How Machine Translation Affects Society: Exploring Care, Bias, and Fairness in Automated Translation

What is it about?

This book looks at how automatic translation tools—like Google Translate—affect people and society. While these tools make communication across languages faster and easier, they can also create problems. For example, they may produce biased translations, ignore cultural differences, or exclude certain groups, such as Indigenous communities. The authors suggest that instead of focusing only on speed and efficiency, we should think about translation technologies in terms of care—care for users, care for communities, and care for fairness. The chapters explore real-life situations where machine translation can help or harm: in education, healthcare, law, politics, and everyday communication. They also discuss issues like gender bias in translations and the invisibility of minority languages online. The main idea is that translation technology is not neutral—it reflects social values and power dynamics. By approaching it with a mindset of care, we can design and use these tools in ways that support equality, respect diversity, and strengthen democracy.

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Photo by Herbert Goetsch on Unsplash

Photo by Herbert Goetsch on Unsplash

Why is it important?

This book is distinctive because it approaches machine translation from an ethics of care perspective, rather than focusing only on technical accuracy or efficiency. By emphasizing relationships, responsibility, and attentiveness to users, it introduces a fresh way of thinking about technology that is rarely applied to translation studies. It also stands out for its interdisciplinary scope, bringing together perspectives from translation studies, law, education, healthcare, Indigenous rights, and technology. This range allows the volume to capture the wide variety of social impacts that automated translation has across different areas of life. Another unique feature is its explicit attention to groups that are often overlooked in discussions of language technology, such as Indigenous communities, everyday users with limited technical knowledge, and women affected by gender bias in translation systems. The work is especially timely given the rapid expansion of machine translation and related artificial intelligence tools into everyday life. These technologies are no longer confined to professional or academic contexts; they now shape education, healthcare, legal systems, and political communication. At the same time, public debates about AI are increasingly concerned with fairness, accountability, and social consequences. By addressing these issues directly and proposing care-centered approaches to design and use, the book offers tools for making translation technology more equitable, inclusive, and socially responsive. Its contribution lies not only in diagnosing existing problems but also in providing a framework for rethinking how translation technologies can support diversity, equality, and democracy.