How to Handle a General Fear of AI among Localization Specialists

It is now becoming clear that artificial intelligence (AI) is inescapable: it is used everywhere, including as part of translation workflow automation. Many translation companies are concerned that they will be forced out of the market, while a lot of freelance translators and client-side translation departments are wondering what their futures might look like.

A well-known industry research agency conducted a survey of translation market participants. It showed that they are all more focused on the possibility of being replaced by AI rather than economic issues or challenges associated with internal processes.

However, to understand the reality and success of AI in a translation company or client-side translation department, an assessment of technological capability and the extent of workflow automation is required, paying special attention to the document translation process.

Basic automation options may include:

• Translation memories (TMs) and translation management systems (TMS): translation memory bases and managing the translation process via a centralized system;
• Use of machine translation (MT) and MT post-editing (МТРЕ): use and customization of various machine translation engines; teaching specialists to work with post-MT texts;
• Automatic quality assurance (QA) checks: setting up customized profiles to identify translation issues.

Companies that already have these tools in place are using automation at a level sufficient to free up human resources from routine tasks, prevent human errors, speed up the translation process and reduce the associated costs.

But what is out there that goes beyond simple automation and is changing translation and localization as we know them today? AI has now emerged alongside proven tools, and is being used in the translation industry in a variety of ways, including:

• As a translation engine (however, it is not particularly good at this at the moment, though there are reasons to believe that it will “upgrade” quickly).
• As a translation tool for videos and all other multimedia content.
• As a content generator in multiple languages, including images.
• As a QA tool (AI is not yet entirely successful as a QA tool, as it fails to take many translation parameters into account, and may deviate significantly from the original during the editing process, which is important in a conventional understanding of translation, etc.).

However, there are two more aspects to translation automation and streamlining: collaboration between clients and the translation company via a platform and personal user accounts, and the implementation of AI directly in a TMS. These are advanced automation options that are unavailable to smaller translation companies, and this is why the clients with large-scale localization needs should seek out major providers who use cutting-edge technologies.

Email is becoming an increasingly outdated and time-consuming way to work: email chains containing comments and important instructions can be easily lost. It is certainly possible to store them in a client-side ERP, but the client is unable to see what exactly the vendor stores and how. Specialized platforms designed to make data exchange more transparent are available. Janus Worldwide uses the Global Technology Platform, which automates client-vendor interactions, displays all information related to orders, files, instructions and communications in every order, and allows clients to calculate translation costs themselves and monitor their budget (Purchase Order) and expenditure. By using this approach, we can get to work on client projects more quickly and minimize extra communications, thanks to an AI-based chat bot. As a result, clients save up to 30% of the time that would otherwise be spent on communicating with vendors, or up to eight working hours per month. For more details, see our article here: https://janusww.com/news/how-would-you-spend-8-hours-free-time-you-can-get-back-using-gtp/

The second advanced option for using AI to automate and speed up the localization process is to create a special AI plugin designed for use in a TMS. Using AI as a translation engine will not produce the necessary level of quality, but if the provider has employed specialists that can set up a TM to utilize AI with a list of parameters (special instructions, variation and model creativity settings), as we do, then the result will exceed expectations. Costs will be significantly reduced, the base AI quality will improve, and the time needed to translate some materials will decrease. For example, one successful example where this has worked for us was the use of such a plugin for projects completed for a client from the pharmaceutical industry, where we were able to work 35% faster while maintaining a high level of quality and significantly cutting production costs.

In conclusion, to answer the question posed at the top of this article, I’m certain that linguists will not be leaving the translation market over the next few years, but will continue to transform their knowledge and skills. They will oversee the training and development of AI, just as they previously learned to work with machine translation (from editing to training engines).

Localization specialists and translation companies should be actively integrating their solutions and technologies into the translation process and doing so consciously, with adequate preparation and testing before moving into real-world tasks, or contacting tech-savvy providers today. Tomorrow, it might be too late.