Kathleen Murphy

Background There is growing consensus in favor of returning individual specific research results that are clinically actionable, valid, and reliable. However, deciding what and how research results should be returned remains a challenge. Researchers are key stakeholders in return of results decision-making and implementation. Multi-omics data contains medically relevant findings that could be considered for return. We sought to understand researchers' views regarding the potential for return of results for multi-omics data from a large, national consortium generating multi-omics data. Methods Researchers from the Molecular Transducers of Physical Activity Consortium (MoTrPAC) were recruited for in-depth semi-structured interviews. To assess understanding of potential clinical utility for types of data collected and attitudes towards return of results in multi-omic clinical studies, we devised an interview guide focusing on types of results generated in the study for hypothetical return based on review of the literature and professional expertise of team members. The semi-structured interviews were recorded, transcribed verbatim and co-coded. Thematic trends were identified for reporting. Results We interviewed a total of 16 individuals representative of 11 sites and 6 research roles across MoTrPAC. Many respondents expressed positive attitudes regarding hypothetical multi-omics results return, citing participant rights to their data and perception of minimal harm. Ethical and logistical concerns around the return of multi-omics results were raised, and they often mirrored those in the published literature for genomic return of results including: uncertain clinical validity, a lack of expertise to communicate results, and an unclear obligation regarding whether to return multi-omics results. With the exception of privacy concerns, respondents were able to give examples within multi-omics of how each point was relevant. Further, researchers called for more guidance from funding agencies and increased researcher education regarding return of results. Conclusion Overall, researchers expressed positive attitudes toward multi-omic return of results in principle, particularly if medically actionable. However, competing ethical considerations, logistical constraints, and need for more external guidance were raised as key implementation concerns. Future studies should consider views and experiences of other relevant stakeholders, specifically clinical genomics professionals and study participants, regarding the clinical utility of multi-omics information and multi-omics results return.

BackgroundArtificial intelligence (AI) has been described as the “fourth industrial revolution” with transformative and global implications, including in healthcare, public health, and global health. AI approaches hold promise for improving health systems worldwide, as well as individual and population health outcomes. While AI may have potential for advancing health equity within and between countries, we must consider the ethical implications of its deployment in order to mitigate its potential harms, particularly for the most vulnerable. This scoping review addresses the following question: What ethical issues have been identified in relation to AI in the field of health, including from a global health perspective?MethodsEight electronic databases were searched for peer reviewed and grey literature published before April 2018 using the concepts of health, ethics, and AI, and their related terms. Records were independently screened by two reviewers and were included if they reported on AI in relation to health and ethics and were written in the English language. Data was charted on a piloted data charting form, and a descriptive and thematic analysis was performed.ResultsUpon reviewing 12,722 articles, 103 met the predetermined inclusion criteria. The literature was primarily focused on the ethics of AI in health care, particularly on carer robots, diagnostics, and precision medicine, but was largely silent on ethics of AI in public and population health. The literature highlighted a number of common ethical concerns related to privacy, trust, accountability and responsibility, and bias. Largely missing from the literature was the ethics of AI in global health, particularly in the context of low- and middle-income countries (LMICs).ConclusionsThe ethical issues surrounding AI in the field of health are both vast and complex. While AI holds the potential to improve health and health systems, our analysis suggests that its introduction should be approached with cautious optimism. The dearth of literature on the ethics of AI within LMICs, as well as in public health, also points to a critical need for further research into the ethical implications of AI within both global and public health, to ensure that its development and implementation is ethical for everyone, everywhere.