Cracking the code: a scoping review to unite disciplines in tackling legal issues in health artificial intelligence
Objectives The rapid integration of artificial intelligence (AI) in healthcare requires robust legal safeguards to ensure safety, privacy and non-discrimination, crucial for maintaining trust. Yet, unaddressed differences in disciplinary perspectives and priorities risk impeding effective reform. Th...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2025-04-01
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| Series: | BMJ Health & Care Informatics |
| Online Access: | https://informatics.bmj.com/content/32/1/e101112.full |
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| author | Tanya Horsley Colleen M Flood Sophie Nunnelley Michael Da Silva Sarathy Kanathasan Bryan Thomas Emily Ann Da Silva Valentina Ly Ryan C Daniel Mohsen Sheikh Hassani Devin Singh |
| author_facet | Tanya Horsley Colleen M Flood Sophie Nunnelley Michael Da Silva Sarathy Kanathasan Bryan Thomas Emily Ann Da Silva Valentina Ly Ryan C Daniel Mohsen Sheikh Hassani Devin Singh |
| author_sort | Tanya Horsley |
| collection | DOAJ |
| description | Objectives The rapid integration of artificial intelligence (AI) in healthcare requires robust legal safeguards to ensure safety, privacy and non-discrimination, crucial for maintaining trust. Yet, unaddressed differences in disciplinary perspectives and priorities risk impeding effective reform. This study uncovers convergences and divergences in disciplinary comprehension, prioritisation and proposed solutions to legal issues with health-AI, providing law and policymaking guidance.Methods Employing a scoping review methodology, we searched MEDLINE (Ovid), EMBASE (Ovid), HeinOnline Law Journal Library, Index to Foreign Legal Periodicals (HeinOnline), Index to Legal Periodicals and Books (EBSCOhost), Web of Science (Core Collection), Scopus and IEEE Xplore, identifying legal issue discussions published, in English or French, from January 2012 to July 2021. Of 18 168 screened studies, 432 were included for data extraction and analysis. We mapped the legal concerns and solutions discussed by authors in medicine, law, nursing, pharmacy, other healthcare professions, public health, computer science and engineering, revealing where they agree and disagree in their understanding, prioritisation and response to legal concerns.Results Critical disciplinary differences were evident in both the frequency and nature of discussions of legal issues and potential solutions. Notably, innovators in computer science and engineering exhibited minimal engagement with legal issues. Authors in law and medicine frequently contributed but prioritised different legal issues and proposed different solutions.Discussion and conclusion Differing perspectives regarding law reform priorities and solutions jeopardise the progress of health AI development. We need inclusive, interdisciplinary dialogues concerning the risks and trade-offs associated with various solutions to ensure optimal law and policy reform. |
| format | Article |
| id | doaj-art-ba800fe7a79c4a44afac8e758bf90be8 |
| institution | OA Journals |
| issn | 2632-1009 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Health & Care Informatics |
| spelling | doaj-art-ba800fe7a79c4a44afac8e758bf90be82025-08-20T02:16:06ZengBMJ Publishing GroupBMJ Health & Care Informatics2632-10092025-04-0132110.1136/bmjhci-2024-101112Cracking the code: a scoping review to unite disciplines in tackling legal issues in health artificial intelligenceTanya Horsley0Colleen M Flood1Sophie Nunnelley2Michael Da Silva3Sarathy Kanathasan4Bryan Thomas5Emily Ann Da Silva6Valentina Ly7Ryan C Daniel8Mohsen Sheikh Hassani9Devin Singh10Office of Research and Evaluation, The Royal College of Physicians and Surgeons of Canada, Ottawa, Ontario, CanadadeanLincoln Alexander School of Law, Toronto Metropolitan University, Toronto, Ontario, CanadaUniversity of Southampton School of Law, Southampton, UKThe Hospital for Sick Children, Toronto, Ontario, CanadaFaculty of Law, Queen’s University, Kingston, Ontario, CanadaUniversity of Ottawa Libraries, Ottawa, Ontario, CanadaUniversity of Ottawa Libraries, Ottawa, Ontario, CanadaUniversity of Toronto Temerty Faculty of Medicine, Toronto, Ontario, CanadaCarleton University Department of Systems and Computer Engineering, Ottawa, Ontario, CanadaPaediatric Emergency Medicine, The Hospital for Sick Children, Toronto, Ontario, CanadaObjectives The rapid integration of artificial intelligence (AI) in healthcare requires robust legal safeguards to ensure safety, privacy and non-discrimination, crucial for maintaining trust. Yet, unaddressed differences in disciplinary perspectives and priorities risk impeding effective reform. This study uncovers convergences and divergences in disciplinary comprehension, prioritisation and proposed solutions to legal issues with health-AI, providing law and policymaking guidance.Methods Employing a scoping review methodology, we searched MEDLINE (Ovid), EMBASE (Ovid), HeinOnline Law Journal Library, Index to Foreign Legal Periodicals (HeinOnline), Index to Legal Periodicals and Books (EBSCOhost), Web of Science (Core Collection), Scopus and IEEE Xplore, identifying legal issue discussions published, in English or French, from January 2012 to July 2021. Of 18 168 screened studies, 432 were included for data extraction and analysis. We mapped the legal concerns and solutions discussed by authors in medicine, law, nursing, pharmacy, other healthcare professions, public health, computer science and engineering, revealing where they agree and disagree in their understanding, prioritisation and response to legal concerns.Results Critical disciplinary differences were evident in both the frequency and nature of discussions of legal issues and potential solutions. Notably, innovators in computer science and engineering exhibited minimal engagement with legal issues. Authors in law and medicine frequently contributed but prioritised different legal issues and proposed different solutions.Discussion and conclusion Differing perspectives regarding law reform priorities and solutions jeopardise the progress of health AI development. We need inclusive, interdisciplinary dialogues concerning the risks and trade-offs associated with various solutions to ensure optimal law and policy reform.https://informatics.bmj.com/content/32/1/e101112.full |
| spellingShingle | Tanya Horsley Colleen M Flood Sophie Nunnelley Michael Da Silva Sarathy Kanathasan Bryan Thomas Emily Ann Da Silva Valentina Ly Ryan C Daniel Mohsen Sheikh Hassani Devin Singh Cracking the code: a scoping review to unite disciplines in tackling legal issues in health artificial intelligence BMJ Health & Care Informatics |
| title | Cracking the code: a scoping review to unite disciplines in tackling legal issues in health artificial intelligence |
| title_full | Cracking the code: a scoping review to unite disciplines in tackling legal issues in health artificial intelligence |
| title_fullStr | Cracking the code: a scoping review to unite disciplines in tackling legal issues in health artificial intelligence |
| title_full_unstemmed | Cracking the code: a scoping review to unite disciplines in tackling legal issues in health artificial intelligence |
| title_short | Cracking the code: a scoping review to unite disciplines in tackling legal issues in health artificial intelligence |
| title_sort | cracking the code a scoping review to unite disciplines in tackling legal issues in health artificial intelligence |
| url | https://informatics.bmj.com/content/32/1/e101112.full |
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