C hat GPT for translators: a survey (2023)

Abstract: This article surveys the most important ways in which translators can use ChatGPT. The focus is on scenarios where ChatGPT supports the work of translators, rather than tries to replace them. A discussion of issues that translators need to consider when using large language models, and ChatGPT in particular, is also provided.

## introduction chatgpt is a conversational agent based on a large language model (llm) specifically trained to enable users to have conversations on a broad range of topics in a desired format, style and language. even though open.ai released chatgpt only at the end of november 2022, in less than 2 months it reached over 100 million users being considered the fastest growing consumer application @xcite . the emergence of chatgpt may seem to the majority of the general population out of nowhere, but open.ai has generated headlines in mainstream media in 2020 with gpt3, a large language model which is a predecessor of chatgpt. because gpt3 was able to generate texts in english that are difficult to distinguish from those written by humans, there was a general fear that it could be misused to generate misinformation, abuse, or produce student essays. chatgpt was built on top of gpt3.5, and more recent versions on gpt4, and part of its success comes from the fact that it operates a "freemium model" which means that many of its features can be accessed for free. this is in contrast to gpt3 which was available only to a limited number of users via an api. the fact that chatgpt can conduct conversations in many languages widened its user base. one of the sections of this survey will provide a brief overview of how chatgpt has been trained to perform better than its predecessors and give a non-technical explanation of how it works. recent months have seen a flurry of blog posts, youtube videos and an increasing number of scientific articles which discuss a wide range of uses of chatgpt from advice for healthy eating 1 and getting rich 2 to how to use chatgpt to support and replace people in their jobs. 3 the fact that chatgpt can handle multilingual text and can translate between languages attracted the attention of the translation industry, leading to renewed predictions that translators will be replaced by computers in the near future. the purpose of this article is to provide an overview of how chatgpt can be used by translators as a support tool and to discuss whether translators should be afraid of chatgpt. while writing this article, it was difficult to decide which sources to use. there are numerous posts on social media and self-published articles on arxiv which can be relevant. however, because some are not peer-reviewed in any way, at times, their analysis is superficial and they contain speculations which are not supported by any data. for this reason, i will refer mainly to articles that have been published in peer-reviewed journals and conference proceedings, and to arxiv articles and posts that have generated enough discussion to consider that they were peer-reviewed in an informal manner. reports from market research companies like common sense advisory foot_0 and nimdzi foot_1 were also used to inform this survey. ## translation-related uses of chatgpt the rest of this extended abstract will briefly present the topics to be discussed in the full survey. a common theme throughout these topics is that chatgpt should not be considered a tool that produces texts which can be used without human revision/checking. instead it is seen as a powerful tool that supports, rather than replaces, its users (translators in the context of this article). ## discussion and conclusions this extended abstract has discussed a few scenarios in which chatgpt could prove useful for translators. the focus was on the application and output of chatgpt. however, in addition to this, there are numerous other issues that should be considered when translators use chatgpt such as privacy, hallucinations, speed and costs. all these issues will be discussed in the full survey. the success of open.ai with chatgpt has pushed other companies like google and meta to release their own products and led to the availability of numerous large language models of different sizes and developed for different purposes. open sourced models like meta's llama-2 are currently used by the research community to develop tools that can help translators either by translating content or by assessing the quality of translations. it is very likely that in the near future we will see tools based on llms that are more appropriate for translation scenarios, but they will require more specialised expertise.