Ask ChatGPT – August 8, 2023

My Conversations with ChatGPT
Machine Translation (MT) and translations generated by AI have brought about a paradigm shift in the translation industry. The output of MT will continue to improve, especially when associated with clients’ translation memories and human editing. Language Service Providers are adapting and are including MT in their processes, when MT is applicable. While linguists will continue to be essential in the process, their role will shift from that of translators to validators of content generated by MT. At Excel Translations, we wanted to know what AI thinks about all of this and decided to have an open conversation on the matter with ChatGPT. I will regularly publish a question and ChatGPT’s response, uncensored.

QUESTION 40:

Is machine translation recommended for a terminology glossary?

Chat GPT’s Response:

Machine translation can be a useful tool for creating a terminology glossary, but it’s important to approach it with caution and consider its limitations. Here are some points to consider:

Pros:

1. Efficiency: Machine translation can quickly generate translations for a large number of terms, which can save time and effort compared to manual translation.
2. Consistency: If used properly, machine translation can help maintain consistent translations for specific terms throughout the glossary.
3. Initial Draft: Machine translation can provide an initial draft that human translators can then review, edit, and refine, which can speed up the process of creating the glossary.

Cons:

1. Accuracy: Machine translation is not always accurate, especially for technical and specialized terminology. It can produce errors or inappropriate translations that may not be suitable for a professional glossary.
2. Context: Machine translation often struggles with understanding context, which can lead to incorrect translations or misinterpretations of nuanced terms.
3. Cultural Nuances: Some terms may have cultural or regional nuances that machine translation might not capture accurately.
4. Quality Control: A glossary is a resource meant to provide accurate and reliable translations. Relying solely on machine translation without human review can lead to inaccuracies.

Best Practices:

If you decide to use machine translation for creating a terminology glossary, consider the following best practices:

1. Human Review: Always have human translators with expertise in the field review and edit the machine-generated translations to ensure accuracy and quality.
2. Customization: Some machine translation systems allow you to train them with your specific terminology and context. This can improve the accuracy of translations for your specific domain.
3. Post-Editing: Allocate time and resources for thorough post-editing of machine-generated translations. This step is crucial to refine the translations and ensure accuracy.
4. Limitations: Clearly document the limitations of machine-generated translations in the glossary itself, so users are aware of the potential inaccuracies.
5. Regular Updates: Machine translation models improve over time, so keep an eye on updates and improvements to the technology and adjust your glossary accordingly.

In summary, while machine translation can be a helpful tool for generating translations for a terminology glossary, it should be used as a starting point that requires human review, editing, and refinement to ensure accuracy and quality.