1. Assess privacy

Ensure sensitive content is not compromised during translation. Some open source tools can send data to third-party servers for processing. It is therefore preferable to choose solutions that guarantee confidentiality. Either by internalizing the solution to your organization or by subscribing to SaaS with your translation partner.

2. Protect data

If you need to translate sensitive content, consider additional protection measures, such as encrypting data before translation or using local servers to limit unauthorized access. If you don’t like either of these suggestions, you’ll need to “anonymize” the data intended for translation so as to protect it.

3. Check quality

NMT can provide translations of varying quality, depending on the technicality of the document, or its language level. Define specific quality criteria to evaluate machine translations. You can measure such things as accuracy, terminology consistency, and linguistic fluency. If any of these criteria are not met, it is recommended that your content be proofread by a mother tongue linguist.

4. Human revision

For sensitive, strategic or legal content, consider human revision to ensure accurate translations. Human, mother tongue reviewers can detect and correct errors that may have a significant impact on the meaning and intent of your content.

5. NMT Engine Training

You may want to consider training customized engines with your own sensitive data to improve translation accuracy. However, be sure to comply with data protection regulations and not disclose confidential information. So, here again, it is preferable to use a company specific solution or an SaaS solution via a professional. The latter will know how to ensure the security of your data, while providing you with training and maintaining your customized translation engines.

6. Awareness of cultural adaptation

Machine translations can be influenced by cultural or linguistic bias, contained in the corpus used in its training. An analysis of the training corpus by a computational linguist is therefore advisable. It will allow you to highlight possible biases or inconsistencies, but also to anonymize your corpus if necessary. The other way to counteract bias and inconsistency is to have a linguist check the machine’s output to ensure a proper and respectful translation.

7. Test and iterate

Perform regular testing to assess the quality of machine translations. If you find recurring problems or specific errors, make the necessary adjustments, whether by adding new sentences to the corpus, adding business terminology, etc. Here again, the computational linguists or terminologists of your language services partner will be valuable to you.

It is important to note that even with all these precautions, machine translation can have limitations and risks when it comes to sensitive content. Assessing your organization’s specific needs and making informed decisions are critical to protecting confidential information and ensuring translation quality.