Copy the page URI to the clipboard
Sides, T.; Farrell, T. and Kbaier, D.
(2023).
DOI: https://doi.org/10.1007/978-3-031-35989-7_65
Abstract
AI has made significant advancements in healthcare, yet its applications are limited to secondary care, with little evidence of its use in primary care. Trust has been identified as a significant factor affecting AI usage, but it does not entirely explain why AI is deployed in some NHS sectors and not others. Organizational infrastructure may also contribute to the lack of AI use in primary care.
Macro level stakeholders such as government bodies and health trusts have expressed interest in integrating AI, allocating resources, and providing training for employees to encourage trust and acceptance of AI. Conversely, at the micro-level stakeholders such as general practitioners and patients, have identified factors such as fairness, accountability, transparency, and ethics as having an impact on trust in AI.
Despite their potential influence, meso-level stakeholders such as managers and IT experts have been largely overlooked in AI research. Investigating their perspectives on trust and relationships across organizational levels is crucial for successful implementation of AI in primary care.
We propose a mixed-methods study design based on a conceptual framework that combines the Technology Acceptance Model-3, Unified Theory of Acceptance and Use of Technology-2, and trust attributes. By combining these models, we aim to gain a better understanding of how stakeholders perceive AI both individually and across organisational levels. Using the proposed model, we present our early findings on the enablers and barriers to AI acceptance in UK primary care. Finally, we discuss future directions on how to overcome the identified barriers.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)
