Over the last two decades our industry has spent a lot of time and energy making the localization process increasingly more efficient. Dollars spent in the process are highly leveraged thanks to the application of translation memories and machine translation, together with sophisticated expert systems and static analysis tools that help ensure that quality can still be achieved at scale. Companies that release products internationally know how to write global-ready code and content, standards exist and are generally adhered to. Companies wishing to extend into international markets for the first time have a deep bench of partners and suppliers that they can rely on to get the job done. Localizing products is not always a trivial task but it is one that is well understood by a mature industry.
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On 15 March, the Imperial Riding School Renaissance Hotel in Vienna was transformed into a battlefield of ideas on new trends and topics related to translation automation during a TAUS Roundtable meeting. The Roundtable was organized around questions on the market viability of translation data, on innovative ways of measuring localization effectiveness and on machine translation quality.
* The title is borrowed from an article written by Bill Joy (then Chief Scientist at Sun Microsystems) and published in Wired Magazine in April 2000. (Why the future does not need us). This article was somewhat gloomy, giving us a warning about a future in which machines essentially dominate us, humans. “We must do more thinking up front if we are not to be (…) surprised and shocked by the consequences of our inventions.” Projecting this fundamental and existential problem on our own sector, the field of translation, could easily lead to depressing and devastating visions of the translation industry in the coming decades, and as a result put us – everyone working in this industry – in a defensive and reactive or inactive state of mind. What we much rather do is be realistic about it, have an open mind about both the upsides and the downsides. The future may not need us, but we certainly need a future.
Last year, I did some New Year's predictions in my post Wishing you an innovative 2015! reflecting on topics that would keep us awake in 2015. To continue writing on these expectations (calling them predictions might be too pretentious), making this a tradition, here is my two cents again on some of the new topics that will dominate this year’s blog posts and translation conferences. Last time, I talked about big data and business intelligence becoming the buzz words of the year. I also mentioned a new direction in the industry towards dynamic pricing based on quality and productivity results. And of course, translation quality will be a popular discussion topic everywhere you go. Just read on to see why...
The TAUS Annual Conference in Silicon Valley opened with a panel discussion about innovation led by Paula Shannon (Lionbridge) who skillfully introduced the concept of sustainable, disruptive and devastating innovation for her panel to discuss. Companies such as Airbnb and Uber were cited as examples of disruptive innovation and with the imminent TAUS Innovation Excellence Award to be given out, there was the distinct feeling that something new was about to happen.
The world can be overwhelming, so it’s tempting to try to make it smaller, more controllable. It’s the same with the world of localization. It’s overwhelming, so much content, so many languages. You would like to make it smaller, more manageable. I don’t want to make this a political debate, but I think we, localization professionals, know best that we cannot establish borders and keep them closed. The world is one. And in fact, if you think about it: our work is all about helping the world (and our customers) communicate better. Isn’t it great to work in a profession with such a noble ideology?
The translation industry is growing, but not fast enough! The amount of content published every day vastly exceeds the amount that can be translated by the few hundred thousand translators in today’s workforce. Machine translation seems to be a part of the solution, yet the world is still waiting for this technology to mature. How do we scale up the translation industry’s capacity for the massive potential opportunity?