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 107:
Will companies in the healthcare space adapt to machine translation for their localization needs? Or will they still prefer a full human translation process with certification?
Chat GPT’s Response:
The adoption of machine translation in the healthcare industry for localization needs depends on various factors, including the specific requirements of the content, regulatory considerations, and the preferences of the companies involved.
Machine translation has made significant advancements and can provide fast and cost-effective solutions for translating large volumes of text. In some cases, especially for less sensitive content like general information or non-regulatory materials, companies may choose to leverage machine translation to expedite the localization process.
However, the healthcare industry deals with highly sensitive and regulated information, such as patient records, medical documents, and regulatory submissions. In such cases, companies may prioritize the accuracy, confidentiality, and compliance of translations, and thus prefer a full human translation process with certification. Human translators are better equipped to understand the nuances of medical terminology, cultural differences, and the importance of maintaining precision in healthcare communication.
Regulatory requirements in the healthcare sector often mandate accurate and certified translations, adding another layer of complexity. Machine translations may not always meet the stringent standards required by regulatory bodies.
That said, there could be scenarios where a combination of machine translation and human review (post-editing) is employed to balance efficiency and accuracy. This approach allows for a quicker turnaround while ensuring that the final output meets the necessary quality standards.
In conclusion, the extent to which companies in the healthcare space will adapt to machine translation for localization depends on the specific context, content type, and regulatory considerations. Some may opt for a hybrid approach, leveraging both machine and human translation, while others may continue to prioritize full human translation for critical healthcare content.
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