Abstract
When free and instant translation is available to many, this may paradoxically render translation ubiquitous and obsolete. Custom Neural Machine Translation (NMT) tools are available for those who need higher quality and more secure translation. The complex algorithms and voluminous training data mean that only larger language-service providers can meet specific standards, which increases oligopolistic market trends. There are a number of issues with NMT including the lack of accountability and increasing standardization/erasure of language(s), propagation of fake content, censorship. Recasting machine translation into an ecosystem of digital authority (Vitali-Rosati, On editorialization, structuring space and authority in the digital age, Institute of Network Cultures, 2018) and building on knowledge as a commons (Hesse and Ostrom, Understanding knowledge as a commons: From theory to practice, MIT Press, 2007), we may conceive of translation as a public utility rather than a commodity (Enriquez-Raido, IJoC, 10, 970–988, 2016).
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Notes
- 1.
There is a whole range of types of interactions between translators and machines: from human translation from scratch to various types of human-and-machine-generated translations (where human translators enlist Computer Aided Translation (CAT) tools to varying degrees), to Neural Machine Translation (NMT) here understood as the automated translation of texts with no post-editing. NMT technologies do rely on significant prior human work through the numerous translations gathered in corpora and the input of developers and engineers, but when a user enters his/her request for translation on NMT interfaces, the end result he or she gets is what the algorithm has computed. For the sake of simplicity we will use the phrase “traditional translation” or “human translation” to designate works of translation which have been produced and validated by humans. Free NMT in this article refers to the fully automated translations provided free of charge by online interfaces, billable NMT refers to the custom solutions offered by language service providers, and NMT to the type of technology.
- 2.
The French original is: La langue dans laquelle nous communiquons, ainsi que les institutions mettant en circulation les problèmes dont nous discutons collectivement, constituent en parallèle l’intelligibilité et la matérialité de notre monde, puisque nous orientons en grande partie nos actions matérielles en fonction de ce que nous croyons saisir des rapports de causalité.
- 3.
The French original is: L’enjeu premier des médias relève de la COMMUNICATION, c’est-à-dire de la coalescence d’une communauté autour de vibrations, d’affections et de préoccupations partagées, bien davantage que de l’INFORMATION, définie par la pertinence et la véracité des représentations de la réalité mises en circulation. Autrement dit: la fonction première des médias de masse serait moins à chercher dans notre attention à la réalité objectale que dans la synchronisation et l’alignement de nos attentions interindividuelles.
- 4.
The French original is: Trois grandes tendances poussent toutefois nos attentions vers des mouvements centripètes qui réduisent indûment la richesse et la diversité de nos expériences sensibles et intellectuelles: nos dynamiques affectives fortement régies par l’imitation, les effets d’alignement inhérents aux médias de masse et les algorithmes de recommandation qui régissent aujourd’hui notre accès à Internet.
- 5.
To be more specific some of those interfaces allow access to variants, but it requires the user to seek them actively and click or hover over specific segments. DeepL offers a number of quality variants at syntagm level, Google Translate only offers one or two rather simple variants at sentence level. If I enter “nos dynamiques affectives fortement régies par l’imitation” in DeepL and click on translate to English, the output is “our emotional dynamics that are strongly governed by imitation.” DeepL suggests “processes, patterns, drives” and five more terms to translate dynamics if one clicks on this word.
- 6.
European Council resolutions usually set out future work in a specific policy area. They have no legal effect but they can invite the Commission to make a proposal or take further action. European Union directives are legal acts which requires member states to achieve a particular result without dictating the means of achieving that result.
- 7.
All of the 50 research articles ranked as most relevant for the query “neural machine translation” on Google Scholar for the year 2017 were written by teams from Computer Departments and Engineering Faculties.
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Larsonneur, C. (2021). Neural Machine Translation: From Commodity to Commons?. In: Desjardins, R., Larsonneur, C., Lacour, P. (eds) When Translation Goes Digital. Palgrave Studies in Translating and Interpreting. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-51761-8_11
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