Evaluation of Generative Artificial Intelligence Implementation Impacts in Social and Health Care Language Translation: Mixed Methods Case Study.

ABSTRACT:

Background

Generative artificial intelligence (GAI) is expected to enhance the productivity of the public social and health care sector while maintaining, at minimum, current standards of quality and user experience. However, empirical evidence on GAI impacts in practical, real-life settings remains limited.

Objective

This study investigates productivity, machine translation quality, and user experience impacts of the GPT-4 language model in an in-house language translation services team of a large well-being services county in Finland.

Methods

A mixed methods study was conducted with 4 in-house translators between March and June 2024. Quantitative data of 908 translation segments were collected in real-life conditions using the computer-assisted language translation

SUBMITTER: Martikainen M 

PROVIDER: S-EPMC12443352 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature