28/02/2026

AI Bias in Legal Translation

Legal translation presents unique challenges because legal concepts are culturally and jurisdictionally embedded. Machine translation systems learn from vast collections of previously translated legal texts. When these training datasets are imbalanced—skewed toward particular legal systems, jurisdictions, or document types—the AI replicates those patterns inappropriately.
15/02/2026

AI Translation Bias in Healthcare

AI has legitimate applications in medical and pharmaceutical translation—accelerating turnaround for appropriate content types, improving terminology consistency across large documentation sets, and reducing costs for lower-risk materials. But in healthcare and pharmaceutical contexts, AI must be deployed with rigorous governance, transparent limitations, and appropriate human oversight.
27/01/2026

AI Bias in Translation & Localisation: Why Data Quality Matters

AI is only as smart as the data it’s fed. When datasets lack diversity, your global message risks being lost—or worse, becoming offensive. Think of AI as a reflection of its training. If the data is skewed, the translation will be too. We break down why biased datasets are the biggest hurdle in modern machine translation and how My Language Hub combines human expertise with ethical AI to keep your communication accurate.
24/02/2025

EU AI Act: implications for Translation Services

The EU Artificial Intelligence Act is poised to revolutionise many industries, and translation services are no exception. As AI becomes an increasingly integral part of the translation process—from machine translation (MT) tools to sophisticated language models—the new regulation brings both challenges and opportunities. In this blog, we break down the key implications of the Act for translation services, discuss the potential benefits, and provide strategies for adapting to this evolving regulatory landscape.