Legal concerns in health-related artificial intelligence: a scoping review protocol

Abstract

Background Medical innovations offer tremendous hope. Yet, similar innovations in governance (law, policy, ethics) are likely necessary if society is to realize medical innovations’ fruits and avoid their pitfalls. As innovations in artificial intelligence (AI) advance at a rapid pace, scholars across multiple disciplines are articulating concerns in health-related AI that likely require legal responses to ensure the requisite balance. These scholarly perspectives may provide critical insights into the most pressing challenges that will help shape and advance future regulatory reforms. Yet, to the best of our knowledge, there is no comprehensive summary of the literature examining legal concerns in relation to health-related AI. We thus aim to summarize and map the literature examining legal concerns in health-related AI using a scoping review approach. Methods The scoping review framework developed by (J Soc Res Methodol 8:19-32, 2005) and extended by (Implement Sci 5:69, 2010) and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews (PRISMA-ScR) guided our protocol development. In close consultation with trained librarians, we will develop a highly sensitive search for MEDLINE® (OVID) and adapt it for multiple databases designed to comprehensively capture texts in law, medicine, nursing, pharmacy, other healthcare professions (e.g., dentistry, nutrition), public health, computer science, and engineering. English- and French-language records will be included if they examine health-related AI, describe or prioritize a legal concern in health-related AI or propose a solution thereto, and were published in 2012 or later. Eligibility assessment will be conducted independently and in duplicate at all review stages. Coded data will be analyzed along themes and stratified across discipline-specific literatures. Discussion This first-of-its-kind scoping review will summarize available literature examining, documenting, or prioritizing legal concerns in health-related AI to advance law and policy reform(s). The review may also reveal discipline-specific concerns, priorities, and proposed solutions to the concerns. It will thereby identify priority areas that should be the focus of future reforms and regulatory options available to stakeholders in reform processes. Trial registration This protocol was submitted to the Open Science Foundation registration database. See https://osf.io/zav7w.

Cracking the Code: A Scoping Review to Unite Disciplines in Tackling Legal Issues in Health Artificial Intelligence

“…We aimed to assess which legal concerns were raised, how they were characterized, and what solutions were proposed by these disciplines. [13] Our review was guided by an a priori protocol and conducted in accordance with the Arksey and O'Malley framework as extended by Levac et al [13][14][15] Reporting was informed by the PRISMA Extension for Scoping Reviews (PRISMA-ScR), including the six Arskey and O'Malley stages. [14] Stage 1: Identifying the Research Question(s)…”

“…For full search terms (used for MEDLINE® and adapted to other databases) see supplemental e-Table 2 or the Protocol. [13] Searches were augmented by hand-searching reference lists of relevant full-text records. [16] All records were imported into a proprietary review software program (Covidence®) for duplicates removal and eligibility assessment.…”

“…Writers in medicine worried about higher risk to clinicians because "the physician is still the natural target of blame" for patient harm. [13][14][15] -Frequent discussion of the balance between human and AI decision-making, with authors from medicine especially emphasizing the value in having a human "in the loop". Some legal writers worried clinician second-guessing might compromise AI's performance.…”

“…Systematic reviews were tracked to ensure inclusion of relevant primary sources. [13] Decisions regarding record inclusion were made by two authors with guidance from a pilottested eligibility assessment form and using record management software. Agreement was assessed and reported using a Kappa statistic.…”

Interdisciplinary Dynamics in COVID-19 Research: Examining the Role of Computer Science and Collaboration Patterns

“…Interdisciplinary research entails not only acquiring a diverse range of data processing and analysis skills but also ensuring the accuracy and reliability of the data itself. Moreover, it is crucial to establish an efficient data management system that facilitates data storage, retrieval, and sharing while addressing concerns related to data security and privacy protection [23,42,[50][51][52]. Additionally, the standardization of data and processing protocol is essential to prevent compatibility issues arising from diverse theoretical frameworks across disciplines.…”