Evaluating the Usability and Accessibility of Cloud-Based AI Translation Interfaces: A Systematic Review of Freelancer User Experience (UX)

Munawaroh, Silvi

International Journal of Research and Applied Technology (INJURATECH)
Vol. 4 No. 2 (2024): Vol 4 No 2 (2024)

This study evaluates the usability and accessibility of cloud-based AI translation interfaces for freelance translators. Using a systematic literature review (SLR) approach, this research synthesizes academic publications and industry reports from the last decade to identify global UX trends in cloud-native CAT tools. Findings reveal that while cloud infrastructure democratizes access to high-level Neural Machine Translation (NMT), significant barriers remain, including high-latency issues in remote regions, steep learning curves for complex AI dashboards, and economic constraints of subscription models. The analysis suggests that current AI infrastructures often prioritize technical scalability over the ergonomic and cognitive needs of non-technical linguists, exacerbating the digital divide. The study concludes that a "Translator-Centered Design" framework is essential to ensure that AI-driven cloud architectures are inclusive and accessible, recommending that developers optimize low-bandwidth performance to support the global freelance community effectively