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## HERMES

## Journal of Language and Communication in Business

Anne Schjoldager, Helle Dam Jensen, Tina Paulsen Christensen & Kristine Bundgaard

## Professional Translator vs. Google Translate: the case of Lars Larsen's Autobiography

## Abstract

Wishing to contribute to a necessary discussion of how the task of translation should be conceptualised in our posthuman world, the paper investigates what characterises a professional translation completely unaided by translation technology and compares it with a translation generated by Google Translate (GT), a well-known and free neural machine translation (NMT), based on artificial intelligence (AI). The source text is Lars Larsen's Danish-language autobiography from 2004, assessed  as  particularly  challenging  to  translate  because  of  many  instances  of  contextually  and  culturally  embedded meaning. Analyses are carried out in three steps: (1) a textual analysis of the source text; (2) a skopos-theoretical analysis of the professional translation; and (3) comparative analyses of the two translations. In terms of wording, two thirds of the translations are assessed  as sufficiently similar to conclude that these parts of the GT translation achieve professional translation quality. The remaining parts are sufficiently different to conclude that professional quality is not achieved by GT. The professional translator complies with professional ethics and Vermeer's hierarchy of rules and succeeds in solving all predefined translation problems, while this is not the case for GT. The reason may be that GT does not understand text in the real sense of the word, does not work situationally and goal-oriented and does not base decisions on professional expertise and ethics. While we are looking into a future with increasingly advanced translation technology, we should not lose sight of what is expected of a professional translation.

## Keywords

Professional  translation;  neural  machine  translation  (NMT);  Google  Translate  (GT);  professional  translation  quality criteria; skopos theory; source-text analysis; artificial intelligence (AI); contextually and culturally embedded meaning.

## 1. Introduction

With this paper, we wish to contribute to a necessary discussion of how professional translation in the  posthuman  age  should  be  conceptualised.  Not  so  long  ago,  professional  translation  was conceptualised  as  a  cognitive,  non-routine  and  complex  task  that  only  humans  can  carry  out. Nowadays, in the wake of technological developments, we need to accept that this conceptualisation may no longer be valid (e.g. Frey & Osborne, 2017, p. 259; O'Thomas, 2017; Tieber, 2022). Since 2016,  based  on  artificial  intelligence  (AI)  and  using  increasingly  large  datasets,  neural  machine translation (NMT) has been taking over translation processes in the language industry to such an extent that human translators are often relegated to the role of post-editors (Christensen et al., 2022). From a product perspective, however, translation quality criteria should probably be the same as before AI-based translation technology kicked in.

Drawing  on  Vermeer's  skopos  theory  (Reiss  &  Vermeer,  1984),  we  argue  that  professional translation  should  continue  to  be  viewed  as  a  service  delivered  to  a  customer,  fulfilling  a  given

* Anne Schjoldager School of Communication and Culture Aarhus University asc@cc.au.dk
- *** Tina Paulsen Christensen School of Communication and Culture Aarhus University tpc@cc.au.dk
- ** Helle Dam Jensen School of Communication and Culture Aarhus University hed@cc.au.dk
- ****  Kristine Bundgaard The Faculty of Social Sciences and Humanities Aalborg University kbundgaard@ikl.aau.dk

purpose  (skopos)  in  a  particular  context  with  a  specified  target  audience  in  mind  and  based  on professional ethics. Within a skopos-theoretical framework, our paper investigates a professional translation carried out in 2004, completely unaided by translation technology (see section 4.2), and compares this with an unedited translation generated in 2022 by Google Translate (GT). GT was chosen  because  it  is  a  free,  easily  accessible  and  highly  popular  NMT,  which  is  used  both professionally and for other purposes on a regular basis by millions of people (Aguilar, 2023).

The source text (ST) of our study is Lars Larsen's rather unique autobiography (Larsen, 2004a). A well-known Danish entrepreneur and business magnate, Larsen founded and was the main owner of JYSK, an international chain of stores, headquartered in Jutland (Denmark) and specialised in selling  quality  bedding  and  other  household  articles  at  discount  prices.  His  autobiography  was distributed as a promotional gift to all Danish households on the occasion of the company's 25 th anniversary. The book was translated into multiple languages, including English, by professional translators. We use the English-language translation (Larsen, 2004b) as a yardstick for professional translation  quality  in  the  GT-generated  translation.  Background  knowledge  for  the  analyses  is provided by interviews with Larsen's then PR manager Carl Erik Stubkier (CES) and the Englishlanguage translator Lotte Kovdal (LK) 1 . Background information is also found in contemporary book reviews and some news articles.

Though  literary  translators  have  begun  to  use  various  types  of  translation  technology  (e.g. Taivalkoski-Shilov & Koponen, 2023, and this volume), literary fiction and other creative genres are still regarded as particularly challenging to translate with the aid of technology. A main challenge is that  translating  such  texts  tends  to  involve  the  interpretation  and  rendition  of  textual  features embedded  in  a  given  context  and  culture,  by  means  of  implicitness,  ambiguity,  vagueness, intertextuality or culture-specific references (e.g. Language  Connections, n.d.; O'Brien  & Ehrensberger-Dow, 2020). Professional translators can understand such textual features by means of intuition and associative thinking and are able to find appropriate translations using their training for strategic decision-making and creativity. GT and other NMTs are still greatly challenged by such features (Guerberof Arenas & Asimakoulas, 2023, and this volume; Guerberof Arenas & Toral, 2022; O'Brien & Ehrensberger-Dow, 2020; Toral & Way, 2018). Larsen's autobiography, which we regard as belonging to a literary genre, was chosen for its many embedded features.

Section 2 presents GT and discusses how it may be reaching human translation quality. Using skopos theory, section 3 defines what characterises professional translation, as opposed to what may be expected of GT. Section 4 reports on three analytical steps. Firstly, using Jakobson's model of verbal communication (Jakobson, 1960/1981), a textual analysis of Larsen's book was carried out to gain insights into textual features and references that might have been identified and analysed by LK. Secondly, drawing on insights from interviews with CES and LK and other background information, a skopos-theoretical analysis was carried out on LK's translation, with an emphasis on the situation and the perceived skopos. Thirdly, a GT translation of selected parts of Larsen's book was compared with corresponding parts of LK's translation. The translations were compared in terms of wording and  textual  length,  in  terms  of  the  occurrence  of  grave  mistakes,  categorised  as  nonsensical translations  or  blatant  mistranslations,  and  in  terms  of  the  adequacy  of  solutions  to  predefined translation problems, using Nord's conception of functional translation problems (e.g. Nord, 2018, pp. 59-60). Section 5 finishes the paper with a brief summary of the results and some concluding remarks.

1  We are grateful to CES and LK for their willingness to talk to us and for allowing us to make use of their important and interesting insights into the circumstances of Larsen's unique book project. CES was interviewed on 7 June 2021 at JYSK's headquarters for approximately 80 minutes. LK was interviewed on 20 June 2021 in her home office for approximately 70 minutes.

## 2. Google Translate

As already mentioned, GT is an extremely popular NMT, freely available online and offering speedy translations between more than 130 languages to millions of people on a regular basis. GT is best used for the translation of short texts as it has a performance limit of 5,000 characters. GT was first launched in November 2006, when it only worked between English and Arabic, but other languages were soon to follow. As far as we know, Danish has been available on GT since September 2008. Other available machine-translation (MT) systems at the time were mainly rule-based (e.g., Systran and Apertium), but GT was launched with a statistical engine from the start (Turovsky, 2016) and was therefore faster and delivered better quality than other MTs at the time, as explained by Macduff Hughes, GT's chief engineer (Economist, 2017a). A statistical MT (SMT) uses predictive algorithms to analyse enormous linguistic datasets. The statistical version of GT used English as a go-between (pivot language) for translations of and into other languages, but this changed in November 2016, when GT was relaunched as an NMT (Aguilar, 2023; Wikipedia, 2023).

The NMT version of GT is described as a powerful AI-based translation engine 'loosely modelled on the human brain' (Economist, 2017b). It uses an advanced type of machine learning, so-called deep  learning 2 ,  based  on  volumes  of  linguistic  data  to  identify  patterns  and  suggest  translation proposals. Unlike an SMT, which translates in a word-for-word or phrase-for-phrase fashion, NMTs use the input sentence as the unit of translation and the surrounding text (the co-text) to factor which translation proposals are most acceptable (Forcada Zubizarreta, 2022b; Lee & Schuster, 2016, p. 1). It seems that NMTs typically use an encoder-decoder framework, which was pioneered by GT. The encoder  processes  the  SL  sentence  and  compresses  it  to  a  so-called  context  vector,  which (supposedly) captures the meaning of the sentence. Based on 'a weighted distribution' in the vector and a predictive algorithm, the decoder uses the context vector to map SL input directly on to TL output (Lee & Schuster, 2016, p. 2).

The output quality of GT and other NMTs is now sufficiently high to be deemed useful in many situations, mostly for personal use (gisting), but also for delivering draft translations to be post-edited in  professional  contexts  (Forcada  Zubizarreta,  2022b).  The  quality  is  especially  improved  when English is involved, due to increasing volumes of digitally available English-language data, but the quality of translations from and into languages with fewer available data, such as Danish, has also improved (Ramati & Pinchevski, 2018; Vincent, 2019). The output quality has increased particularly for grammaticality, fluency and, to a certain degree, accuracy (Macken et al., 2019). Some would even say that GT and other NMTs have begun to outperform human translators (e.g. Hassan et al., 2018, p. 2; Läubli et al., 2018; Pym & Torres-Simón, 2021), while others are adamant that this is not going to happen any day soon, and the reason for this is that NMTs lack human qualities. Thus, for instance,  based  on  a  qualitative  study  of  GT  translations  between  English,  French,  German  and Chinese of various literary books, Hofstadter concludes that GT does not understand anything and therefore does not translate in the real sense of the word (Hofstadter, 2018, p. 16), which may explain why  GT  struggles  to  translate  some  contextual  and  culture-specific  elements  that  professional translators are expected to deal with quite routinely.

It is important to point out that the relatively high output quality of GT is achieved by reusing data from publicly available online translation corpora, such as those provided by the United Nations or  the  European  Union,  or  from  web  texts  in  multiple  languages  (Forcada  Zubizarreta,  2022a; Language Connections, n.d.; Moorkens & Lewis, 2020, pp. 469-470). Legally, the owners of these translation corpora or web texts are afforded protection under copyright laws, but the legal risk for GT is now minimal because the harvested data is processed and fragmented into unrecognisable units, making it almost impossible to prove ownership to such data (Forcada Zubizarreta, 2022a). This poses a serious ethical issue with using GT that is seldom discussed. Another serious issue with using GT relates to data privacy protected by EU's General Data Protection Regulation (GDPR) (European Parliament and the Council of the European Union, 2016). Thus, for instance, an ethical problem arises when users upload source material containing personal data that is appropriated by GT and used for data training.

2  Deep learning is: 'A type of machine learning considered to be in some way more dynamic or complete than others; esp. machine learning based on artificial neural networks in which multiple layers of processing are used to extract progressively more features from data' (Oxford English Dictionary, 2023).

## 3 Professional translation

GT is a disembodied AI system emulating human thinking (Massey, 2021); it cannot make conscious, strategic and ethical decisions based on cultural, contextual and other knowledge of the world. A professional translator is a human being who is able to make such decisions, using cognition, intuition and creativity. Like other professionals, professional translators are bound by professional ethics, such  as  diligence,  accountability,  integrity,  confidentiality  and  accuracy  in  their  work.  From  a business perspective, a professional translator is an individual who provides a paid-for translation service required by and delivered to a customer (ISO International Organization for Standardization, 2015; Mossop et al., 2020, p. 6). Though translation is an increasingly unregulated profession (e.g. Samuelsson-Brown, 2006, p. 89), professional translators are generally expected to have acquired translational skills and competences through education, training and/or experience, which entails that they  are  trained  to  use  their  intelligence  and  expertise,  including  how  to  use  tools,  to  deliver translations of a certain standard (Schjoldager et al., 2010, pp. 114-118).

According to the Oxford English Dictionary, to 'translate' is: 'To convert or render (a word, a work, an author, a language, etc.) into another language; to express or convey the meaning of (a word or  text) using  equivalent  words in  a  different  language'  (Oxford  English  Dictionary,  2023,  our emphasis). The dictionary also lists a number of related and more figurative senses of the verb (for instance, to adapt an idea from one context into another), but the definition quoted above is first on the list, and we think that it expresses how translation is understood by most people who have not studied or practised professional translation. It is therefore important to point out that translation involves much more than 'using equivalent words', a fact that is generally acknowledged within translation studies. What is more, equivalence as a defining feature of translation is rejected by many translation  scholars,  notably  within  skopos  theory  (Reiss  &  Vermeer,  1984).  Inspired  by  HolzMänttäri's translational action theory (Holz-Mänttäri, 1984), Vermeer (e.g. Vermeer, 1989/2000) defines translation as a particular type of communicative action, emphasising that - just like any other human action - translation is geared towards a specific purpose, which is always embedded in a given situation. The purpose of a translation is referred to as 'skopos', which is Greek for 'purpose'.

Skopos scholars focus on what the target text (TT) needs to achieve (e.g. Nord, 2005b, pp. 1617). Rejecting the notion of equivalence, they prefer to discuss the expected degree of invariance between a TT and its ST in terms of adequacy or fidelity (e.g. Nord, 2018, pp. 33-36). To support a skopos approach to translation, Vermeer proposes a hierarchy of three translation rules (Nord, 2018, pp. 28-31): (1) The skopos rule, which stipulates that the TT must fulfil the designated purpose of the translation; (2) the rule of intratextual coherence, which stipulates that the TT must be translated in such a way that TT receivers can understand it; and (3) the fidelity rule or the rule of intertextual coherence, which stipulates that the TT must reflect the ST in an adequate way. It is important to note that skopos and intratextual coherence (in that order) are prioritised over ST fidelity.

When describing the ST as 'an offer of information' (Vermeer, 1989/2000, p. 222), Vermeer argues that the ST is just one of several influences; he does not, as some critics have suggested, issue a carte blanche to translate without consideration of the form and content of the ST (Nord, 2018, p. 25; Schjoldager et al., 2010, pp. 158-159). On the contrary, as emphasised by Nord, the translation process should integrate a careful and thorough ST analysis (Nord, 2005a; 2018, pp. 58-59). The aim of this analysis is to provide valuable input for the translator's decision-making process, not least regarding which strategies should be used to solve which translation problems (Nord, 2018, p. 59; Schjoldager et al., 2010, p. 174). As an addition to the general set of professional ethics mentioned above, Nord proposes an obligation of loyalty to parties with legitimate interests in the translation product, including ST sender, commissioner and TT receivers (Nord, 2018, p. 117).

Nord  sets  up  a  translation  typology  according  to  differing  skopoi,  building  on  Vermeer's discussion of documentary and instrumental translations (Vermeer, 1989/2000, pp. 231-232): If a translation is documentary, the skopos is to create a metafunctional TT: a text about a text, which makes the approach source-culture oriented (Nord, 2018, p. 46). If a translation is instrumental, the skopos is to achieve either the same function or a similar function as that of the ST, which makes the approach  target-culture  oriented  (Nord,  2018,  p.  48).  While  somewhat  similar  to  previous dichotomies - such as Nida's formal vs. dynamic equivalence (Munday et al., 2022, pp. 56-57; Nida & Taber, 1974) - Nord's typology is essentially different in that neither translation type is inherently better than the other (Nord, 2005b, pp. 26-27).

While scholars sceptical of skopos theory argue that a purpose-oriented approach oversimplifies the task of translating literary genres and jeopardises the transfer of the originality of the ST (e.g. Nord,  2018,  p.  112),  Nord  shows  how  different  skopoi  may  produce  different  types  of  literary translations of the same text. Furthermore, pointing out that 'the conventional translation type in literary  prose  seems  to  be  documentary  and  exoticising'  (Nord,  2018,  p.  94),  she  recommends instrumental translation types for literary genres, giving translators more freedom to choose creative solutions to translation problems. Interestingly, though creativity is widely regarded as a distinctly human ability, the notion has not received much attention within translation studies (e.g. Guerberof Arenas & Toral, 2022, pp. 184-185). In a rare quantitative study of translational creativity, Guerberof Arenas and Toral (2022) compare human translations of an English-language short story by Kurt Vonnegut into Catalan and Dutch with those of an NMT. Defining translational creativity as the achievement  of  acceptability  and  novelty  (inspired  by  Bayer-Hohenwarter  &  Kussmaul,  2020), Guerberof Arenas and Toral conclude that the human translations are more creative than those of the NMT, including post-edited versions (see also Guerberof Arenas & Asimakoulas, 2023; and this volume).

## 4 The case study

As already mentioned, Larsen's autobiography was chosen for our case study because it offers many examples of contextually and culturally embedded meaning, which is challenging to translate. In addition,  the  case  of  Larsen's  book  was  useful  because  its  professional  translation  (by  LK)  was carried  out  completely  without  translation  technology.  The  first  step  of  the  analysis  (4.1)  was  a textual analysis of Larsen's book in its own right. The second step (4.2) focused on the translation situation and the perceived skopos of LK's translation. With a view to ascertaining the professional quality of the GT translation, the third step (4.3) comprised several stages in which LK's translation of selected parts of Larsen's book were compared with the GT translation of these parts.

## 4.1 A textual analysis of the source text

To  structure  the  ST  analysis,  we  used  Jakobson's  classical  model  of  verbal  communication (Jakobson,  1960/1981;  Schjoldager  et  al.,  2010,  pp.  21-25).  Jakobson  uses  a  conduit  metaphor, representing communication as a transfer process in which a sender's message is sent and received (Grady, 1998). Though this model may be criticised for placing too much emphasis on the sender and too little on the receiver, we found the model useful because we focus on Larsen's intentions as a sender. The model comprises six communicative dimensions, which we refer to below as sender, situation, channel, receiver, text and style 3 .

3  Jakobson's own terms are (in the order of our own paper): addresser, context, contact, addressee, message and code.

## Sender

Lars Larsen (1948-2019) is easily identifiable as the sender. His full name is mentioned twice in the title on the front page, which also suggests the genre as that of an autobiography, cited here from LK's translation: 'Hello my name is Lars Larsen - I have a good offer. An autobiography by Lars Larsen' (Larsen, 2004b). We first wondered if Larsen was really the text producer, but CES (Larsen's PR manager) assured us that this was certainly the case and showed us Larsen's original, hand-written manuscript on display in an exhibition on JYSK history at the headquarters in Aarhus.

Larsen began with a single shop in 1979 in Aarhus, the largest town on the peninsula of Jylland (Jutland), which makes up the western part of Denmark. The business formula was to sell quality bedding  and  other  household  goods  at  reasonable  prices.  The  company  was  called  'JYSK Sengetøjslager' [JUTLANDIC bedding storeroom] 4 . Larsen's choice of 'JYSK' in the name was a deliberate choice because it signalled Jutlandic values, which he expected would appeal to customers (Larsen, 2004a, p. 44). In Denmark, people from Jutland were (and probably still are) reputed to be down-to-earth, honest, hard-working, thrifty, modest and friendly, and Larsen took advantage of this (e.g.  Laugesen,  1999).  Perhaps  this  was  also  why  Larsen  preferred  the  unpretentious  title  of 'købmand',  a  traditional  word  for  a  tradesman  or  merchant,  to  the  title  of  'direktør'  [managing director] or CEO, which he certainly was (Larsen, 2004a, p. 184). The word 'købmand' combines the Danish words for 'buying' and 'man' (cf. German: 'Kauffman'). According to an often-used Danish/English dictionary (Axelsen, 2010), 'købmand' may be translated into 'grocer', 'businessman', 'dealer', 'merchant', 'shopkeeper' or 'storekeeper'. However, for various reasons, in our case, 'grocer', 'dealer', 'shopkeeper' and 'storekeeper' do not convey the right connotations.

Despite his Jutlandic modesty, to cut advertising costs, Larsen used himself as the public face of JYSK, especially in a series of very short, but highly popular TV commercials, which were among the  very  first  in  Denmark.  All  commercials  featured  Larsen  speaking  in  his  well-known  and characteristic Jutlandic dialect, always greeting viewers with 'Go'daw' (Jutlandic for 'hello') and never failing to offer a 'good offer'.  The front page of the book refers to these commercials by depicting a small TV screen (under the main title) with Larsen holding a feather and looking directly at two spectators on a sofa (Appendices 1 and 2).

## Situation, channel and receivers

The autobiography was printed locally and inexpensively and was published on 1 April 2004 as part of  a  well-planned  advertising  campaign  celebrating  JYSK's  25 th anniversary.  Paperbacks  were distributed  for  free  to  all  Danish  households  (2,400,050  copies),  while  hardbacks  were  given  to employees, business partners and friends in Denmark. Both versions may be regarded as the channel for Larsen's promotional message. According to an article in the Danish newspaper Berlingske , the book became the most read Danish book at the time (Kassebeer, 2004), and, based on an investigation conducted by SONAR 5 , approximately 800,000 Danes had read the book by May 2004, and just as many  had  read  some  of  it.  We  therefore  conclude  that,  as  an  advertising  outlet,  Larsen's  book excelled.

## Text and Style

Larsen's  style  is  informal,  often  humorously  understated  and  characterised  by  an  abundance  of witticisms. Richly illustrated by photographs, newspaper clips, JYSK advertisements and business documents, the book comprises a total of 192 pages, divided into 130 short and unnumbered chapters, narrating Larsen's personal and professional history. The book relays many personal anecdotes and internal  JYSK  jokes,  and  it  is  full  of  culture-specific  references  that  readers  are  expected  to  be familiar with, such as places, people and historical events in Denmark. Though the aim of Larsen's autobiography was obviously promotional, several Danish newspapers and magazines reviewed it as a literary book. Most reviewers criticise Larsen's lack of literary style, but praise his humour and value the book as an account of Danish society from the 1970s and onwards (Tetzlaff, 2019/2004). A review in Nordisk Litteratur proclaims Larsen the 'Duvet King of Denmark', praises the book for its 'very special form of social realism prevalent in Jutland' and describes the content as a 'fairytale about a crack-brained businessman from North Jutland' (Bager, 2005, p. 178).

4 In this article, glosses in English are provided in square brackets.

5  SONAR is a Danish market and opinion research company (https://sonar.dk/) .

## 4.2 The translation situation and the skopos

Using a skopos-theoretical framework, we analysed the professional translation situation and the perceived skopos, assuming that these should be used as a basis for the assessment of the human translation quality of GT.

## Translation situation

According to the printer's inscription, 2,000 English-language translations were published. These were given to employees and business  partners abroad, especially at JYSK's many international branches. LK is an authorised and fully qualified translator between Danish and English as well as Larsen's niece. When asked to translate the book,  she  was  at  the  beginning  of her  career.  As  a professional translator, LK prefers to translate into Danish, her native language, but she also accepts work into English, as in the case of Larsen's book. Most of Larsen's family work or have worked for JYSK, including LK's mother and brothers, but, apart from the translation, LK has not worked for JYSK. A local translation  company  was  in  charge  of  all  other  translations  of  the  book,  but  LK explains that Larsen and his wife preferred her for the English version.

As Larsen's niece, LK already knew Larsen's history and was also familiar with  his business model, communicative style and sense of humour. It is therefore safe to conclude that it was easier for LK to understand the ST than for most other translators. However, as LK soon realised, translating the autobiography was quite challenging for many reasons, as mentioned in 4.1. LK found much help and  inspiration  in  various  bilingual  and  monolingual  dictionaries,  but  she  also  benefitted  from discussing difficult translation problems with a London-based colleague. Though some translation technology was available at the time, LK did not use it for Larsen's book because she did not expect it to be helpful. If she were to translate a similar ST today, she would probably look for inspiration on JYSK's own website, but their website had very little English-language content back then. In sum, as far as finding solutions to the many translation problems, LK was probably just as challenged as any other qualified native Danish translator between Danish and English.

## Skopos

LK was not given specific instructions for the translation, but she knew that the Danish version was to be distributed to all Danish households, and she assumed that her translation was to be sent to business contacts and colleagues abroad, which was indeed the case. LK does not remember how much she considered the target audience while translating. Assuming that she must have operated on a  perceived skopos, we asked her about various translation problems, inviting her to explain her reasoning. Thus, for instance, we asked LK about a particularly challenging problem that occurs when  Larsen  explains  JYSK's  basic  values,  written  into  an  official  document  referred  to  as  a 'gåseæg' [goose egg], alluding to JYSK's many goose-feather duvets and pillows and also to the company's  goose  logo.  The  JYSK  values  are  expressed  by  means  of  three  Danish  keywords, beginning with 'K' and abbreviated into 'KKK': 'Købmand - Kollega - Korpsånd' [Tradesman Colleague  -  Team  spirit]  (Larsen,  2004a,  p.  186).  It  is  not  possible  to  find  adequate  English translations  for  all  three  keywords  that  begin  with  'K',  and  even  if  it  were,  using  the  'KKK' abbreviation in English risks raising some unfortunate associations (cf. the Ku Klux Klan). LK is evidently  aware  of  these  problems 6 and  solves  them  with  due  consideration  for  the  translation situation:  '[…]  we  called  our  values  KKK  which  stands  for  Købmand  -  Kollega  -  Korpsånd (Businessmanship - Colleagueship - Team spirit)' (Larsen, 2004b, p. 186) 7 . Based on this and other translations  discussed  with  LK,  we  conclude  that  she  was  influenced  by  a  perceived  skopos:  to translate Larsen's text in such a way that it could achieve a promotional and informative function similar to that of the ST. This indicates an instrumental approach.

## 4.3 Professional translation vs. Google Translate

We used selected parts of Larsen's book for the comparative analyses, namely, the first part of the title and four chapters selected for their many types of translation problems (in Nord's sense). Below, the selected parts will be referred to collectively as source-text data (ST-d). Table 1 gives an overview of ST-d, quoting the book title and chapter headings in LK's translations (in quotation marks). The chapters  are  listed  in  chronological  order,  enumerated  by  letters  A.  to  D.  The  chapters  were subdivided into analytical segments, which were identified by means of full stops in the ST, except in a few cases that were identified by other means (in the book title, for instance). As shown in the final row of Table 1, a total of 128 segments were identified and analysed.

Table 1: Overview of source-text data (ST-d)

| Data       |   Book title: 'Hello my name is Lars Larsen' (front page) |   A. 'Dear employees, suppliers, family, friends, collaborators and everybody else who receive this book' (p. 5) |   B. 'Memorial Award ofDKK 500 and 'Tailored' Clothes for my Confirmation' (pp. 22-24) |   C. 'You Can Only Die from Stress and Old Age' (pp. 183-184) |   D. 'Business- manship - Colleagueship - Team Spirit' (pp. 186-187) |   Seg- ments - all |
|------------|-----------------------------------------------------------|------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------|---------------------------------------------------------------|----------------------------------------------------------------------|--------------------|
| Seg- ments |                                                         1 |                                                                                                               23 |                                                                                     40 |                                                            33 |                                                                   31 |                128 |

The book title has already been introduced in 4.1 and will be discussed further below. Chapter A. is a foreword signed by Larsen himself, thanking readers for their part in his growing business empire, explaining about the anniversary and announcing that the company name will now be shortened to just 'JYSK' for all outlets, except in Germany and Austria 8 (Larsen, 2004a, p. 5). Chapter B. tells a typical story from Larsen's impoverished childhood, growing up with a single mother and three older siblings: How a study grant made it possible for him to continue his schooling after the age of 14 and how he told 'a little white lie' regarding a very inexpensive suit that he wore for his confirmation, claiming  that  it  was  'tailored'  (Larsen,  2004b,  p.  23).  Chapter  C.  focuses  on  Larsen's  gradual withdrawal from the day-to-day running of JYSK, describing himself as a 'young pensioner' who can pass on 'experience to the next generation' (Larsen, 2004b, p. 183). Chapter D. comprises the last pages of the book and explains Larsen's vision for JYSK, including the three keywords that are quoted  in  the  chapter  heading  (also  discussed  in  4.2,  above).  ST-d  was  then  mapped  on  to corresponding parts of LK's translation, which will be referred to as TT-1. The GT translation of STd was generated in July 2022 and was also mapped on to ST-d. We will refer to the GT translation as TT-2.

6  We categorised such translation problems as language- and situation-related (see section 4.3).

7  The three keywords are still used by JYSK, but the English translations are now (2023): 'Tradesman - Colleague -

Corporate Spirit'. As far as we can see on their website, the abbreviation 'KKK' is no longer used in Danish or English (https://job.jysk.dk/dk/jysk-arbejdsplads).

8  For a while, 'Danishes Bettenlager' [Danish bedding storeroom] was still preferred in Germany and Austria.

We will now report on our findings regarding text lengths (4.3.1), the extent of human quality in GT (4.3.2), the occurrence of grave mistakes (4.3.3) and how predefined translation problems are dealt with (4.3.4).

## 4.3.1 Text lengths

The relative lengths of ST-d and the two TTs were measured to detect any significant differences in this respect between the TTs. According to Blum-Kulka's explicitation hypothesis, translators are generally inclined to explicate implicit elements, which tends to make TTs longer (Blum-Kulka, 1986; Olohan & Baker, 2000). Furthermore, in translations from Danish into English, TTs might be slightly  longer  because  of  different  conventions  in  Danish  and  English  regarding  the  writing  of compound words. Danish writes series of two or more words together (closed compound words), whereas English prefers to write words separately (open compound words). Lengths were therefore measured in words as well as in characters, which were measured both without and with blanks. An example from chapter C. of a closed compound word in Danish is 'pensionsalder' (one word, no blank), which is rendered by an open compound word in English: 'pension age' (two words, one blank) in LK's translation (Larsen, 2004b, p. 183).

Table 2 gives an overview of the respective lengths of ST-d, TT-1 and TT-2. Percentages are rounded up, and highest figures are marked by bold.

Table 2: Comparing text lengths

| Texts   | Words         | Characters without blanks   | Characters with blanks   |
|---------|---------------|-----------------------------|--------------------------|
| ST-d    | 2,099         | 9,410                       | 11,530                   |
| TT-1    | 2,242 (+6.4%) | 9,756 (+3.5%)               | 12,017 (+4%)             |
| TT-2    | 2,267 (+7.4%) | 9,575 (+1.7%)               | 11,811 (+2.4%)           |

As expected, both TT-1 and TT-2 are slightly longer than ST-d in terms of both words and characters (without and with blanks). TT-2 comprises more words than TT-1, whereas TT-1 has more characters than TT-2 (without and with blanks). We regard these quantitative differences as so slight that they are of little significance for the present study.

## 4.3.2 Human quality in GT

Using TT-1 (LK's translation) as a yardstick for human quality in TT-2 (GT), we ascertained the degree of textual similarity between the two TTs. The premise was that TT-2 elements that were assessed as textually similar to corresponding TT-1 elements needed no or little post-editing before publication,  which  we  defined  as  human  quality.  For  our  purposes,  elements  were  assessed  as textually similar if the wording was identical or near-identical. Near-identical elements were slightly different in word order, word class and, if verb forms, in tense, aspect or mood. Using this definition, we found that, out of a total of 2,267 words in TT-2, 1,410 words were textually similar to words in corresponding places in TT-1. This means that approx. 62% of TT-2 is textually similar to TT-1. Results were very similar regarding characters without and with blanks. We therefore conclude that a  relatively  large  part  of  TT-2  would  probably  have  needed  no  or  little  post-editing  before publication. We are not sure how significant this is, but we think the high level of similarity between the two TTs may be linked to the fact that PDF versions of both Larsen's book (Larsen, 2004a) and LK's translation (Larsen, 2004b) have been available online at least since the summer of 2022, when we checked for the first time. This means that LK's translation might have been used to train GT's dataset before TT-2 was generated 9 .

## 4.3.3 Grave mistakes

Expecting grave mistakes to occur in TT-2, but not in TT-1, we proceeded to look for such mistakes in the TTs. We  categorised grave mistakes as either nonsensical translations or blatant mistranslations.  A nonsensical translation prevents  the  reader  from  making any  sense  of  the  TT element in question. This can be detected just from reading the TT, without consulting the ST. Eleven TT-2 elements were categorised as nonsensical translations, whereas none were found in TT-1. Table 3 shows an example of nonsensical translation. The table quotes ST segment 28 in chapter D. as well as corresponding elements in TT-1 and TT-2. In this and the following tables, the relevant ST and TT elements are italicised ,  the  ST element is marked by bold ,  and unacceptable TT elements are marked by red . Again, glosses in English are added in square brackets.

Table 3: A nonsensical translation in TT-2

| Segment   | ST-d                                                                                                                                                                                                                                     | TT-1                                                                                                        | TT-2                                                                                                           |
|-----------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------|
| D.28      | Det kæmper vi så for hver eneste dag ved at finde den rette vare, på det rette tidspunkt og til den rette pris. [So, this is what we fight for every single day by finding the right product, at the right time and at the right price.] | Wefight to do that every single day by finding the right product, at the right time and at the right price. | Wethen fight for it every single day by breathing the right product, at the right time and at the right price. |

In segment D.28, Larsen presents the JYSK values and his business model. In the previous segment (D.27), it is explained that the aim at JYSK is to satisfy customers, and, in D.28, it is explained how they fight to do this 'by finding the right product […]'. In TT-2, the ST element 'finde' [finding] is rendered as 'breathing', which is nonsensical: you cannot 'breathe' a product.

A blatant mistranslation renders ST meaning in a way that is contrary to what was intended by the ST sender. It is necessary to consult the ST to detect a blatant mistranslation. Nineteen TT-2 elements were categorised as blatant mistranslations, whereas none were found in TT-1. Table 4 gives two examples of blatant mistranslation from chapter B., which concerns Larsen's childhood wish  to  further  his  education  after  seven  years  of  obligatory  schooling  (c.  1962).  His  teacher recommended that Larsen went on to 'realskolen', an optional three-year lower secondary school (discontinued in 1975), but his mother would not allow it for financial reasons. Eventually, Larsen's mother was made to change her mind, and, in B.9, it is suggested that the clinching argument was a substantial study grant that he would then be eligible for.

9  We have tried to contact Google Denmark several times to enquire how likely it is that LK's translation has been used to train GT's dataset. They never got back to us on this.

Table 4: A blatant mistranslation in TT-2

| Segment   | ST-d                                                                                                                                                                                                                                                                                                                   | TT-1                                                                                                                                              | TT-2                                                                                                                                                |
|-----------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------|
| B.9       | Men det der nok fik størst indflydelse var, da han kunne hviske mor i øret, at hendes 'Lille Lars' var indstillet til et mindelegat på 500 kr. [But that which probably had the biggest influence was when he could whisper in mother 's ear that her 'little Lars' was nominated for a memorial award of 500 kroner.] | But the biggest influence was probably when he whispered in mother's ear that her 'young Lars' had been nominated for a memorial award of DKK500. | But the probably biggest benefit was when he could whisper in his mother's ear that her "Little Lars" was set for a memorial scholarship of DKK500. |

In TT-1, the ST element 'indflydelse' is rendered by 'influence', which is right. In TT-2, the element is rendered by 'benefit', which is definitely misleading (and the position of the adverbial 'probably' is  also misleading). The genitive pronoun 'his', which is added in front of 'mother's', was also categorised  as  a  blatant  mistranslation:  the  reference  of  'his'  in  TT-2  becomes  the  teacher  (the previously mentioned 'he'), but, if anything, it should have been Larsen himself.

As mentioned, nonsensical translations and blatant mistranslations were only found in TT-2. This is hardly surprising, since TT-2 is an unedited GT translation, while TT-1 is a quality-checked and proofread professional translation.

## 4.3.4 Predefined translation problems

Aiming to zoom in on those ST elements that require human problem-solving and decision-making skills  to  translate,  we  turned  our  attention  to  those  elements  that  we  had  defined  in  advance  as translation problems. The method for this was as follows: If an equivalent for an ST element could not be found that would be useful for fulfilling the skopos, the ST element in question would be defined as a translation problem. In contrast, if an equivalent could be found that would be useful, the  ST  element  would not be  defined  as  a  translation  problem.  Based  on  this,  we  found  63  ST elements that could be predefined as translation problems. Sometimes the same translation problem was found in several segments for similar ST elements, including derivatives or inflections of the same Danish expressions. In such cases, these were counted as one translation problem.

Ten of the 63 translation problems are rendered in similar ways in the two TTs, while 53 are rendered  in  dissimilar  ways.  Similar  and  dissimilar  renditions  were  categorised  by  means  of microstrategies, defined as micro-level transformations of the ST (Molina & Hurtado Albir, 2002; Schjoldager et al., 2010). The microstrategy analysis did not consider dissimilarities due to grave mistakes in TT-2 (see 4.3.3). Grave mistakes may sometimes be explained as failed attempts to solve translation problems. However, since they only occur in TT-2, we find it more likely that they are due to other factors, such as GT's faulty reading of the ST.

The  ten  translation  problems  that  are  dealt  with  in  similar  ways  are  mainly  translated  using microstrategies such as deletion or functional equivalence. The reason for this similarity might be that TT-1 and TT-2 both use standardised ways of dealing with these translation problems. For the 53  translation  problems  that  are  dealt  with  in  dissimilar  ways,  there  are  significant  differences between TT-1 and TT-2 in the use of microstrategies. TT-1 exhibits quite a variety of microstrategies in connection with the translation problems, while TT-2 shows little variety. The microstrategies used in TT-1 are normalisation, generalisation, explicitation, substitution and deletion. TT-2 uses word-for-word direct translation and, in a few cases, copying, deletion and functional equivalence.

We found three categories of translation problems in ST-d:

1. Situation-related  translation  problems :  cultural  and/or  contextual  references  to  institutions, customs, ideas, events, objects etc. that are deemed to be particularly Danish, Jutlandic or JYSKrelated and do not have useful equivalents in English.
2. Style-related translation problems : idiomatic, dialectal or register features in Danish that do not have useful equivalents in English.
3. Language-related translation problems: Danish/Jutlandic-language structures or elements that do not have useful equivalents in English.

Table 5 gives examples of a language-related translation problem ('da') and a style-related translation problem ('den kære Lars Larsen').

Table 5: A language-related translation problem and a style-related translation problem

| Segment   | ST                                                                                                                                                                                                                                                | TT-1                                                                                                                                        | TT-2                                                                                                   |
|-----------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------|
| A.13      | Mange vil måske mene, at nu har han da fået storhedsvanvid - den kære Lars Larsen - og det kan da også godt være. [Many might think that now he is surely suffering from megalomania - the dear Lars Larsen - and that may certainly also be so.] | Many people might think that now he is certainly suffering from delusions of grandeur - the dear Mr Lars Larsen - and that may be the case. | Many may think that now he has gone mad with greatness - the dear Lars Larsen - and it may well be so. |

The two 'da' elements in Table 5 were categorised as language-related translation problems, whereas the  phrase  'den  kære  Lars  Larsen'  [the  dear  Lars  Larsen]  was  categorised  as  a  style-related translation problem. There are many short adverbs in Danish like 'da' that are notoriously difficult to  translate  because the meaning varies  according to context and style.  We  categorised the 'da' elements in A.13 as language-related translation problems, but we could also have categorised them as  style-related. 10 Here  'da'  means something like 'surely' or 'certainly'. In the first  part of the segment, Larsen wishes to emphasise that readers might now think that he is delusional when he expects 2.4 million Danes to be interested in his autobiography. LK has clearly understood Larsen's intentions and translates in due consideration of the skopos. We categorised the microstrategy in connection with the first 'da' element in TT-1 ('certainly') as functional equivalence, while the microstrategy in TT-2 was categorised as deletion. The deletion is quite in line with the way that many translators tend to deal with 'da', especially in formal texts, which may suggest that a pattern of this may be found in GT's dataset. In the second part of segment A.13, the meaning of 'da' is similar, but this time it is used together with the informal phrase 'det kan da også godt være' [that may certainly also be so]. LK translates the phrase into 'that may be the case', deleting both 'da' [certainly] and 'også' [also]. We think LK's translation conveys Larsen's intentions and categorised it  as  functional equivalence. TT-2 translates the phrase into 'it may well be so', which was also categorised as functional equivalence. This indicates that a standardised translation of the phrase may be available in GT's dataset.

Furthermore, Larsen inserts an indirect and ironical reference to himself: 'den kære Lars Larsen' [the dear Lars Larsen]. In TT-1, 'Mr' is added in front of 'Lars Larsen', which we categorised as explicitation. The formal address of 'Mr' is still frequent in English, whereas the Danish equivalent

10  Throughout the book, Larsen uses another short adverb, 'jo', whose meaning can also vary a great deal. Sometimes, in informal use, 'jo' might be translated into 'you know' or 'of course', if something is supposed to be well-known to the receiver already. In more formal use, 'jo' can, for instance, be used to emphasise admission or blame.

'hr.' is nowadays regarded as outdated in most contexts. The reason for LK's explicitation is probably an  attempt to  tailor  the  translation  for  Larsen's  international  readers.  In  TT-2,  the  rendition  was categorised as a word-for-word direct translation.

Table 6 gives examples of a style-related translation problem ('Go'daw') and a situation-related translation problem ('Jeg har et godt tilbud').

Table 6: A style-related translation problem and a situation-related translation problem

| Segment   | ST-d                                                                                                            | TT-1                                               | TT-2                                                 |
|-----------|-----------------------------------------------------------------------------------------------------------------|----------------------------------------------------|------------------------------------------------------|
| Title     | Go'daw jeg hedder Lars Larsen - Jeg har et godt tilbud [ Hello , I'm called Lars Larsen - I have a good offer ] | Hello my name is Lars Larsen - I have a good offer | Go'daw, my name is Lars Larsen - I have a good offer |

The  first  element  in  the  title,  'Go'daw'  [Hello],  was  categorised  as  a  style-related  translation problem, whereas the second element, 'Jeg har et godt tilbud' [I have a good offer] was categorised as a situation-related translation problem. The spelling of 'Go'daw' indicates a dialectal (Jutlandic) and  informal  style.  In  standard  Danish,  the  informal  spelling  is  'go'dav'  [hello]  and  the  formal spelling is 'goddag' [how do you do]. The latter is used as a traditional greeting when people meet. Note that this is not the same as the informal greeting 'god dag' [good day] (two words), which is increasingly used informally when people leave, probably influenced by English: 'have a good day'.

LK  uses  normalisation  and  renders  'Go'daw'  as  'Hello',  which  does  not  have  regional  or dialectal connotations, but the level of formality is probably similar. In TT-2, copying is used, which is nonsensical. As already explained, the segment comprises the main part of the book title and is a reference to Larsen's famous TV commercials, which always started with exactly these words. We therefore regarded the element as a situation-related translation problem. Apart from the translations of  the  first  element  ('Go'daw'), the  renditions  are identical in  the two  TTs. We  categorised  the identical parts as functional equivalence, considering the situational reference to Larsen's Danish commercials, including his Jutlandic pronunciation, which is impossible to convey precisely to an international audience. This means that only the translations of the first ST element contribute to our understanding of differences between the two types of translation.

Table 7 gives examples of a situation-related translation problem ('købmand') and a style-related translation problem ('Gøre').

Table 7: A situation-related translation problem and a style-related translation problem

| Segment   | ST-d                                                                                                                                                                   | TT-1                                                                                       | TT-2                                                                             |
|-----------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------|
| D.8       | Selvfølgelig gælder det om at være den gode købmand . [Of course, it is about being the good tradesman ]                                                               | Of course it is all about being a good businessman,                                        | Of course, it's about being the good grocer.                                     |
| D.9       | Gøre kunden glad for købet og gerne selv have et glimt i øjet. [ To make the customer happy with the purchase and preferably you yourself having a twinkle in the eye] | making the customer happy with their purchase and preferably having a twinkle in your eye. | Make the customer happy with the purchase and like to have a twinkle in the eye. |

The ST element 'købmand' [tradesman] in D.8 was categorised as a situation-related translation problem, while the abrupt use of the infinitive verb form 'Gøre' [To make] in D.9 was categorised as a style-related translation problem. Table 7 also illustrates a strategy that is used sometimes in TT-

1, but never in TT-2, namely an amalgamation of two interconnected segments. This shows LK's awareness of Larsen's intentions and a consideration for readability.

As mentioned, Larsen preferred to use the title of 'købmand' [tradesman] rather than that of CEO, and he also made sure that it was included as the first of JYSK's three keywords. We categorised 'købmand'  and  the  derivative  'købmandskab'  [tradesmanship]  as  situation-related  translation problems  because  they  describe  an  important  part  of  Larsen's  image  and  also  characterise  his business approach, but they may also be seen as language-related translation problems: 'købmand' mostly means 'grocer', the owner of a small business that sells groceries, but it may also mean 'merchant'  or  'tradesman',  which  are  more  general.  While  none  of  these  can  be  regarded  as equivalents  of  'købmand'  in  Larsen's  case,  'tradesman',  with  its  modest  connotations  of 'shopkeeper' or 'salesman', might be the closest.

LK  translates  'købmand'  into  'businessman'  and  'købmandskab'  into  'businessmanship', which shows that she was very aware of Larsen's intentions and translates in due consideration of the skopos. LK also makes sure that 'købmand' and its derivatives are translated in the same way throughout the book, ensuring intratextual coherence (Vermeer's second rule). This is not the case for  TT-2,  where  these  elements  are  translated  in  different  ways  in  chapter  D.:  The  'købmand' elements  are  translated  into  'merchant'  (D.1.  and  D.6.)  or  'grocer'  (D.8),  while  the  derivative 'købmandskab'  is  translated  into  'merchandising'  (D.  18).  While  LK's  translations  of  these elements were categorised as functional equivalence, the translations in TT-2 were categorised as direct  word-for-word  translations,  but  'grocer'  and  'merchandising'  were  also  marked  as nonsensical. We think Table 7 shows essential differences between TT-1 and TT-2.

## 5. Concluding remarks

The  paper  aims  to  contribute  to  a  necessary  discussion  concerning  the  conceptualisation  of professional translation in the posthuman age, when professional translation is increasingly carried out by means of advanced translation technology. The aim of the case study was to ascertain the extent to which GT may reach human translation quality. Within a skopos-theoretical framework, selected parts of a professional English-language translation of Larsen's unique autobiography (TT1), completely unaided by technology, was compared with a GT-generated translation into English (TT-2) of the same parts. The perceived skopos of the professional translation was identified as translating  in  such  a  way  that  a  function  similar  to  that  of  the  ST  was  achieved,  indicating  an instrumental translation. Though large parts of TT-2 are similar to TT-1, we cannot conclude that the perceived skopos is achieved by TT-2. This was particularly clear in connection with many instances of contextually and culturally embedded meaning in Larsen's book. As anticipated, GT proved to be particularly challenged by these.

The conclusions of the comparative analyses may be summarised like this:

1. In line with Blum-Kulka's explicitation hypothesis, implicit elements are explicated in both TTs, though more so in TT-1. The explicitations might explain why both are a little longer than the source-text data (ST-d).
2. Nearly two thirds of TT-2 are sufficiently similar to TT-1 for us to conclude that these parts of TT-2 would need no or little post-editing before publication, meaning that TT-2 reaches human quality in these parts.
3. A little more than one third of TT-2 is sufficiently dissimilar to TT-1 for us to conclude that these parts of TT-2 would need extensive post-editing before publication, meaning that TT-2 does not reach human quality in these parts.
4. Grave  mistakes,  categorised  as  nonsensical  translations  or  blatant  mistranslations,  were  only found  in  TT-2.  We  conclude  that  these  are  caused  by  factors  that  are  difficult  to  ascertain, including a GT failure to read ST elements.

5. Attempting to focus on those ST elements that require a human capacity for problem-solving, we identified ST items that could be categorised as situation-related, style-related or language-related translation  problems.  When  solving  these,  TT-1  clearly  complies  with  professional  ethics, including loyalty towards the sender, and with Vermeer's hierarchical rules concerning skopos, intratextual coherence and ST/TT fidelity. This is not the case for TT-2. Furthermore, TT-1 uses a variety of microstrategies to solve the identified translation problems, whereas TT-2 mostly applies word-for-word direct translation or deletion, which mostly do not solve the problems.

One explanation for the poorer results for GT is that, unlike a professional translator, GT does not understand text in the real sense of the word, does not work situationally and goal-oriented and does not base decisions on professional expertise and ethics. However, though GT (and other NMTs) may not deliver human quality at the moment, we must accept that powerful AI tools will increasingly be able to deliver high-quality translation output. Lately, though not purpose-built to translate, AI-based generative models like OpenAI's ChatGPT are reported to outperform NMTs and deliver human translation quality (Timothy, 2023). Translations generated by such models happen in an interactive process, in which users can prompt the system with contextual information and strategic instructions. Be that as it may, we argue that the conceptualisation of professional translation and professional translation quality criteria must remain the same, regardless of who translates and regardless of which tools are used.

## References

- Aguilar,  R.  (2023).  How  Accurate  is  Google  Translate. Weglot .  https://www.weglot.com/blog/how-accurate-is-googletranslate
- Axelsen, J. (2010). Gyldendals røde ordbøger: Engelsk-dansk ordbog 12. udgave (12th ed.). Gyldendal.
- Bager, P. (2005). The Duvet King of Denmark. A Fairy-tale about a crack-brained businessman from North Jutland. Nordisk Litteratur - Nordic Literature , 178-180.
- Bayer-Hohenwarter, G., & Kussmaul, P. (2020). Translation, Creativity and Cognition. In F. Alves & A. Lykke Jakobsen (Eds.), The Routledge Handbook of Translation and Cognition 1st. ed. (pp. 310-325). Routledge.
- Blum-Kulka, S. (1986). Shifts of Cohesion and Coherence in Translation. In J. House & S. Blum-Kulka (Eds.), Interlingual and Intercultural Communication: Discourse and cognition in translation and second language acquisition studies (pp. 17-35). Gunter Narr.
- Christensen,  T.  P.,  Bundgaard, K.,  Schjoldager,  A.,  &  Dam  Jensen,  H.  (2022).  What  Motor  Vehicles  and  Translation Machines  Have  in  Common-A  first  step  towards  a  translation  automation  taxonomy. Perspectives.  Studies  in Translation Theory and Practice , 30 (1), 19-38.
- Economist,  T.  (2017a,  19  June).  TECHNOLOGY  QUARTERLY.  FINDING  A  VOICE  -  Language  finding  a  voice. Economist , 32 pages. https://www.economist.com/technology-quarterly/2017-05-01/language
- Economist, T. (2017b, 29 April). Translation platforms cannot replace humans. Economist . https://www.economist.com/books-and-arts/2017/04/29/translation-platforms-cannot-replace-humans
- European Parliament and the Council of the European Union (2016). European Parliament and the Council of the European Union of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) .  https://gdprinfo.eu/
- Forcada Zubizarreta, M. L. (2022a, 06.07.2022). Licenses and usage rights of linguistic data in machine translation . Paper at NeTTT (New Trends in Translation and Technology), Rhodes.
- Forcada Zubizarreta, M. L. (2022b). Machine translation . AIETI, the Iberian Association for Translation and Interpreting Studies. https://www.aieti.eu/enti/machine\_translation\_ENG/entry.html
- Frey,  C.  B.,  &  Osborne,  M.  A.  (2017).  The  future  of  employment:  How  susceptible  are  jobs  to  computerisation? Technological Forecasting and Social Change , 114 (January), 254-280. https://www.sciencedirect.com/science/article/abs/pii/S0040162516302244
- Grady, J. (1998). The 'Conduit Metaphor' Revisited: a Reassessment of Metaphors for Communication. In J.-P. Koenig (Ed.), Discourse and cognition: bridging the gap (pp. 1-16). CSLI Publications.
- Guerberof Arenas, A., & Asimakoulas, D. (2023). Creative skills development: training translators to write in the era of AI. Hermes - Journal of Language and Communication in Business (63), 227-243.

https://tidsskrift.dk/her/issue/view/10431

- Guerberof Arenas, A., & Toral, A. (2022). Creativity in translation: machine translation as a constraint for literary texts. Translation Spaces , 11 (2), 184-212.
- Hassan, H., Aue, A., Chang, C., Chowdhary, V., Clark, J., Federmann, C., Huang, X., Junczys-Dowmunt, M., Lewis, W., Li,  M.,  Liu,  S.,  Liu,  T.-Y.,  Luo,  R.,  Menezes,  A.,  Qin,  T.,  Seide,  F., Tan,  X.,  Tian,  F.,  Wu,  L., Zhou,  M.  (2018). Achieving Human Parity on Automatic Chinese to English News Translation. microsoft.com .

https://www.microsoft.com/en-us/research/uploads/prod/2018/03/final-achieving-human.pdf

- Hofstadter, D. (2018). The Shallowness of Google Translate. The Atlantic .

https://www.theatlantic.com/technology/archive/2018/01/the-shallowness-of-google-translate/551570/

- Holz-Mänttäri, J. (1984). Translatorishes Handeln: Theorie und Metode . Suomalainen Tiedeakatemia.
- ISO International Organization for Standardization. (2015). ISO 17100:2015 Translation services  - Requirements for translation services (amended 2020). 19. https://www.iso.org/standard/59149.html#amendment
- Jakobson, R. (1960/1981). Linguistics and Poetics. In Volume III Poetry of Grammar and Grammar of Poetry (pp. 18-51). De Gruyter Mouton. https://www.degruyter.com/document/doi/10.1515/9783110802122.18/html#Chicago
- Kassebeer,  S.  (2004).  Dyne-Larsen  er  landets  mest  læste. Berlingske .  https://www.berlingske.dk/kultur/dyne-larsen-erlandets-mest-laeste
- Language Connections. (n.d.). The Pros and Cons of Google Translate . https://www.languageconnections.com/blog/thepros-cons-of-google-translate/
- Larsen,  L.  (2004a). Go'daw  jeg  hedder  Lars  Larsen:  jeg  har  et  godt  tilbud  -  en  selvbiografi .  Hansen  Mejlgade. https://ipaper.ipapercms.dk/jysk/dk/larsen/2dde2572\_46be\_4ca4\_83d9\_7170549a66c9/?page=24#/
- Larsen,  L.  (2004b). Hello  my  name  is  Lars  Larsen:  I  have  a  good  offer  -  an  autobiography .  Hansen  Mejlgade. https://campaign-paper.jysk.co.uk/larsen/ab46b5f6\_4f5f\_4d61\_9100\_f687729f52d1/
- Laugesen, G. (1999, 28 September). Den jyske mafia. Information . https://www.information.dk/1999/09/jyske-mafia
- Lee, Q. V., & Schuster, M. (2016). A Neural Network for Machine Translation, at Production Scale. Research Google blog . https://research.google/blog/a-neural-network-for-machine-translation-at-production-scale/
- Läubli, S., Sennrich, R., & Volk, M. (2018). Has Machine Translation Achieved Human Parity? A Case for Documentlevel Evaluation . Conference on Empirical Methods in Natural Language Processing, October 31 - November 4, 2018, Brussels, Belgium.
- Macken, L.,  Brussel,  L.  V.,  &  Daems,  J.  (2019).  NMT's  wonderland  where  people  turn  into  rabbits.  A  study  on  the comprehensibility of newly invented words in NMT output. Computational Linguistics in the Netherlands Journal , 9 , 67-80. https://biblio.ugent.be/publication/8639616/file/8639617.pdf
- Massey,  G.  (2021).  Re-framing  conceptual  metaphor  translation  research  in  the  age  of  neural  machine  translation: Investigating translators' added value with products and processes. Training, Language and Culture , 5 (1), 37-56.
- Molina, L., & Hurtado Albir, A. (2002). Translation Techniques Revisited: A Dynamic and Functionalist Approach. Meta (Montréal) , 47 (4), 498-512.
- Moorkens, J., & Lewis, D. (2020). Copyright and the re-use of translation as data. In M. O'Hagan (Ed.), The Routledge Handbook of Translation and Technology (pp. 469-481). Routledge.
- Mossop, B., Teixeira, C., & Hong, J. (2020). Revising and editing for translators (Fourth edition. ed.). Routledge.
- Munday, J., Blakesley, J., & Pinto, S. R. (2022). Introducing translation studies: theories and applications (Fifth edition. ed.). Routledge.
- Nida, E., & Taber, C. R. (1974). The Theory and Practice of Translation . Published for the United Bible Societies, E.J. Brill.
- Nord, C. (2005a). Text Analysis in Translation. Theory, Methodology, and Didactic Application of a Model for TranslationOriented Text Analysis . Rodopi.
- Nord, C. (2005b). Translating as a purposeful activity: A prospective approach. TradTerm , 11 , 15-28. http://www.revistas.usp.br/tradterm/article/view/49673/53784
- Nord, C. (2018). Translating as a Purposeful Activity 2nd Edition . Routledge Taylor & Francis Group.
- O'Brien, S., & Ehrensberger-Dow, M. (2020). MT Literacy - A cognitive view. Translation, Cognition & Behavior , 3 (2), 145-164.
- O'Thomas, M. (2017). Humanum ex machina: Translation in the post-global, posthuman world. Target: International Journal of Translation Studies , 29 (2), 284-300.

https://www.academia.edu/33884086/Humanum\_ex\_machina\_Translation\_in\_the\_post\_global\_posthuman\_world

- Olohan,  M.,  &  Baker,  M.  (2000).  Reporting  that  in  translated  English.  Evidence  for  subconscious  processes  of explicitation? Across Languages and Cultures , 1 (2), 141-158.
- Oxford English Dictionary. (2023). translate, v. In Oxford English Dictionary .

- Pym,  A.,  &  Torres-Simón,  E.  (2021).  Is  automation  changing  the  translation  profession. International  journal  of  the sociology of language (IJSL) , 39-57.
- Ramati, I., & Pinchevski, A. (2018). Uniform multilingualism: A media genealogy of Google Translate. New media & society , 20 (7), 2550-2565.
- Reiss, K., & Vermeer, H. J. (1984). Grundlegung einer allgemeinen Translationstheorie [Towards a General Theory of Translational Action]. Niemeyer.
- Samuelsson-Brown,  G.  (2006).  Translation:  Profession.  In  K.  Brown  (Ed.), Encyclopedia  of  Language  &  Linguistics (Second Edition) (pp. 89-92). Elsevier.
- Schjoldager, A., Gottlieb, H., & Klitgård, I. (2010). Understanding Translation (1st ed., 2nd print-run) . Academica/Hans Reitzels Forlag.
- Taivalkoski-Shilov, K., & Koponen, M. (2023). Literary Post-editing and the Question of Copyright. Hermes - Journal of Language and Communication in Business (63), 196-207. https://tidsskrift.dk/her/issue/view/10431
- Tetzlaff, M. (2004/2019). Anmeldelse: Go'daw, jeg hedder Lars Larsen - Jeg har et godt tilbud. Politiken (24 March 2004/19 August 2019).
- Tieber, M. (2022). Perfect MT and the Concept of Translation. Abstract HAL panel at NeTTT Conference, 4-6 July 2022, Rhodes Island, Greece. https://slator.com/nettt-international-conference-set-for-4-6-july-2022-in-rhodes-greece/
- Timothy, M. (2023). How to Use ChatGPT as a Language Translation Tool. MakeUseOf (MUO) . https://www.makeuseof.com/how-to-translate-with-chatgpt/
- Toral,  A.,  &  Way,  A.  (2018).  What  Level  of  Quality  can  Neural  Machine  Translation  Attain  on  Literary  Text?  In  J. Moorkens, S. Castilho, F. Gaspari, & S. Doherty (Eds.), Translation Quality Assessment. From Principles to Practice . Springer. https://arxiv.org/abs/1801.04962
- Turovsky,  B.  (2016).  Ten  years  of  Google  Translate. Google The  Keyword .  https://blog.google/products/translate/tenyears-of-google-translate/
- Vermeer, H. J. (1989/2000). Skopos and Commission in Translational Action. In L. Venuti (Ed.), The Translation Studies Reader (pp. 221-232). Routledge.
- Vincent, J. (2019). Google's head of translation on fighting bias in language and why AI loves religious texts. An interview with  Google's  Macduff  Hughes. The  Verge .  https://www.theverge.com/2019/1/30/18195909/google-translate-aimachine-learning-bias-religion-macduff-hughes-interview
- Wikipedia. (2023). Google Translate . https://en.wikipedia.org/wiki/Google\_Translate

Hello

Go'daw

## Appendices

## Appendix 1: Front page - Danish version (Larsen, 2004a)

An autobiography by Lars Larsen

En selvbiografi af Lars Larsen

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Appendix 2: Front page - English version (Larsen, 2004b)

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