Machine translation vs Human translation

Machine simultaneous translation vs human translation: The undeniable differences

As Artificial Intelligence continues to evolve, speech-to-speech technologies offering machine simultaneous translations have been born, promising both speed, cost-effectiveness and high ROI for companies implementing them. However, it remains clear that AI-based simultaneous interpreting will never be able to replicate the cultural knowledge, in-depth understanding of languages, local information and expertise of human interpreters.

Human conference interpreting can be defined as the simultaneous or consecutive real-time translation done by a human conference interpreter of an original speech into a target language providing in-person or online audiences with the ability to understand the original message in their native language.

While it is clear that human translators cannot replicate some of the things that machine translation tools are capable of doing (like working 24×7 without a salary and a night’s sleep), there are some factors that clearly demonstrate that human translation is more reliable and still the only option in many situations:

• Human translators are naturally more capable, especially when it comes to dealing with complex content that implies understanding specialized vocabulary, speeds, accents, intonations, body language, irony, humor, sarcasm… and a deep understanding in complex and highly-specialized fields like medicine or law.
• They are more careful with the vocabulary and terminology used by taking cultural and language nuances into account. A machine does neither understand nor think or correct itself.
• They can ensure the respect of confidential information. Cloud-based speech-to-speech technologies say they respect confidentiality, but how can LSPs and end-clients really find out whether their data is being stored somewhere, shared with third-parties or misused now or in 3 years’ time? Again, do we have the certainty that these companies do not use our data to feed their algorithms in order to improve their language models?

Machines lack humanity. In our Western fast-paced and highly-technological societies, the human touch matters, even more so.

• AI-based subtitling and simultaneous translation technologies are not, by far, reliable enough. These technologies are not mature enough to penetrate all markets. Companies marketing them are really eager to surf the wave of tech pioneers. This is licit. What it’s not, is promising fake El Dorados. Clients should test them properly before compromising effective communication or, even worse, losing prestige in front of their clients. AI hallucinations create outputs that are nonsensical or altogether inaccurate.

It is nonetheless possible to combine both AI-based translation tools and human translation. This is something that professional interpreters, professional associations and LSPs have been doing lately, in order to understand and make the most of these recent advancements in technology, which can result in more efficiency and productivity for everybody.

Should you wish to test these technologies, contact us!