Is AI translation really eco-friendly?
1 min read
The rise of large language models (LLMs) for machine translation (MT) has undeniably boosted productivity, but it also carries an environmental cost. Training these models and serving millions of on-the-fly translations daily demands substantial computational power and energy, which can lead to increased carbon emissions. While the EU AI Act (February 2025) centres on risk management, transparency and data governance,…
The rise of large language models (LLMs) for machine translation (MT) has undeniably boosted productivity, but it also carries an environmental cost. Training these models and serving millions of on-the-fly translations daily demands substantial computational power and energy, which can lead to increased carbon emissions.
While the EU AI Act (February 2025) centres on risk management, transparency and data governance, it does not yet mandate sustainability reporting for AI providers. Nevertheless, Europe’s broader digital sustainability initiatives encourage providers to monitor and disclose their energy consumption and carbon footprint—paving the way for greener AI services.
Translators can play their part by choosing platforms that optimise server efficiency, leverage renewable energy and batch requests. By favouring eco-conscious tools and workflows, it’s possible to balance high-quality translations with environmental responsibility.
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