpublished bibliographic material (including reports, dissertations, book chapters, etc.) will be considered based on the following inclusion criteria: the presence of explicit (bio)ethical arguments or reasons (concept) for or against the procurement and use of organs or tissues from infants, defined as a child from birth until 1 year old (population), in the biomedical domain, including transplantation, research, and commercial development (context). We will search for relevant studies in the National Library of Medicine (including PubMed and MEDLINE), Virtual Health Library, Web of Science, Google Scholar, EBSCO, Google Scholar, PhilPapers, The Bioethics Literature Database (BELIT), EthxWeb as well as grey literature sources (e.g., Google, BASE, OpenGrey, and WorldCat) and the reference lists of key studies to identify studies suitable for inclusion. A three-stage search strategy will be used to determine the eligibility of articles, as recommended by the JBI methodological guidelines. We will exclude sources if (a) the full text is not accessible, (b) the main text is in a language other than English, or (c) the focus is exclusively on scientific, legal, or religious/theological arguments. All articles will be independently assessed for eligibility between two raters (MB & XL); data from eligible articles will be extracted and charted using a standardised data extraction form. The extracted data will be analysed descriptively using basic qualitative content analysis. Ethical review is not required as scoping reviews are a form of secondary data analysis that synthesise data from publicly available sources. Our dissemination strategy includes peer review publication, presentation at conferences, and outreach to relevant stakeholders. The results will be reported according to the PRISMA-ScR guidelines. An overview of the general data from the included studies will be presented in the form of graphs or tables showing the distribution of studies by year or period of publication, country of origin, and key ethical arguments. These results will be accompanied by a narrative summary describing how each included study or article relates to the aims of this review. Research gaps will be identified and limitations of the review will also be highlighted. A paper summarising the findings from this review will be published in a peer-reviewed journal. In addition, a synthesis of the key findings will be disseminated to biomedical settings (e.g., conferences or workshops, potentially including ones linked to university hospitals) in the UK, USA, Türkiye, and Singapore. They will also be shared with the academic community and policy makers involved in the organ procurement organisations (OPO), which will potentially consider our recommendations in their decision-making processes regarding infant tissue/organ donation practice in these countries. The use of a rigorous, well-established methodological framework will ensure the production of a high-quality scoping review that will contribute to the bioethics literature.A comprehensive search of disciplinary and cross-disciplinary databases will be undertaken to ensure coverage of all possible sources that meet the inclusion criteria for the review.This review will focus exclusively on infant tissue/organ procurement/use in biomedical contexts, providing a comprehensive and reliable source of ethical arguments for future debates on this sensitive topic.The review will be limited to articles published in English, which increases the risk of missing relevant sources published in other languages.The review will be limited to articles for which the full text is available, which increases the risk of missing relevant sources that otherwise may have been included in the scoping review had the full text been accessible.

Barış M ，Lim X ，T Almonte M ，Shaw D ，Brierley J ，Porsdam Mann S ，Nguyen T ，Menikoff J ，Wilkinson D ，Savulescu J ，Earp BD ... -  《-》

Artificial intelligence technologies and compassion in healthcare: A systematic scoping review.

Advances in artificial intelligence (AI) technologies, together with the availability of big data in society, creates uncertainties about how these developments will affect healthcare systems worldwide. Compassion is essential for high-quality healthcare and research shows how prosocial caring behaviors benefit human health and societies. However, the possible association between AI technologies and compassion is under conceptualized and underexplored. The aim of this scoping review is to provide a comprehensive depth and a balanced perspective of the emerging topic of AI technologies and compassion, to inform future research and practice. The review questions were: How is compassion discussed in relation to AI technologies in healthcare? How are AI technologies being used to enhance compassion in healthcare? What are the gaps in current knowledge and unexplored potential? What are the key areas where AI technologies could support compassion in healthcare? A systematic scoping review following five steps of Joanna Briggs Institute methodology. Presentation of the scoping review conforms with PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews). Eligibility criteria were defined according to 3 concept constructs (AI technologies, compassion, healthcare) developed from the literature and informed by medical subject headings (MeSH) and key words for the electronic searches. Sources of evidence were Web of Science and PubMed databases, articles published in English language 2011-2022. Articles were screened by title/abstract using inclusion/exclusion criteria. Data extracted (author, date of publication, type of article, aim/context of healthcare, key relevant findings, country) was charted using data tables. Thematic analysis used an inductive-deductive approach to generate code categories from the review questions and the data. A multidisciplinary team assessed themes for resonance and relevance to research and practice. Searches identified 3,124 articles. A total of 197 were included after screening. The number of articles has increased over 10 years (2011, n = 1 to 2021, n = 47 and from Jan-Aug 2022 n = 35 articles). Overarching themes related to the review questions were: (1) Developments and debates (7 themes) Concerns about AI ethics, healthcare jobs, and loss of empathy; Human-centered design of AI technologies for healthcare; Optimistic speculation AI technologies will address care gaps; Interrogation of what it means to be human and to care; Recognition of future potential for patient monitoring, virtual proximity, and access to healthcare; Calls for curricula development and healthcare professional education; Implementation of AI applications to enhance health and wellbeing of the healthcare workforce. (2) How AI technologies enhance compassion (10 themes) Empathetic awareness; Empathetic response and relational behavior; Communication skills; Health coaching; Therapeutic interventions; Moral development learning; Clinical knowledge and clinical assessment; Healthcare quality assessment; Therapeutic bond and therapeutic alliance; Providing health information and advice. (3) Gaps in knowledge (4 themes) Educational effectiveness of AI-assisted learning; Patient diversity and AI technologies; Implementation of AI technologies in education and practice settings; Safety and clinical effectiveness of AI technologies. (4) Key areas for development (3 themes) Enriching education, learning and clinical practice; Extending healing spaces; Enhancing healing relationships. There is an association between AI technologies and compassion in healthcare and interest in this association has grown internationally over the last decade. In a range of healthcare contexts, AI technologies are being used to enhance empathetic awareness; empathetic response and relational behavior; communication skills; health coaching; therapeutic interventions; moral development learning; clinical knowledge and clinical assessment; healthcare quality assessment; therapeutic bond and therapeutic alliance; and to provide health information and advice. The findings inform a reconceptualization of compassion as a human-AI system of intelligent caring comprising six elements: (1) Awareness of suffering (e.g., pain, distress, risk, disadvantage); (2) Understanding the suffering (significance, context, rights, responsibilities etc.); (3) Connecting with the suffering (e.g., verbal, physical, signs and symbols); (4) Making a judgment about the suffering (the need to act); (5) Responding with an intention to alleviate the suffering; (6) Attention to the effect and outcomes of the response. These elements can operate at an individual (human or machine) and collective systems level (healthcare organizations or systems) as a cyclical system to alleviate different types of suffering. New and novel approaches to human-AI intelligent caring could enrich education, learning, and clinical practice; extend healing spaces; and enhance healing relationships. In a complex adaptive system such as healthcare, human-AI intelligent caring will need to be implemented, not as an ideology, but through strategic choices, incentives, regulation, professional education, and training, as well as through joined up thinking about human-AI intelligent caring. Research funders can encourage research and development into the topic of AI technologies and compassion as a system of human-AI intelligent caring. Educators, technologists, and health professionals can inform themselves about the system of human-AI intelligent caring.

Morrow E ，Zidaru T ，Ross F ，Mason C ，Patel KD ，Ream M ，Stockley R ... -  《Frontiers in Psychology》

Ethical, legal, and social considerations of AI-based medical decision-support tools: A scoping review.

Recent developments in the field of Artificial Intelligence (AI) applied to healthcare promise to solve many of the existing global issues in advancing human health and managing global health challenges. This comprehensive review aims not only to surface the underlying ethical and legal but also social implications (ELSI) that have been overlooked in recent reviews while deserving equal attention in the development stage, and certainly ahead of implementation in healthcare. It is intended to guide various stakeholders (eg. designers, engineers, clinicians) in addressing the ELSI of AI at the design stage using the Ethics by Design (EbD) approach. The authors followed a systematised scoping methodology and searched the following databases: Pubmed, Web of science, Ovid, Scopus, IEEE Xplore, EBSCO Search (Academic Search Premier, CINAHL, PSYCINFO, APA PsycArticles, ERIC) for the ELSI of AI in healthcare through January 2021. Data were charted and synthesised, and the authors conducted a descriptive and thematic analysis of the collected data. After reviewing 1108 papers, 94 were included in the final analysis. Our results show a growing interest in the academic community for ELSI in the field of AI. The main issues of concern identified in our analysis fall into four main clusters of impact: AI algorithms, physicians, patients, and healthcare in general. The most prevalent issues are patient safety, algorithmic transparency, lack of proper regulation, liability & accountability, impact on patient-physician relationship and governance of AI empowered healthcare. The results of our review confirm the potential of AI to significantly improve patient care, but the drawbacks to its implementation relate to complex ELSI that have yet to be addressed. Most ELSI refer to the impact on and extension of the reciprocal and fiduciary patient-physician relationship. With the integration of AIbased decision making tools, a bilateral patient-physician relationship may shift into a trilateral one.

Čartolovni A ，Tomičić A ，Lazić Mosler E 《-》