Research Article

AI Translation Tools vs Human Translators: User Satisfaction and Accuracy Perceptions

Abstract

The growing availability of translation tools that utilize artificial intelligence (AI) has revolutionized multilingual communication as far as fast, convenient, and inexpensive translation is concerned. While there have been numerous advancements made in machine translation technologies, issues concerning satisfaction level and accuracy of the translation performed by such tools have persisted when compared to human translators. Therefore, this study seeks to examine and compare user satisfaction and perception between AI translation tools and human translators regarding the accuracy, reliability, readability, and quality of the translation process. In this case, a survey quantitative comparative research design was adopted by surveying language learners, professional translators, students, educators, and other users of translation services. Respondents were required to provide opinions on the quality of translation done by both the translation tool and human translator using a questionnaire that used a five-point Likert scale. Statistical tests were performed to reveal possible differences in user satisfaction and perception between the two forms of translation. The results show that the use of AI translation tools is favored due to the speed and convenience, translating into user satisfaction especially for simple routine translation tasks. However, there were noticeable disparities in perception of translation accuracy and reliability, with satisfaction varying according to the type of translation required. The findings of this paper add to the literature concerning the application of artificial intelligence in linguistic processes. The results show that the use of AI in translation facilitates easy translation processes, especially when dealing with normal conversations. On the other hand, the involvement of human translators is key in achieving accuracy and quality of translation services. The results of this paper have many applications in translation companies, language training institutions, and technology firms that focus on developing artificial intelligence systems for language applications.