{"title":"Defending the last bastion","authors":"Hongtao Wang","doi":"10.1075/babel.00330.wan","DOIUrl":null,"url":null,"abstract":"\n Growing interest has been noted in applying AI-powered machine translation (MT) to literary translation, hailed as\n the last bastion of human translation. Despite achieving considerable progress in this field, research has either ignored or\n underestimated the particularity, complexity, and cultural significance of literary translation, which can be examined from a\n sociological approach. Drawing on the sociological theories of Bourdieu, Latour, Callon, and Baudrillard, the present paper\n analyses the innate nature of literary translation and highlights three fundamental issues that need to be addressed in applying\n MT to literary texts. First, the poetics of literary translation is built on human translators’ long-acquired habitus, thus, in\n the case of MT, an algorithm comparable to the creative human habitus must be derived if MT aspires to take on the role of the\n human translator. Second, literary translation constitutes a dynamic network connected by various human and non-human actors, thus\n the aspects not included in the interlingual transference of MT should be compensated through more effective interactions between\n the machine and other actors. Third, the cultural-ethical issues related to MT should be thoroughly examined because the present\n MT of literary texts is a machine simulation of the psychological human translation, which undermines both the meaning generation\n of literary translation and the knowledge accumulation of cultural production. Therefore, literary translation must be handled by\n qualified human translators until we can undoubtedly ensure that MT can be effectively and safely applied to literary texts.","PeriodicalId":44441,"journal":{"name":"Babel-Revue Internationale De La Traduction-International Journal of Translation","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Babel-Revue Internationale De La Traduction-International Journal of Translation","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1075/babel.00330.wan","RegionNum":4,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
引用次数: 0
Abstract
Growing interest has been noted in applying AI-powered machine translation (MT) to literary translation, hailed as
the last bastion of human translation. Despite achieving considerable progress in this field, research has either ignored or
underestimated the particularity, complexity, and cultural significance of literary translation, which can be examined from a
sociological approach. Drawing on the sociological theories of Bourdieu, Latour, Callon, and Baudrillard, the present paper
analyses the innate nature of literary translation and highlights three fundamental issues that need to be addressed in applying
MT to literary texts. First, the poetics of literary translation is built on human translators’ long-acquired habitus, thus, in
the case of MT, an algorithm comparable to the creative human habitus must be derived if MT aspires to take on the role of the
human translator. Second, literary translation constitutes a dynamic network connected by various human and non-human actors, thus
the aspects not included in the interlingual transference of MT should be compensated through more effective interactions between
the machine and other actors. Third, the cultural-ethical issues related to MT should be thoroughly examined because the present
MT of literary texts is a machine simulation of the psychological human translation, which undermines both the meaning generation
of literary translation and the knowledge accumulation of cultural production. Therefore, literary translation must be handled by
qualified human translators until we can undoubtedly ensure that MT can be effectively and safely applied to literary texts.