Pages: 18

This introductory chapter establishes the framework for the handbook, outlining its key motivations, aims, epistemological leanings, (meta)theoretical underpinnings, and conceptual constellations. A special focus is placed on how AI-driven language and translation technologies are moving toward a quasi-independent machinic agency within contemporary multilingual societies. Tools like neural machine translation and generative multilingual AI challenge conventional conceptions of translation as a solely human-centred practice. This chapter describes these tools’ dual role as socially constructed and socially constructing agents, while also considering their evolution towards increasingly human-machinic entanglements in the global knowledge economy. Highlighting the ontological, epistemological, and axiological dimensions of sociotechnical translation research, the chapter critiques the commodification of language and the exploitative dynamics within modern digital ecosystems. Large language models (LLMs) and AI-driven translation tools need to be reframed as increasingly interdependent and autonomous machinic agents, which calls for an integrated critical posthumanist perspective that decisively transcends simplistic binary distinctions between humans and machines. Addressing these tools’ ecological and societal challenges and benefits, the chapter advocates for engaged interdisciplinary, sociotechnical, and empirical approaches for translation technology research. This contribution, ultimately, proposes a more outspoken, ethically grounded trajectory for a nascent sociology of translation technology, envisioning a future aligned with ecologically sustainable and socially equitable values and practices.

Pages: 94

No chapter abstract available.

Pages: 15

This chapter critically surveys the intersection of translation technologies and digital capitalism, painting with a deliberately broad brush to place the discussion in the wider context of ideological and socioeconomic shifts. It provides a holistic critique of the wider ethical and environmental implications wrought by industrial extractivism and technological automation. The chapter highlights the pervasive commodification of language and translation in the global digital economy, emphasising the ideological undercurrents of instrumental reason, technological determinism, and data colonialism. The argument draws on insights from political economy and interrogates the exploitative dynamics underpinning the translation industry, with a focus on algorithmic governance and the platformisation of translation labour. By connecting the digitisation of (crowdsourced) translation workflows to broader ideological, political, and socioeconomic trends, it challenges prevailing neoliberal and profit-driven paradigms, advocating for a transformative rethinking of translation technologies as common goods that are embedded in collectively shared and ecologically sustainable practices. The chapter envisions an alternative trajectory for the translation profession within a globally inclusive and cooperative digital multitude. This contribution, ultimately, underscores the need to reframe translation technologies as potential catalysts for ethically sound, sustainable, and equitable transcultural mediation in a rapidly digitising, increasingly interconnected, and arguably “posthumanist” world.

Pages: 17

This chapter addresses the transformation of the economic value of translation caused by the growing influence of business strategies that explore the full potential of emerging technologies. It explores economic theories of value with a special emphasis on how digital technology has not only altered production processes but also reshaped perceptions of labour’s contribution to the economy. Theories such as “heteromation” illustrate how the digitalisation of production, under advanced capitalism, has contributed to a global reduction – and potentially even the destruction – of the value of human labour. By applying the theory of “heteromation” to professional translation, the chapter seeks to elucidate the economic and discursive factors underlying the diminishing economic value of translation. It also considers the implications of these value frameworks for current and future research in translation studies. Concluding with a reflection on the opportunities presented by the new wave of technology, the chapter underscores the potential to preserve and enhance both the social and economic value of translation.

Pages: 13

This chapter investigates how language and translation have been represented from the 1950s to 2024 in the field of artificial intelligence (AI), in particular, through various contexts, personalities, and narratives associated with AI. Having emerged from Cold War cryptography, in which language was seen as a code, AI has now evolved to serve the profit-driven surveillance of online exchanges, in which language is seen as a resource and commodity. Public debate in the 2020s is polarised between a messianic interpretation of language technology and warnings about the risks of using AI. Retracing this history unveils the underlying assumptions and explicit goals of AI-powered translation algorithms, which differ fundamentally from human translation, as they have been designed to deal with standardised information, leaving out vast swathes of the human linguistic experience.

Pages: 20

Historically, the ways in which languages and their speakers are positioned and perceived in terms of their value in relation to one another are shaped by factors that are not simply linguistic but intricately linked to and locally and globally interwoven with social, cultural, political, and economic spheres. The minoritisation of many languages continues to occur today, affecting which digital technologies and translation technologies are accessible to them for use, and the extent to which their speakers participate in the conversations of the digital age, be it in their mother tongue or in translation. The chapter considers how the neoliberal capitalist markets and ideologies that are guiding the development and evolution of ICTs, translation technologies, and the internet have led to the commodification of languages and cultures, digital divides, and asymmetrical flows of information and knowledge in translation. In a rapidly evolving digital world that confers high value on online presence, and with translation markets increasingly engaged in competing AI technologies and devices for global communication, how can we imagine a more equitable and sustainable multilingual future in and for translation? The recent generative AI and machine translation technologies integrated within popular user apps and platforms around the world mean that translation technologies have a role to play more than ever before.

Pages: 14

Disruptive technologies such as artificial intelligence (AI) shape new modes of communication and translation. This chapter analyses the impact of generative AI in translation from a cyberfeminist perspective, investigating the hegemonic dimensions of technology. AI technologies reinforce patriarchal and racist logic inherent in Western conceptions of progress, which practices of translational resistance challenge. The chapter applies cyberfeminist theory to examine the limitations and risks but also the potential of AI language technologies in translation. The violence in AI’s “machinic” epistemologies causes material and psychological harm for marginalised groups, alongside significant environmental exploitation. Applying cyberfeminist principles can challenge these hegemonic tendencies by exposing the limitations of translational neural machines. Furthermore, the chapter proposes a critical posthumanist deconstruction of technologised discourse, applying cyborg logic to disrupt hegemonic narratives and established power structures. This allows for a critical, yet affirmative discourse about translation technologies and their impact on society and marginalised perspectives.

Pages: 13

This chapter introduces the concepts of Critical Theory of Technology (CTT) and Critical Theory of Translation Technology (C3T), providing an overview of their relevance to both translation studies and the translation industry. It explores the impact of digital technologies such as computer-assisted translation (CAT) tools, machine translation (MT), and large language models (LLMs) on the practices and roles of translators, managers, and other industry stakeholders. The chapter applies CTT, especially Andrew Feenberg’s ideas, to challenge the perception of technology as neutral, emphasising its deep entanglement with social, political, and economic structures. Through C3T, critical issues like de-skilling, professional alienation, and the commodification of translation practices, advocating for a human-centred design and ethical considerations in technology development are addressed. The chapter also engages with posthumanist perspectives, questioning whether the integration of AI risks undermining the cognitive and communicative uniqueness of human translation. The chapter offers a balanced view, suggesting that technological advancements should enhance rather than replace human expertise, and calls for a reorientation that places human values at the centre of translation practice and theory.

Pages: 78

No chapter abstract available.

Pages: 12

Technology is often seen as apolitical or politically neutral in modern societies since it can be employed both for progressive and regressive aims. An important number of philosophers and sociologists have challenged this vision, claiming that technology cannot be disentangled from politics. After a brief discussion of various ways in which technology needs to be seen as political, this chapter addresses the political relationship between translation and technology through two pairs of oppositions: ‘inclusion’ versus ‘exclusion’ and ‘commoning’ versus ‘dispossession’. The chapter pays attention to instances in which translation and technology unite for beneficial purposes through the inclusion of less-favoured individuals and the generation of new commons (i.e., shared resources) and collectives. Then, it discusses examples in which technology has a negative impact that leads to the exclusion of collectives and to the dispossession of individuals and groups. Through these conceptual lenses, the chapter shows that the interaction of translation and politics is always politically complex, as positive and negative consequences do not necessarily exclude each other; in fact, they can occasionally overlap and intermingle.

Pages: 15

This chapter explores the intersection of knowledge commons and cooperative models of translation within the context of cognitive capitalism, highlighting their underexplored significance in the industries of translation. It conceptualises translation as a critical element of the “knowledge commons”, where translation workers are seen as “knowledge workers” engaged in cognitive, communal and intellectual labour. Grounded in Marxian theoretical frameworks, the chapter discusses how translation cooperatives, as an alternative to privately owned, profit-driven and exploitative companies, offer a model centred on collective production, democratic decision-making and shared ownership. These cooperatives not only seek to improve the working conditions of translators but also advance a fair and sustainable approach to translation as a commons-based activity. The chapter reviews the governance structures of translation cooperatives, their collaborative decision-making processes and their strategies for balancing the needs of translation workers with those of the broader community. By underlining the transformative potential of cooperative models, the chapter suggests that these institutional frameworks can help create a fairer and more sustainable translation economy globally, offering insights for rethinking work and compensation in knowledge-driven industries.

Pages: 11

The digital revolution has ushered in unprecedented global connectivity, transforming business models and media content creation. This chapter discusses online collaborative translation (OCT) against the backdrop of critical debates in platform studies, addressing three key objectives: the concept of OCT, its position in the platform society, and its socio-economic ramifications. It proposes OCT as the top-level concept to encapsulate varied forms of digital translation practices (ranging from crowdsourcing to emerging practices like danmu subtitling), owing to its neutrality and inclusivity. In this chapter, OCT is conceptualised along five dimensions: platform nature, engagement pathway, initiation approach, agents involved, and translation modality. This chapter also discusses the important role that translation plays in platform evolution, design, and workflow development, contributing to the phenomenon of platformisation. Additionally, it highlights concerns about translator exploitation as digital labourers by profit-driven platforms. In an era where data is considered the “new oil” and neo-Taylorism prioritises productivity, quantity, and speed, there is a pressing need to address some unsustainable practices in OCT and translation at large.

Pages: 14

Digital translation policies emerge from the tension between technological upheaval and the inherent sociolinguistic complexity of our globalized societies. In this context, societies are actively involved in various policymaking efforts related to digitalization and communication technology, which also have implications for the field of digital translation. This chapter approaches the question of digital translation (and interpreting) policy from a multidisciplinary perspective, establishing connections among translation and interpreting studies, language policy studies, and social studies of science and technology. The chapter, firstly, elaborates a conceptual framework around the notion of digital translation policy considered as a dynamic social and ideological process that aims to define goals, prescribe courses of action, and routinise decision-making regarding the interaction between humans and specific technologies used in translation and interpreting. Using the public service sector as an example, it outlines, secondly, key issues in the field of digital translation policy, focusing on themes such as digital sovereignty and language technology, data governance and machine translation, human oversight of communicative artificial intelligence systems, as well as responsibility and risk. Finally, it focusses on emerging critical aspects that will rise in importance in the future, particularly the relationship between multilingual artificial communication and the commodification of language.

Pages: 12

Local governments play a pivotal role in delivering information to residents with diverse linguistic backgrounds. To meet the need for multilingual information provision, local governments have implemented machine translation (MT) in various communication scenarios, such as translating municipal websites and offering multilingual consultation services to residents. This chapter provides an overview of the circumstances and challenges associated with local governments’ use of MT, as highlighted by individual studies and practices. It outlines possible solutions to the issue of MT quality through techno-translational intervention methods, which include pre-editing, post-editing, and MT adaptation. The chapter also examines the societal impact of MT. Based on the framework of translation policy, it focuses on how the growing use of MT technologies can alter translation management, practices, and beliefs. MT technologies have prompted the reconsideration of translation management in local governments – for example, concerning decisions on languages to be supported, the volume of information to be translated – and have reshaped the translation practices and beliefs of municipal staff and residents. The chapter also provides an outlook on the future, focusing on an enhanced use of MT, including user-centric evaluation and controlled authoring of source documents.

Pages: 12

Translation technology tools play a pivotal role in overcoming linguistic and other communication-related obstacles in different types of crises. Drawing on real-life examples, the chapter explores translation technology as an agency-enabling solution that facilitates access to instant, accessible information. The complex interaction between translation tools, human actors, and society is mapped through the lenses of sociological theories of agency. The chapter highlights how the development and deployment of such technologies can affect both crisis preparedness and containment, frequently amplifying the voices of governments and technology providers at the expense of those directly affected. To establish inclusive, technology-enabled communication, the chapter offers recommendations for contextually relevant crisis policies and management strategies, advocating for adaptable approaches and positioning human translators as safeguards against overreliance on AI tools. It also underlines the need for transparent, trustworthy communication channels and balancing sociocultural factors and power dynamics, ensuring that crisis communication is inclusive and people-centred.

Pages: 68

No chapter abstract available.

Pages: 13

This chapter explores the histories, the intersections, and the futures of Translation Studies (TS) and Digital Humanities (DH). Over the past two decades, DH has developed a dual paradigm: employing digital methods to advance humanities research and applying humanities theories to analyse digital media and culture. Translation, once central to this endeavour, gradually faded from the DH landscape, overshadowed by broader paradigms like linguistics and literature, and by a pervasive monolingual bias. In recent years, DH has evolved into a complex, transdisciplinary field that aims for both global reach and linguistic diversity. At the same time, TS has begun integrating digital methodologies, reflecting a growing synergy with DH. This contribution examines the history of DH, its relevance to translation scholars, and the potential for translation studies to enhance the multilingual and global dimensions of DH. It advocates for a more inclusive digital scholarship that expands language representation and fosters global collaboration as well as for a translation scholarship aligned to the hybrid practices, media, and modalities of the digital age.

Pages: 13

This article examines the significance of the distinction between human (HT) and machine translation (MT) for the history and historiography of Translation Studies (TS). It argues that this distinction has not only been relevant for TS during the last couple of years in which MT effectively has become a permanent feature of our daily digital infrastructure of communication. Rather, the distinction between HT and MT permeates the history of TS since its disciplinary inception after World War II. The chapter claims that the human/machine distinction can be understood as an unacknowledged Leitdifferenz in the history of TS – a guiding distinction constitutive of the disciplines self-understanding, object and aims. By differentiating between “transhumanist” and “humanist” forms of the distinction between HT and MT, this contribution traces how this Leitdifferenz has impacted TS, not only during its early, linguistic years but also after the cultural turn. The chapter proposes an alternative genealogy of TS which questions the established disciplinary narrative of emancipation and progress. The benefit of this genealogy consists in shedding light on overlooked aspects inherent in this narrative. The chapter closes with thoughts about a possible posthumanist form of the distinction between HT and MT.

Pages: 15

This chapter addresses the question: “What is translation when performed by a machine?” While Translation Studies (TS) has decades of expertise in conceptualising translation, defining the concept within machine translation (MT) research and development remains challenging. This contribution traces the evolution of translation concepts in TS, examining the discipline’s theoretical “turns” and comparing them to the translation notions embedded in different MT models, from rule-based to neural. As these models have evolved, MT has become a ubiquitous part of daily life, integrated into web browsers, smartphone apps, and social media, subtly shaping public perception to view translation as a simple, automated process not requiring human insight. By offering translation as an easily accessible, often free service, MT risks devaluing the cultural and economic value of human translation. TS can counter this trend by promoting inclusive, precise, and adaptive conceptualisations that emphasise the societal importance of human translation in transcultural communication and global knowledge exchange. Such an approach not only educates the public on the cultural and societal value of translation in general but also raises awareness of the respective strengths and limitations of various forms of translation, be it human, machine, or hybrid.

Pages: 12

This chapter challenges the uncritical adoption of proprietary translation technologies in translator training institutions, arguing that it perpetuates hegemonic views of technology and undermines the principles of autonomy, openness, and social responsibility. Departing from Bertolt Brecht’s concept of the moral responsibilities of scientists, it critiques the dominant business paradigm and highlights the need for a nuanced understanding of the socioeconomic dynamics that shape the translation industry. The chapter exposes problematic practices that perpetuate technological discrimination and advocates for the use of Open Educational Resources (OER) and free, open-source software (FOSS) to foster inclusive learning environments. A decision-making framework is proposed to prioritize FOSS and cross-platform compatibility, enhancing technological and linguistic sovereignty, and empowering future translators to navigate the ethical implications of technology. Ultimately, the chapter emphasizes the importance of recognizing technology as a human construct with moral values and urges educators to cultivate critical awareness among students to ensure that technological advancements serve the emancipation of the translators of tomorrow.

Pages: 13

Various types of technology commonly deployed by professional translators can also be used in educational settings to provide support for text comprehension and production. In recent years, neural machine translation engines have had the most noticeable impact. Freely available services, such as Google and DeepL, have been rather uncritically embraced by many educators, researchers and students while being vilified by others, especially language teachers concerned about the future of society, not to mention their profession. Yet this widespread engagement with these popular translation technologies has also sparked growing awareness of the need for more multilingual content across all areas of society. This chapter provides an overview of how translation technologies can be, and have already been, incorporated into higher education outside the translation classroom. We reflect on the role of translation technology in fostering (machine) translation literacy, which is increasingly important for educational institutions under pressure to increase their international profiles and curricula. Rather than eliminating the need for people to learn languages or be involved in producing multilingual content, the greater accessibility of translation technology and its informed use can, and should, make both a necessary and a valuable contribution to promoting more active multilingualism in higher education.

Pages: 67

No chapter abstract available.

Pages: 12

Technological advances in machine translation (MT) are enabling more widespread human-machine interactions across nearly all areas of cross-lingual communication. With MT being increasingly integrated into human translation workflows, the translation profession is also experiencing profound transformations. To better understand these changes, this chapter centres the discussion on two key interrelated aspects of human-machine interaction. First, attention is paid to users’ attitudes towards MT and their role in shaping the interplay between users and technology. Research in this area has shown that users’ attitudes are context-dependent and largely influenced by their perception of MT output quality. The second part focuses on human-machine interactions stemming from the integration of MT into professional translation workflows. These interactions are co-shaped by technological developments as well as by individual and organisational factors such as translators’ skills and ways of working, ergonomic factors, and LSPs’ approaches to determining freelance translators’ remuneration. The chapter ends with a proposal to implement further regulation and training in the light of the opportunities and ethical challenges posed by emerging AI-powered technologies such as ChatGPT.

Pages: 14

Digitalisation is transforming the translation industry. Technologies such as computer-assisted translation, machine translation, translation management systems, and lately also large language models are reshaping work routines, workflows, and cognitive processes. This transformation not only entails benefits but it also has unexpected and sometimes undesirable consequences. In this chapter, we adopt a critical perspective on automation in the translation workplace, drawing on theories of digital workplace transformation and technostress. Applying concepts of layering and orders of effects of workplace technologies as well as different technostress creators, the chapter reviews workplace-oriented translation studies research and demonstrates a technological addition logic in the translation industry. This is leading to positive convergent and first-order effects but also to unintended changes in organisational hierarchies and the role and status of translators, reflecting second- and third-order effects of digital workplace transformation. The review also shows that several technostress creators seem to be at play in the translation industry. The chapter argues that the distinction between technological layers and orders of effects as well as the concept of technostress are valuable contributions to investigating technology-induced changes in the translation workplace and understanding the psychological aspects of the digital transformation.

Pages: 13

Recent advancements in natural language processing have led to improved machine translation quality and wider adoption of post-editing practices. The chapter explores how MTPE is changing the translation profession by analysing perspectives from industry, academia, and professionals. It discusses the evolution of quality assessment in machine translation and how it differs from quality concepts in Translation Studies. The adoption of MTPE has transformed translation work into a revision task, affecting translators’ workflows and remuneration. The chapter also addresses the responses of professional associations to the growing prevalence of MTPE, highlighting concerns about working conditions and the quality of end products. It examines the challenges faced by translators in adapting to MTPE requirements and the impact on different sectors of the language industry. Finally, it argues for the development of sustainable production processes that prioritise long-term benefits for all stakeholders. It concludes by emphasising the need for collaborative practices and technologies that empower all involved parties to ensure quality outcomes and foster a fair global market.

Pages: 13

Given the increasingly prevalent role of technology in the practice of translation and interpreting (T&I), and related research, this chapter discusses issues related to the goals and processes of optimising T&I technologies. Both the data sources used in developing technology and the data generated in its use are addressed, thereby highlighting the interrelated nature of data, optimisation goals and processes, and technological implementation. More specifically, optimisation in T&I contexts is addressed from the perspective of identifying areas for improvement, simplifying processes, and streamlining operations. The chapter examines how these issues relate to product, process, user experience, and societal impact from multiple vantage points, recognising the inherent tension between the various stakeholders impacted by optimisation practices. The discussion extends to misconceptions related to big data, technology, and optimisation as well as emerging issues related to open science, data management, and ethics.

Pages: 13

This chapter is concerned with automated translation of specialised genres, particularly through neural machine translation (NMT). To set the scene, the chapter first traces the history of translation-focused automation and discusses various models that have been proposed with regard to translation automation. It then elaborates on the concepts of specialised genres and domain-adapted machine translation and discusses specialised translators and their role in specialised communication communities. Then, the chapter takes a sociotechnical perspective and analyses the impact that translation automation via NMT may have on translators’ expert status and agency in MT-assisted specialised translation networks. This sociotechnical perspective is followed by a sociolinguistic/epistemic perspective, which narrows the focus to the immediate textual impact of NMT. In this context, the chapter discusses potential epistemic distortion of specialised discourse through instances of machine translationese and/or post-editese, which may lead to the suppression of target-cultural specialised genre conventions. The chapter concludes by suggesting some strategies that translation studies and translation didactics could employ in light of translation automation via NMT in order to counter negative effects on translators’ expert status and agency and to avoid epistemic distortion of intercultural specialised communication.

Pages: 82

No chapter abstract available.

Pages: 14

In this chapter, we explore the environmental impact of translation technologies, particularly focusing on energy consumption within the digital translation industry. While much of the more technical research on these translation technologies emphasises optimising translation quality and productivity, limited attention is given to the environmental considerations or the ecological footprint of the information and communication technology (ICT) infrastructure that supports these systems. Digital translation tools, including machine translation (MT), computer-assisted translation (CAT) and translation management systems (TMS), are heavily dependent on computational resources, contributing to a significant energy use and carbon emissions. We delve into the environmental consequences of modern translation workflows, examining the power demands of state-of-the-art neural MT models, which require large amounts of data and energy. We advocate for awareness and a more responsible use of translation technologies by offering practical recommendations to reduce the models’ environmental impact. These include power-monitoring software, careful consideration of hardware requirements, and adopting green practices in training and using models. Ultimately, we advocate for a balanced approach to translation technology development – one that considers long-term ecological sustainability alongside technical performance. The adoption of greener policies and practices across the ICT and translation industries is essential to minimise the negative environmental effects of translation technologies.

Pages: 10

The “Internet of Things” (IoT) is a term coined in the late 1990s to designate digital infrastructure enabling interconnectedness between “things” (e.g., appliances and sensors). The term gained popularity in the 2010s, being prominently featured in mainstream headlines and publications, including The Economist. Interestingly, the IoT is largely absent from Translation Studies (TS) research conducted around the same time. Admittedly, this makes sense given the launch of neural machine translation (NMT) in 2016 and the more recent introduction of ChatGPT, two events that arguably had more currency and relevance for TS. Still, there is also value in diachronic studies that seek to map and analyse the import of various technological shifts, which is the primary goal of this chapter. Incidentally, the IoT offers a rich field for exploring translation between non-human, non-sentient “things”. This chapter addresses the IoT and translation in four key areas: 1) industrial systems; 2) personal smart devices; 3) smart buildings, smart sites, and smart cities; and 4) the Covid-19 pandemic and privacy-first design.

Pages: 15

This chapter examines the linguistic, social, and educational implications of integrating deep learning into Machine Translation (MT) through neural network technology. Neural Machine Translation (NMT) is widely regarded as a valuable tool for society and institutions. However, it raises important questions about human involvement in machine learning, particularly with regard to the supervision of NMT systems and the evaluation of translation quality. The recent proliferation of Large Language Models (LLMs), such as GPT-4, which rely heavily on English-centric training data, further complicates these issues by potentially reinforcing language homogenisation and socio-cultural bias. This chapter explores how the prevalence of such training data in deep learning and the lack of human supervision in NMT training could affect linguistic diversity and perpetuate bias. It first outlines current deep learning algorithms in Natural Language Processing (NLP) and the importance of human intervention to mitigate errors and bias. The chapter then addresses the need for more inclusive language corpora to ensure representation of low-resource languages. Finally, it highlights the critical role of end-user awareness in the evaluation of NMT applications, especially in contexts such as language learning and academic communication, where the impact of AI on human cognition is significant.

Pages: 13

Creativity is often considered the decisive factor that distinguishes professional translations from machine-generated content. However, creativity is quite an elusive concept that is difficult to identify, measure, and compare. Although translators have employed their creativity for centuries, there is limited data that describes creativity in translation, including the creative person, the process, the product, and the environment. This lack of data becomes even more pronounced when technology is integrated into the translation workflow. This chapter seeks to address this gap. It provides an overview of creativity concepts in both the social sciences and translation studies and analyses existing research on creativity, technology, and translation. In doing so, it focuses on experiments that explore creativity, including cases where it is mediated by technology. Based on the available data, the chapter discusses the constraints that technology may impose on creativity and offers suggestions on how technology and creativity could be better understood or studied from a human-centred perspective.

Pages: 15

Since the mid-2010s, there has been renewed interest in the automation of literary translation, with both neural machine translation (NMT) and large language models (LLMs) currently applied to the task. Much research in the field has been concerned with technical issues such as how generic systems can be customized for literary translation and how outputs should be evaluated. Other sources focus on the impact of automatic literary translation on translated texts, the translation process, readers’ experience, and the translation market. The consequences for human literary translators of the increased uptake of NMT and LLMs in the profession have also received attention, with translators’ associations particularly vocal in their opposition to the perceived misuse of the technology. This chapter surveys these developments, ultimately arguing that despite the controversy it engenders, research into what we label “literary machine translation” still has much to offer, given its potential to inform critiques of the practice, to propose ways in which machines might assist rather than replace humans in literary translation, and to mould public opinion in a context in which literary machine translation is already a commercial reality.

Pages: 13

Machine translation (MT) is known to suffer from gender bias, with non-binary individuals being often neglected in research on the topic. While gender-fair language (GFL) could foster their visibility and increase gender sensitivity, its implementation in language technology can be regarded as highly controversial, ideologically loaded, and technically difficult. This chapter provides a critical discussion of GFL, its impact on society as a form of language planning, and its implications for translation and MT. We discuss influencing factors on the success of introducing new gender forms and acknowledge that the strategy to be preferred is still an open debate in research and the non-binary community, with the current consensus that different contexts will require different strategies. This complicates finding technically feasible strategies for debiasing MT beyond the binary and raises issues for translators to apply GFL in their daily work. We critically discuss the possibilities of introducing GFL to MT and possible pitfalls of this endeavour for the technology and the community developing it. We argue that a change in the MT paradigm, which currently exclusively relies on the source text to produce exactly one target text, might be necessary to achieve gender-fair MT.

Pages: 53

No chapter abstract available.

Pages: 12

This chapter provides an overview of key emerging themes in research that look at machine translation (MT) as an everyday communication tool. The chapter considers three broad MT use contexts: web browsing, social media, and interactions that take place in a shared physical space. A thread running through these contexts is the complex and double-edged nature of MT’s impact. When MT tools work, they help messages to travel further and wider, but MT can also distort and mislead, especially when faced with the non-standard language of social media posts. On public sector websites, MT provides access to information, but translation errors can also ostracise and potentially harm vulnerable communities. As part of the process of navigating these risks and benefits, the chapter calls for further research on MT’s portability and its capacity to permeate different spaces as an embedded, and sometimes inconspicuous, service. We highlight the need for more collaboration between translation and interpreting and for more examination of increasingly blurry distinctions between physical and virtual environments and between technologies themselves. Working across these blurred boundaries is, we argue, essential for future research on translation, interpreting and multilingual communication.

Pages: 13

Alongside the rise in professional translators’ use of machine translation (MT), non-translators have also begun to integrate MT into their everyday lives, including in their work. Companies and organisations have integrated MT into internal as well as external communication processes, and its use in fields such as legal, healthcare, academia, and journalism is growing. This chapter first gives an overview of research on these use cases to date, then examines the implications this growing reliance on MT poses. These include both opportunities, such as the benefits and the challenges the technology brings to humankind, including a growing demand for focus on risks and MT literacy, a need for guidelines and regulations on MT use, and an emerging need for new types of tools for users. In addition to these, the growing use of MT among non-translators brings with it implications and opportunities for professional human translation.

Pages: 12

As the number of users of machine translation tools continues to grow – particularly outside of the language industries – there is a need for improved machine translation literacy among these user groups. Following a brief summary of key differences between dedicated machine translation tools and tools based on large language models that can be used for translation, this chapter introduces some core elements of machine translation literacy, including awareness of how data-driven approaches work and different translation scenarios, a need for transparency, and an appreciation of effective ways to interact with these tools. The chapter then considers what machine translation literacy can draw from other domains (e.g., privacy and ethics), before presenting some societal and economic implications of machine translation literacy (e.g., viability and sustainability of the translation profession, new markets for translation, and environmental costs of translation tools). Finally, the chapter concludes with some future directions for research on machine translation literacy, including considerations of how it can be tailored to different user profiles.

Pages: 14

With the advent of AI approaches to machine translation (MT), we have seen a huge improvement in quality. However, this has resulted in levels of overhyping of MT capability, which has led some commentators to invoke “the singularity” and claim that human translators are doomed as their jobs will be taken over completely by machines. While performance gains using AI techniques are impressive, they do not merit hyperbolic claims concerning their performance. Whenever there is a paradigm shift performance gains are seen quite quickly, but level off reasonably soon thereafter. Based on 35 years experience building MT systems of different types, this article attempts to apply some perspective as to what the future holds, especially for human translators, who – I contend – will continue to play a critical role, even if further performance gains are to be seen and MT is to be more widely adopted.