Artificial intelligence contribution to translation industry: looking back and forward

TL;DR

This comprehensive 45-year analysis examines AI's evolving role in the translation industry, highlighting trends, hotspots, and challenges, especially with neural models and large language models like ChatGPT.

Contribution

It provides a detailed scientometric and thematic review of AI's impact on translation research, emphasizing recent developments and future challenges in the field.

Findings

AI significantly advances translation industry with neural networks and large language models.

Research hotspots include machine translation, low-resource languages, and neural models.

Ongoing challenges involve low-resource languages, dialects, and cultural nuances.

Abstract

This study provides a comprehensive analysis of artificial intelligence (AI) contribution to research in the translation industry (ACTI), synthesizing it over forty-five years from 1980-2024. 13220 articles were retrieved from three sources, namely WoS, Scopus, and Lens; 9836 were unique records, which were used for the analysis. We provided two types of analysis, viz., scientometric and thematic, focusing on Cluster, Subject categories, Keywords, Bursts, Centrality and Research Centers as for the former. For the latter, we provided a thematic review for 18 articles, selected purposefully from the articles involved, centering on purpose, approach, findings, and contribution to ACTI future directions. This study is significant for its valuable contribution to ACTI knowledge production over 45 years, emphasizing several trending issues and hotspots including Machine translation, Statistical machine translation, Low-resource language, Large language model, Arabic dialects, Translation quality, and Neural machine translation. The findings reveal that the more AI develops, the more it contributes to translation industry, as Neural Networking Algorithms have been incorporated and Deep Language Learning Models like ChatGPT have been launched. However, much rigorous research is still needed to overcome several problems encountering translation industry, specifically concerning low-resource, multi-dialectical and free word order languages, and cultural and religious registers.