AI Translation Tools and Linguistic Inclusion in Healthcare
Ellen Van Praet (Ghent University)
The integration of Artificial Intelligence (AI) in translation tools holds considerable promise for enhancing linguistic inclusion and accessibility in healthcare services. This empirical study examines the perspectives of 20 healthcare managers in Flanders, Belgium, regarding the adoption of AI-powered translation tools to communicate with non-native patients. Through qualitative interviews analyzed using NVivo software, the research reveals a paradox within healthcare organizations’ inclusivity efforts: while healthcare providers quickly adopt AI tools for immediate benefits, managers express hesitation due to concerns about data privacy, reliability, and integration with Electronic Patient Records (EPR) and Electronic Medical Records (EMR) systems.
The study discusses specific cases where managers reported how AI tools effectively broke down language barriers, facilitating inclusive communication with non-native speakers. However, it also examines instances where they reported that language barriers persisted due to the tools’ inadequacies. The tension between the rapid adoption of AI tools and institutional caution may result in unintended exclusion, as managers weigh the operational benefits against potential risks.
The paradox remains unresolved because, while the operational benefits are clear and immediate, the risk management issues are complex and difficult to address, leading to a state of tension and uncertainty within the healthcare system in Flanders. Hence, in conclusion, this study highlights the need for validation processes, clearer guidelines, privacy-preserving mechanisms, and the provision of necessary infrastructure and training to support healthcare organizations’ inclusivity efforts.
Keywords: AI translation tools, linguistic inclusion, healthcare accessibility, usability, GDPR, qualitative research, applied linguistics