Gabriel Fairman

Translators and Executives Need to Talk.

Last week, Bureau Works published some serious data about our context-sensitive translation technology. It was a rigorous study that evaluated over 4 million translated segments. Our engineering team works closely with our data scientists to produce good data that will be helpful in advancing our industry. They are scientists through and through, dissecting the data we collect for deep and nuanced insights.

I, on the other hand, am more of a data backhoe. I roll into a mine of potential information, scoop out a rough chunk, and see what I find inside. I do this by asking questions on LinkedIn. They are opinion questions, but opinions and emotions are their own type of data. They are data on where we are as a community, and they tell us what we need to develop in the relational part of the localization business.We often think about how to develop from a business perspective, a tech perspective, or a linguistic perspective, but asking people how they feel tells us where we need to develop from a human perspective. My type of data collection isn’t as refined as my team’s work, but it is useful. It is raw, straightforward, and it points straight at the conversations we need to have.

That is exactly what happened with my last LinkedIn poll.

What was the question?

Although the question is visible above, LinkedIn’s character limits on the polls mean that context is lost in the pursuit of concision. But, this question is supercharged with context, so it is important to clarify.

Basically, since the advent of Machine Translation there have been discussions about the value of post-editing. Translators correctly say that their expertise is still required to arrive at a quality translation, and that they are tapping into this expertise to review MT output.

On the other hand, business leaders are also correct when they recognize that post-editing is often (not always) less time-consuming and cognitively intense than translation. And, that much of the work that goes into post-editing is reading and confirming that the machine translation is correct. As machine translation improves across many languages, the number of edits a linguist is required to make continues to decrease. Business leaders also recognize, as any business leader would, that the price of MTPE is often lower than the price of translation. Right or wrong, that is what the market has done.

Source: https://go.proz.com/blog

Full article: https://go.proz.com/blog/bad-data-good-insights