With his 1967 essay, “The Death of the Author,” theorist Roland Barthes dealt a hefty blow to the authoritarian grip authors had over literature. “Literature is that neuter, that composite, that oblique into which every subject escapes, the trap where all identity is lost, beginning with the very identity of the body that writes,” Barthes posits, effectively severing the once-unbreakable tie between author and work.
The modern translator faces a similar identity crisis. In the past decades—thanks to the advent and rise of artificial intelligence and machine translations—visionaries and technological prophets have been predicting the death of translators worldwide. We talk about one prominent visionary in another article: the Dutch language expert Jaap van der Meer, who equates the rise of artificial intelligence with the eradication of human translators. With all this talk of robots replacing humans, translators are on edge, fearing for their vocations as if, any minute now, they will hear news of the invention of a universal translation machine that will render them useless for good.
But as many readers realize, “The Death of the Author” wasn’t intended to oust authors from their tenured positions or undercut their role and prowess in any way. If anything, Barthes’ essay sheds light on the curious phenomenon of literary works taking on life after creation: a life beyond the author’s intentions. By severing the tie between writer and opus, Barthes gives a newfound purpose and power to authors; writers are no longer mere storytellers or transcribers of thoughts—rather, they are creators, like a deity, blowing life into soulless words.
The decades-long debate over whether human translators are necessary or obsolete can also be understood in a similar way. The notion of the death of the translator stems from a long discourse of machine translation, its rise to stardom, and seemingly infinite capabilities. As justified translators are in fear for their livelihoods, it’s one thing to understand machine translation developments as a threat and another to think of MT as a reformative piece of technology to enrich human translation.
The integration of machines in translation is a recent phenomenon. But as we speak, translators all over the world employ machine translations (or forms of it, such as computer-aided translation, postediting, etc.) to help with more accurate, more efficient translations. While thinkers and futurists might ramble on about singularity, perfect artificial intelligence, and human parity, translators are doing the hard work of incorporating new technology to aid in their human, lived experiences translating. While theorists preach the death of the translator, real human translators are already grappling with what it means to live in a hyper-technological world, negotiating for themselves a hybrid workplace alongside machines.
Such is the defense of human translation in a purely ideological discourse. One look at the real world presents an overwhelmingly positive view of the human translator. Here are some of the real-world current news in which human translation is necessary and important.
- Translators in Big Tech
Slator, the popular news source for all things related to the language industry, recently published an article with job openings at Silicon Valley companies—jobs for translators, linguists, and localization specialists. “Machine translation (MT) and adjacent language technologies are driving industry-wide demand for natural language processing (NLP) engineers and machine learning researchers. But that trend is not the whole story. The same companies are also aggressively hiring qualified linguists,” says Seyma Albarino, a staff writer for Slator.
According to Albarino, there is an empty vacuum between traditionally human roles (customer support, QA) and technical roles (MT, etc.) for roles regarding language and linguistics. Some of Albarino’s findings include:
- Apple: technical translator, localization and editorial producer
- Meta: language manager, market specialists
- Amazon: data linguist, product manager
- Google: search language specialist, market responsibility specialist
- Tencent: senior localization manager (regional), marketing operations manager (regional)
These are just a few of the numerous linguist and translator jobs available in Big Tech. Even Google, Amazon, and Meta—pioneers of the machine translation industry—still need and hire human translators and linguists, given the inaccuracy of machine translation.
- New University Programs in Translation
Last year, Yale University announced the inception of the Yale Translation Initiative, whose mission is “to promote the interdisciplinary study of translation at Yale and beyond, encompassing its literary, social, political, economic, legal, technological, and medical dimensions.” The initiative is for Yale undergraduates and Ph.D. candidates, who will be allowed to partake in projects, seminars, and courses to enrich their understanding of translation as a feasible, necessary skill. “Translation has become increasingly central to the workings of the contemporary world,” states its introduction; courses are offered in a wide range of subjects, from literary translation to machine translation.
- Video Streaming in a COVID-19 World
With so many people suffering from pandemic-induced isolation, video streaming has hit new highs in its popularity. Viewers can choose from a plethora of services (Netflix, Hulu, Disney Plus, HBO Max, etc.) depending on their tastes and celebrity crushes. The more global video streaming becomes, the bigger the demand for translation—especially subtitling and dubbing—gets.
Netflix, the most popular and well-known among its competitors, revealed their investments in subtitling and dubbing in their January 20, 2022 conference, as part of their presentation on Q4 2021. Gregory K. Peters, the COO and Chief Product Officer of Netflix, announced that Netflix has “subtitled 7 million run time minutes in ’21 and dubbed 5 million run time minutes.” What’s more, Netflix is learning “how to do that better and how to make that localization more compelling to our members.”
That is a step in the right direction, especially for Netflix, which has recently come under fire for their half-hearted, inaccurate subtitle translations for the South Korean hit TV series Squid Game. The errors, semantic in nature, stems from the translator’s decision to eliminate cultural nuance in favor of a more localized translation: a decision that, in this context, is deemed wrong, but one that a computer couldn’t possibly make given its current limitations.
This Netflix anecdote, however controversial, makes the important claim that translation is a deliberate, careful process consisting of minute, nuanced decisions. While certain translations are correct—and some are wrong—a process of deliberation is what makes human translation necessary and important. Machine translations couldn’t possibly accomplish such a feat; what is needed, then, is more monetary investment in content translation, so as to improve the quality of human translation. This leads us to the last point of this article: high-risk source texts.
- Translation in High-Risk Situations
A 2021 study by researchers at the Olive View-UCLA Medical Center and the Memorial Sloan Kettering Cancer Center tested the accuracy of Google Translate in medical text translations for seven commonly spoken languages. Their findings were not surprising; the authors report that “GT [Google Translate] for discharge instructions in the ED [Emergency Department] is inconsistent between languages and should not be relied on for patient instructions.” The study is of note mainly because medical translation never quite gets the attention it deserves; the authors note that “many hospitals have no mechanism for written translation,” and therefore “ED providers resort to the use of automated translation software, such as Google Translate (GT) for patient instructions.”
Translations in languages such as Spanish and Tagalog showed decent accuracy: Google Translate’s into-Spanish translation had a 94% accuracy rate, while Tagalog had a 90% accuracy. Korean and Chinese fared a bit worse, with 82.5% and 81.7% accuracy respectively. On the other end of the spectrum, Google’s Farsi translation received a 67.5% accuracy rate and Armenian, 55%. Of these mistranslations, some were capable of “potential harm,” up to 2% in Spanish and 8% in Chinese.
COVID-19 has brought these issues into the spotlight; linguistic and cultural differences have hindered medical treatment in many COVID-19 cases, as can be seen in this report by researchers at Lake Erie College of Osteopathic Medicine.
The necessity of human translators is not bound to these four particular fields, but these four points should be enough to firmly argue against the death of the translator. Translators are not dead; they are alive and critically needed in a number of industries, of which technology, literature, entertainment, and medicine are mere examples.
The discourse against translators is not just discouraging, but also harmful. In a tech-savvy move towards mechanization, companies have begun to rely on lazy machine translation and underfunded human translators to cut costs and time when, instead, translators should be nurtured, trained, and paid in full for their efforts at bridging gaps in communication. These are more important questions and issues to be considered, much more important than whether or not computers will replace translators in future.
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