Artificial Intelligence in Health Professions Regulation: An Exploratory Qualitative Study of Nurse Regulators in Three Jurisdictions

Abstract

Background Artificial intelligence (AI) refers to a broad group of technologies that are increasingly commonplace in everyday life; however, they have had only limited application in regulatory practice. Purpose The present study explored nursing regulators’ perceptions of the role and value of AI in regulation and potential barriers and facilitators to the uptake and implementation of AI. Methods Three facilitated focus group sessions with 28 representatives of regulators from Australia, the United Kingdom, and the United States were conducted. Content analysis of verbatim transcripts was completed. Results Key themes that emerged included (a) interest in how AI could enhance sustainability and improve cost-effectiveness of certain regulatory processes and (b) concerns regarding how the term “artificial intelligence” itself could be problematic. Specific barriers to the uptake of AI in regulation included concerns regarding codification of system bias, negative public perception, and lack of clarity around accountability for decision-making. Facilitators to implementation included enhancing the consistency of processes and improving the decision-making and utility in supporting trend analyses and audit functions. Conclusion Additional work in exploring how best to incorporate evolving AI technologies in regulatory practice—and what they should be named—is required, but these findings suggest that promising outcomes may lie ahead. Artificial intelligence (AI) refers to a broad group of technologies that are increasingly commonplace in everyday life; however, they have had only limited application in regulatory practice. The present study explored nursing regulators’ perceptions of the role and value of AI in regulation and potential barriers and facilitators to the uptake and implementation of AI. Three facilitated focus group sessions with 28 representatives of regulators from Australia, the United Kingdom, and the United States were conducted. Content analysis of verbatim transcripts was completed. Key themes that emerged included (a) interest in how AI could enhance sustainability and improve cost-effectiveness of certain regulatory processes and (b) concerns regarding how the term “artificial intelligence” itself could be problematic. Specific barriers to the uptake of AI in regulation included concerns regarding codification of system bias, negative public perception, and lack of clarity around accountability for decision-making. Facilitators to implementation included enhancing the consistency of processes and improving the decision-making and utility in supporting trend analyses and audit functions. Additional work in exploring how best to incorporate evolving AI technologies in regulatory practice—and what they should be named—is required, but these findings suggest that promising outcomes may lie ahead.

Ähnliche Arbeiten