5 Ways Translators Can Make AI Better 

Don’t fall into the trap of believing translators are out and AI is in. Hand in hand, the two are capable of much more than either alone.

The hand of a translator and the hand of AI coming together to symbolize the role translation services have in AI translation.

There is a lot of talk these days about how AI is likely to wipe out the entire professional translation industry. Though there is no doubt that AI presents the need for professional translation partners to adapt, the truth is that translators have much to offer AI in return for the benefits it provides. 

1. Providing High-Quality Parallel Corpora:

One of the most concrete ways in which translation services can assist in the development of AI is by creating, curating, and maintaining large datasets of parallel texts in multiple languages. Such datasets serve as training material for machine learning models, helping AI systems learn how to translate between languages more accurately. 

By providing well-translated, diverse content, translators can ensure that AI systems have access to high-quality training data. With language being as fluid as it is, the inclusion of professional translation partners would assure that these datasets would not only be precise, but up to date with trends and advances in any respective field. Naturally, such a setup would exponentially increase the accuracy of machine translation making it a far safer option than it is today.  

Annotating and Correcting Machine Translations:

Professional translators can and already do review and correct machine-generated translations (or MT) to improve their accuracy and fluency. By annotating errors and providing alternative translations, translators help AI systems learn from their mistakes and refine their language models. This process of post-editing machine translations (or MTPE) is crucial for identifying common errors and improving the overall quality of AI-generated translations for a variety of language combinations

3. Collaborating with Developers:

Though this may seem an illogical pairing, translators should absolutely collaborate with AI developers to provide feedback on translation systems and contribute to their ongoing development and improvement.  

By sharing insights from their linguistic expertise, translators can help developers understand the nuances of different languages and improve the performance of AI translation models. This collaboration may involve participating in beta testing, providing input on user interfaces, and suggesting improvements based on real-world translation challenges and cultural nuances. 

4. Conducting User Feedback and Evaluation Studies:  

Language service providers can also be harnessed to conduct user feedback and evaluation studies to assess the performance of AI translation systems in real-world scenarios.  

By soliciting feedback from end users and evaluating the quality of machine-generated translations in different contexts, translators can consistently identify areas for improvement and provide valuable insights to AI developers. This iterative feedback loop helps refine AI translation models and ensures that they meet the needs and expectations of users across diverse linguistic and cultural settings

5. Advocating for Ethical and Inclusive AI:

Regardless of having the whole world at its fingertips, AI is often suspiciously limited by the stereotypes of its creators. Translators are in a position to advocate for ethical and inclusive AI practices within the translation community and the broader tech industry.  

This includes promoting diversity and representation in training data, advocating for transparency and accountability in AI algorithms, and addressing biases and stereotypes in machine-generated translations. By championing these principles, translators can help ensure that AI translation systems benefit all users and uphold high standards of linguistic accuracy and cultural sensitivity. 

Progress is always a 2-way street and though we have all seen (and heard) what AI is capable of, we can’t seem to shake the tendency to look at it as a final product. However impressive, there is no one-size-fit-all translator that can effortlessly and precisely translate for all fields in all languages.  

Just as language is constantly in flux, so too must AI constantly adapt and improve to keep pace with us. As an industry, it is in our best interest to implement technology that benefits our clients and at GORR, we understand that to fall behind is to be left behind.  


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