Artificial intelligence and human translation: A contrastive study based on legal texts

Abstract

Artificial intelligence has advanced significantly in recent years, affecting multiple aspects of life. In particular, this has had an impact on the machine translation of texts, reducing or removing human interaction. Artificial intelligence (AI)-based translation software models have thus become widely available, and these now include Google Translate, Bing, Microsoft Translator, DeepL, Reverso, Systran Translate, and Amazon Translate. Several computer-aided translation (CAT) tools such as Memoq, Trados, Smartcat, Lokalise, Smartling, Crowdin, TextUnited, and Memsource are also available. More recently, artificial intelligence has been applied in the development of applications such as ChatGPT, ChatSonic, GPT-3 Playground, Chat GPT 4 and YouChat, which simulate conversational responses to researchers' inquiries, mimicking human interactions more directly. This study thus aimed to examine any remaining contrasts between human and AI translation in the legal field to investigate the potential hypothesis that there is now no difference between human and AI translation. The paper thus also examined concerns about whether the need for human translators will decline in the face of AI development, as well as beginning to assess whether it will ever be possible for those in the legal field to depend only on machine translation. To achieve this, a collection of legal texts from various contracts was chosen, and these pieces were both allocated to legal translators and subjected to AI translation systems. Using a contrastive methodology, the study thus examined the differences between AI and human translation, examining the strengths and weaknesses of both approaches and discussing the situations in which each approach might be most effective.