Large Language Models And The Future Of AI Translation: Opportunities And Obstacles

Abstract

In recent years, the rise of artificial intelligence (AI) technology has transformed the way we interface with digital systems. This study investigates the perceptions of  Qassim University LLMs users regarding the opportunities, challenges, and future of LLMs in multilingual translation. This study used a quantitative approach by employing a questionnaire of LLMs. The findings reveal that the participants acknowledge significant advantages of LLMs in speed, cost-effectiveness, and contextual handling, while simultaneously highlighting limitations in cultural understanding and idiomatic expression. The research underscores the necessity of balancing LLM efficiency with the irreplaceable role of human expertise. Findings indicate a collaborative future for LLMs in translation, serving as support tools rather than replacements. Notably, gender significantly influences future outlook, with females exhibiting greater optimism. However, educational level and age show no significant impact. This study emphasizes the need for a nuanced integration of LLMs, recognizing both their transformative potential and inherent limitations to ensure accurate and culturally sensitive communication.