The core question
A Reddit user recently posed an intriguing question: why don’t tech giants like Google and OpenAI utilize AI for their internal translation needs, despite the potential cost savings and efficiency gains of machine translation post-editing (MTPE)? Both companies, known for their extensive use and development of AI, instead opt for human-only translations for consumer-facing materials.
Potential risks
The answer likely lies in the inherent risks associated with relying on AI for critical translations. While AI translation technology has made significant strides, it still struggles with nuances of language, cultural context, and the precise conveyance of meaning necessary for legally binding documents like contracts or safety-critical instructions. An AI might miss crucial details or introduce inaccuracies that could have significant legal or practical consequences. The cost savings of MTPE might be outweighed by the potential costs of errors.
Why it matters
The emphasis on human translation reflects a prioritization of quality and accuracy over cost efficiency, especially when dealing with documents that could impact users. Consumer trust is paramount, and inaccurate translations could lead to confusion, dissatisfaction, and even legal liability. Companies may deem the risk of errors too high to justify using AI, even with human post-editing.
The industry response
The user’s observation aligns with the broader experience of many freelance translators. The demand for high-quality, fully human translation remains strong among companies who understand the importance of clear, accurate communication. While MTPE has its place in certain contexts, for documents requiring utmost precision and clarity, human translation continues to be the preferred approach.
Future considerations
The ongoing advancement of AI translation technology might eventually change this dynamic. However, until AI can reliably handle the intricacies of language and context with the same level of accuracy and understanding as a skilled human translator, companies are likely to continue prioritizing human expertise, particularly for consumer-facing materials. The balance between cost and quality remains a key consideration in this evolving landscape.