The easiest job in the translation industry has to be the one disparaging machine translation (MT). As a former boss of mine would say when he saw such e-mails: “Those guys are not busy.”

A day doesn’t pass without some link being circulated my way, either on Twitter or e-mail, highlighting poor applications of machine translation. Some dismally poor translated output is shown (almost always the result of the use of a free online translation service) along with some subjective declaration about how using Google Translate, Bing Translator, and others, is dangerous to your brand’s reputation, will drive away your customers, and so on (translation: “I haven’t a clue about the potential or proper application of MT really, but I think my job is under threat or you must pay me to do it instead”).

Of course feeding text randomly into a free online MT engine will result in a less than perfect translation, at times by a very long shot indeed. Except, you can get equally dreadful results by giving poor quality information, with no context or glossary, to the wrong type of human translator too (and still pay for the privilege).

Such tiresome “MT be bad” examples have brought nothing new to the translation debate in two decades. And then, of course, there are times when these free online services do a very good job indeed. But those examples are rarely declared. Natch.

For those who do understand the potential and application of MT, they must counter all this stuff by the mass circulation of correct examples of MT output. Match every lazy, bad example with a better, applicable one. The role of information quality, of customization, and post-editing needs to be explained more. And, critically, the role of MT in alleviating information poverty too must be brought to the fore.

How many of the MT knockers out there are permanently offering translation services for free for high value, life-saving information in Asia or Africa?