Artificial Intelligence, Machine Learning, and the Future-Proofed Translator: What I Learned from TAUS

With machine learning on the rise, most of us think that the need for skilled translators will decrease. That couldn’t be further from the truth.

Posted
September 23, 2019
Author
Tess Whitty
Category
Share this article

With machine learning on the rise, most of us think that the need for skilled translators will decrease. That couldn’t be further from the truth.

I was fortunate enough to be one of the 130 participants to attend the Translation Automation User Society (TAUS) Global Content Conference in June 2019 (and the only freelance translator). The two-day event was full of networking, knowledge sharing, and inspirational speeches.

The TAUS Global Content Conference focuses on big questions, including the progress of machine translation (MT) technology, whether human parity is possible, how machine learning (ML) will impact global communication, and what the rise of technology means for freelance translators.

What follows are my takeaways from the conference and how what I learned could affect translators around the world. For additional information, check out the footnotes for the 2019 conference.1

LESSON 1: NEURAL MACHINE TRANSLATION (NML) WILL FUNDAMENTALLY ALTER THE TRANSLATION PROCESS

Although we’ve had to deal with the rise of computer-assisted translation (CAT) and other early MT tools, most of these left the basic tenets of translation untouched. Jobs were still priced on a per-word basis and the translator was the only link between the source and final content. In short, the flowchart of a freelance translator’s tasks looked much the same as it did 20 or 30 years ago. Nowadays, though, that’s no longer the case. Here are a few ways that upcoming technologies will permanently alter the translation process:

  • Pricing on a per-word basis may no longer be practical. Instead, calculating rates and payments may work better using hourly fees or project-based fees.
  • For some jobs, you’re more likely to serve as a proofreader. While people might not be willing to pay a high-end translator to do the grunt work, they’re still open to bringing you on for an editing role.
  • Your next project manager might be an algorithm. With automatically generated content, where deadlines and algorithms drive decisions, the need for dedicated project managers will shrink. The data generated from algorithms will then be used to drive recruitment, predict market readiness, and determine translation needs. In other words, a computer could be your boss one day.
  • Multimedia translation is the future. With voice recognition and augmented reality on the rise, the need for translators willing to adapt to these new technologies will increase. Translators who are willing to embrace these different platforms, including the voice-assisted search for online queries, will benefit.

LESSON 2: THE PROPER APPLICATION OF MT AND ARTIFICIAL INTELLIGENCE IN YOUR WORKFLOW CAN SET YOU APART FROM THE COMPETITION

As language specialists, we tend to think of MT and artificial intelligence (AI) as the monsters under the bed. But if we’re willing to embrace these monsters, we can use them to our advantage. Having an efficient MT tool on hand can help cut costs and drastically increase our production ability, at least if we know how and when to use it.

LESSON 3: FIND YOUR NICHE TO FUTURE-PROOF YOUR BUSINESS

John Tinsley, chief executive officer of Iconic Translation Machines and an expert in the MT field, opened his session with a startling statistic: “99% of today’s global content is translated by MT without any human intervention.” Hearing numbers like that are enough to leave most translators waking up in a cold sweat, but I’m not one of them. My research shows that there’s plenty of room for both machine and human translators in the marketplace. In fact, the Bureau of Labor Statistics estimates that the employment outlook for translators and interpreters will increase 29% by 2024.2 Of course, many of you are probably wondering what you can do to ensure that you are positioned for growth.

Generalists and low-quality content mills will be the main casualties in this battle of man versus machine. To succeed in the future, you’ll need to specialize in a field that values accuracy and creativity over speed and volume. Examples of these fields include medical oncology research, renewable energy development, and automotive patent law, as well as more creative fields such as marketing. Transcreation, because of their ability to merge copywriting with nuance and emotion, will also be well-positioned against the rising tide of automation.

There is also a new field of specialization that merits your attention. International companies are hungry for freelance translators with experience in digital marketing and social media. They need people who understand local search marketing and can adjust their messaging to meet the needs of customers and search engines alike. Even if an oncology degree is out of reach, the internet is awash with knowledge about customer service, search engine optimization, and social media management.

LESSON 4: THERE’S A NEW TRANSLATION BUSINESS MODEL ON THE RISE

Up until a few years ago, there were two prominent business models translators followed: they either collaborated directly with clients or worked for language services providers. Many freelance translators make a living straddling the line between the two. These two ways of working demand different technologies, processes, and timelines. Now, many translators will be forced to contend with a third translation model: crowdsourcing.

In this model, popularized by platforms such as Smartcat and Gengo, end clients plug their content into a virtual translator community. The platform then automates job management on both sides. By removing the geographical barriers between the translator and the end client, the crowdsourcing model opens the market to lower-cost providers in markets where the cost of living is much lower. These lower costs will ultimately hurt those language services providers stuck in the middle. This new business model gives you even more reason to specialize and find your niche.

LESSON 5: MACHINE LEARNING IS CREATING NEW ROLES FOR TRANSLATORS

If generalists and low-quality translators will lose their place in the market, then new, more specialized people will take their place. In the next few years we expect to see a sharp increase in the demand for:

  • Post-Editors of MT: While some companies don’t mind machines doing the lion’s share, they’re skittish about releasing raw MT content into the market. Therefore, they’ll want someone to read over the outputted text for mistakes. The corrections will then be fed back into the data pipeline to further improve the machine’s output. This is a possible field for translators willing to take it on, which could even create a new type of translator.
  • Transcreators: Machines still struggle to combine culture, language, and emotion into a creative and compelling text. To get that done right, you need a human. Machines also have a difficult time understanding cultural nuances, emotions, and the psychology involved in proper translation, all of which are vital to sales and marketing. For that reason, transcreators should weather the digital transformation just fine.
  • Spoken Content Specialists: Audio is being hyped as the new communication platform. Over time, text interfaces are being replaced with voice-powered assistants like Google Home, Alexa, and Siri. Podcasts are also growing in popularity. This shift to audio requires a different sort of translator. Those who work in this field must find ways to convey the importance of social, gender, and emotive markers in the work they produce. They must also be prepared to work with speakers of various dialects to create more localized, regionalized content.
  • Brand Ambassadors: With more of the world coming online, globalized branding is becoming increasingly important. Worldwide retailers will need help ensuring that their company’s values and beliefs are effectively communicated across geographical borders. This will require translators who are willing to act as product testers and advise companies on how best to adjust their products to meet the needs of their target markets.
  • Local Storytellers: Good marketing is built around good narratives. Simply translating these stories into a target language rarely has the desired impact that companies want. That’s why these groups are looking for people who know how to craft a good tale. This is a perfect role for translators who dream of a career as a creative writer. With the demand for personalization growing, the need for this type of work will only increase.
  • Conversational Agent Consultants: Like it or not, chatbots are here to stay. While much of their development has happened in English-speaking countries, they’re now being deployed in markets all around the world. Still, these “conversational agents” need a human to help fine-tune and perfect them. People in this position will need a good understanding of human psychology, machine logic, and customer service to succeed.

LESSON 6: MACHINE LEARNING WILL GIVE YOU INSIGHT INTO YOUR WORK

Translators, as connected professionals, will eventually benefit from the datafication of their work. The rise of algorithm and MT will make it easier for us to analyze our work habits, performance levels, and productivity. Eventually, ML could allow us to build a data narrative of our past choices and spell check preferences. It could then use that data to make suggestions to improve the overall quality of our work. With this data at our fingertips, we’ll also have a new way to quantify our value to clients and potential employers.

LESSON 7: TRADITIONAL TRAINING ISN’T ENOUGH

Academic training for translators usually consists of two things: translation theory and practical translation. The latter tends to focus on CAT tools and general customer service. The former focuses more on ethics, linguistics, and sociology. The topic of MT is barely more than a footnote in these areas. The curriculum rarely makes room for the advanced algorithmic knowledge, specialized skill sets, and advanced information technology tools required for the future. Until more universities adapt to this, new translators will have to turn to industry mentors and less traditional sources to help prepare them for the future of the industry.

LESSON 8: WE NEED TO STOP BEING AFRAID OF MT AND STEP UP TO HELP SHAPE IT

Machine translation tools are often built by software engineers with little to no knowledge of the industry itself. This often results in tools that are clunky, complicated, and poorly designed for the translation process. But just like we did with bilingual print dictionaries and translation memories, we have a chance to change that. We can reach out to designers and engineers and provide our insights to help bring about needed change that will enhance the efficiency of these tools in our work. Or perhaps we can join a group or become guinea pigs for the next generation of tools coming down the pipeline. Whatever you do, don’t let the advent of ML leave you voiceless. Do everything you can to make sure that the end product you use is well suited to your work.

LESSON 9: THE NEED FOR GLOBALIZED CONTENT HAS NEVER BEEN GREATER

With ML on the rise, most of us think that the need for skilled translators will decrease, but that couldn’t be further from the truth. As large population centers become increasingly digitized, there’s now an insatiable need for translators willing to work in those markets. Furthermore, with all that big data flying around, there’s a huge need for people to translate and make decisions across cultural lines. In short, while machines will take away a lot of the grunt work, freelance translators will be given more opportunities to make a difference.

WHERE DOES THIS LEAVE US?

Based on what I learned from TAUS, translators need to up their game, focus on niche markets, use MT as a tool to boost productivity and provide ancillary services, and consider adjusting their business models or pricing schemes to keep their use of MT profitable.

Attending TAUS was an eye-opening experience, being the “linguist” among technology companies. I not only learned a lot about the present state of the industry, but also gained many insights into what’s coming. If we specialize and use our human powers to our advantage, we have no reason to fear MT and its associated impact.

Notes
  1. TAUS Global Content Conference, http://bit.ly/TAUS-2019.
  2. Occupational Outlook Handbook (Bureau of Labor Statistics), http://bit.ly/TI-job-growth.

Tess Whitty is an English>Swedish freelance translator specializing in corporate communications, software, and information technology. She has an M.Sc. in economics and an MA in marketing and worked previously as a marketing manager. She shares her knowledge and experience in marketing and business as a speaker, trainer, consultant, author, and podcaster. Contact: tess@swedishtranslationservices.com.


Source: www.ata-chronicle.online

Leave a Reply

Your email address will not be published. Required fields are marked *