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Language services today stand on the cusp of a disruptive transformation that will redefine how professional linguists work. This shift will come from the availability of ubiquitous artificial intelligence (AI) that extends their reach and capability and makes them far more efficient than they could otherwise be. CSA Research calls this new professional the “augmented translator.” Just as “augmented reality” uses AI to enrich individuals’ access to relevant information about their surroundings, this transformation provides linguists with more context and guidance for their projects. They work in a technology-rich environment that automatically processes many of the low-value tasks that consume an inordinate amount of their time and energy. It brings relevant information to their attention when needed. This computing power will help language professionals be more consistent, more responsive, and more productive, all the while allowing them to focus on the interesting parts of their jobs rather than on “translating like machines.” Until now language technology developers have focused their work on speeding up the process and lowering costs. Those drivers have left many translators feeling alienated from the very aspects of their work that attracted them to the job in the first place – the creativity of language, the challenge of solving difficult problems, and the ability to work on stimulating texts and topics. Translators often find that they spend as much time managing the technology as they do translating, and that their rates are always under pressure. The augmented translation model changes all this by assisting linguists when they need it and getting out of the way when they do not. Today we see bits and pieces of this new paradigm, but the outlines are coming into focus. What will this new model look like? We predict it will use the following technologies:
If this vision is to become a reality, the individual technology components will need to talk to each other and work and learn from the linguist. For example, an ACE system will query a terminology database to identify terms and suggest them. The MT system will interface with both to disambiguate text and use their suggestions. All of these will feed into the translation memory, which will increasingly merge with MT. The lights-out project management system will learn about different linguists, their schedules, and their strengths and weaknesses and route work to them based on an individually tailored profile. The advantage for linguists is that they will no longer be at the end of a chain with no influence on the process. Instead, they will control and work with all of this technology and become many times more productive. It will lower their cost per word even as it increases their value and effective hourly rate. It will relieve the tedium of translating repetitive variants of basic texts and help translators by more consistent and accurate. Such transformations have occurred in other sectors. For example, computerized bookkeeping eliminated the arithmetic aspect of accountants’ jobs in the 1980s – and thus freed them to focus on business planning and real-time financial analysis that is worth far more than merely tracking funds after the fact. So too, the next generation of augmented translators will eliminate routine low-value tasks that machines can handle perfectly well, and will instead focus on adding value and increasing the value of language for their clients. CSA Research finds that LSPs that embrace technology already grow more quickly than those that hold back and the emergence of augmented translation will only add to this advantage. This new way of working uses technologies that already exist in new combinations, rather than waiting for some pie-in-the-sky new AI developments. It does not replace language professionals, but instead gives them the tools and resources to deliver their best value and quality. The shift to augmented translation will not be painless, but because the technology shifts to a linguist-centered perspective, it will hold tremendous potential for those linguists who are willing to embrace the changing landscape of technology.
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