Talking To Machines

Surely you do online banking and do your taxes with the help of software, but would you depend on artificial intelligence or ask a machine for financial advice?

What if you need an email written in Mongolian translated into English in a rush? Enter Google Translate or any other number of software solutions, powered by machine translation. In 2012, I spoke with Larry Adams, one of Narrative Science’s representatives at the time, about the main features of their program, which mines data to author a piece of writing that is indistinguishable from what a human writer would create. What drives the translation of large volumes of content is speed, not quality.

For the sake of argument, I’ll oversimplify the issue a little bit. There are large translation companies that operate in bulk and outsource language services to the cheapest providers, from India to Argentina. Other companies try to stay competitive by emphasizing quality, and then hire a more expensive professional workforce in developed countries. The downward push on translation costs continues. After all, translation is a necessary cost of doing business, like buying office supplies or ordering printer ink cartridges.

While American business owners recognize the need and advantages of addressing the translation of documentation for their products or services, it's hard for them to see the direct connection between higher sales and better-written translations. Hence, the advantages of quality translation are intangible ones, great concepts in an abstract world.

Companies with overseas offices trust their salespeople in their different geographies to check the accuracy of the translated documents. In-country reviews are an established quality control, but translation managers often face an uphill battle to perform these analyses according to quality translation standards because the reviews’ completion depends on the time and availability of the reviewers — the people who are in charge of selling and marketing the products. Their primary job is to market and sell, not to sit down and review translations, a task that is not a natural part of their role.

In the meantime, companies are offered a variety of technologies to automate most of the translation process: translation memories, terminology databases, automated quality controls, confirmed translations with the lock-out of changes (so that future translators or editors cannot modify them once approved), and, of course, machine translation.

As machine translation reaches new, more robust performance markers, a question insinuates itself: Will it be possible to completely automate the creative process of translation by sheer data mining and parsing of linguistic patterns in the corpus? Once the engine is properly customized, software solutions devised by companies like Narrative Science may make the high cost of writing standard sports news and financial articles a thing of the past. There seems to be a technological answer to our most pressing problems. Will translators be relegated to the minor role of editors, no more creators of original translations?

Machines and software, regardless of their level of automation, still operate in a GIGO fashion (garbage in, garbage out). The machine is no better than the operator that programmed it. Intuition, creativity, the right turn of phrase, the cumulative sound judgment that comes from years of writing experience cannot be automated. Your business uses sophisticated software and complex machines to churn out products and project sales. But, who do you turn to for sales, marketing or financial advice vital to your business? A machine? A software bot?

By: Mario Chávez