TECHNOLOGY

Some 20-odd years ago, Annette Hemera — now at Anzu Global — started working in the language industry. At the time, folks in the industry were witnessing the painful and troublesome birth of new technologies: computer-aided translation, translation memories, automatized terminology management, and the growth of machine translation (MT). Back then the language industry arena was loud and heated with frustrated and doubtful discussions about decreasing translator fees, shrinking vendor margins, and client complaints of declining quality. Coffee breaks were spent reading and commenting on those outrageous stories of faulty translations and poor global marketing — remember “Chevy no va?”

But no one could have anticipated what was coming. We have been going through a new-age version of the Industrial Revolution.

Alex Yanishevsky, an MT expert with 20 years under his belt, likens the growth of artificial intelligence (AI) to the invention of the Gutenberg printing press. Likewise, Jay Marciano, who has been involved in MT since 1998, once wrote in an article for this magazine (back when it was still Multilingual Computing), that the impact of AI is comparable to the impact of sound on the silent picture industry. It is disruptive and creating many new career opportunities.

AI in the globalization industry is here to stay. What should language owners and personnel do? Well, when everyone else is doing it, it might be time for you to start doing it too. This article will discuss many of the AI technologies applied to the language industry and the related career paths and opportunities for people in or entering the globalization space.

Let’s take a step back for a second: What even is AI? AI is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition, and machine vision. Machine tasks very often include intellectual processes like learning from past experiences (machine learning), generalizing, and reasoning. You can classify artificial systems into artificial narrow intelligence, artificial general intelligence, and artificial super intelligence.

Where do AI and the language industry overlap? More like, “Where don’t they?”

AI is predicted to power 95% of global customer interactions by 2025. Our knowledge is encoded in language, Marciano says. For a machine to be intelligent, it must understand languages. Natural language processing (NLP) has been a huge part of AI since the beginning, he points out. MT is a subset of NLP.

With the integration of MT and AI, all the roles in the translation/localization process are impacted. Translators/editors are interfacing with computer output and doing post-editing. Localization project and program managers manage the workflow and integrate the data. Localization (L10n) and internationalization (I18n) QA engineers can use AI technology to better identify bugs.

Another more recent development in the AI and language industry is multilingual data creation. Companies that collect, curate, and maintain multilingual data to improve machine learning (ML) and AI frameworks. This linguistic data can be used for call centers, hospitals, chat boxes, doctors’ offices. Data service providers include Appen, Scale AI, E2f, GlobalMe, WeLocalize, Cloudfactory, and Telus.

Multiple careers are created with the growth of multilingual data creation, says Matt Grotenstein, CEO of Performance Localization. Data service providers need large numbers of bilingual people to annotate the data. They need program managers to oversee the bilingual data collectors and streamline the process. They need senior salespeople to sell the curated multilingual data to companies like Apple, Microsoft, Amazon, Facebook, and Google.

AI is also used in the interpreting field: multilingual text-to-speech and speech-to-text applications. A teacher, nurse, or lawyer speaks in one language and live transcription can be read simultaneously in multiple languages. AI is also used with the deaf and hard of hearing. Vannessa LeBoss, who works at AvodahMed, explains they have an AI software used for doctor patient visits to transcribe, dictate, and highlight conversations between deaf and hard of hearing patients and doctors.

With virtual assistant technology and the global rollout of products like Amazon Alexa, Google Assistant, Apple Siri, Microsoft Cortana, and Samsung Bixby, bilingual computational linguists are needed to write the dialogs, scripts, and answers to queries.

And of course, there’s the new free AI chatbot, ChatGPT, which writes articles in English using AI technology. To expand globally, a host of globalization personnel will be required.

Careers and training

If you are interested in being part of the language industry and this AI revolution, where do you go?

Olga Beregovaya, the VP of AI and MT at Smartling, and one of the experts and visionaries in the field writes the following:

“I am often asked what I would recommend to young people who want to choose a language professional career and what skills I’d deem most important. To me, it is all about engaging with AI. If you want to be a translator — study NLP, be very well-versed in comparative linguistics, most definitely know how to both post-edit MT output and be very familiar with language models and the requirements for the underlying datasets. If you are thinking of being more on the operations side — most definitely data analysis, reporting, strong understanding of how AI classification and predictions work, so you can design your programs and projects taking most advantage of data analysis performed by the machine, and you — being the data analyst person making decisions based on the AI analysis.”

Alex Yanishevsky suggests you can divide the career paths into “hard” and “soft” skills. If you want to enter the field and are a programmer or have strong technical skills, then get a degree in computer science with a minor in linguistics. Or, get a degree in computational linguistics. There are programs at Harvard or MIT to get a certificate in data analytics or data science. Go to www.Coursera.org and search for degrees or certificates in ML, data science, data analytics, computational linguistics. Simplilearn offers online bootcamp for digital skills training and has several courses on AI.

For those of us already in the globalization field, take on new tasks involving AI technology: work on MT projects, oversee data creation plans, work with speech-to-text technologies. Audit a course in AI to fine tune your knowledge. Your interest, efforts, and experience with global AI technologies will increase your value and expand your global career opportunities.

AI has strongly influenced the globalization industry. The impact will only grow. There are many opportunities within the language industry and AI — help yourself.

Here is a partial list of careers in AI/Language Industry for programmers or bilingual people with technical skills/scripting languages:

• Natural Language Processing Engineering in many different languages
• AI/ML – Machine Learning Engineer
• AI/ML Computer Vision Engineer
• AI/ML Data Engineer
• AI/ML Software Engineer
• Applied Machine Learning Lead
• Cloud Architect
• AI Data Scientist, Natural Language Processing
• Senior Applied Scientist, Human
• Language Technology
• Bilingual Computational Linguist

If your strength and interest is with the ‘soft’ skills of languages, management, Jay Marciano mentions:

• Language Technology Analyst
• Language Process Analyst
• Machine Learning Supervisor
• Machine Learning Evaluator
• Translation Quality Assessor