Impact of Large Language Model on the Translation Profession: Opportunities and Challenges for Human Translators - Senapa, Charit; Sattayaporn, Pannatee; Samrittitanon, Lalita (Chophayom Journal, 2024)
This study examines the role of Large Language Model (LLM) AI in translation, focusing on its capabilities and the potential risks it poses to human translators. LLM, a form of artificial intelligence trained on massive datasets across multiple languages, has shown significant proficiency in natural language processing and translation tasks. This has led to increased reliance on LLM for translation across various professions, raising concerns about the displacement of human translators. The study investigates the advantages and disadvantages of LLM in translating texts between Thai and English comparing to human translators. Despite the AI’s remarkable speed and ability to handle over 100 languages, challenges remain in ensuring cultural appropriateness, linguistic consistency, and contextual understanding. Additionally, the study highlights the potential biases in AI outputs and the risk of hallucinations—where AI generates plausible but incorrect translations. Human translators are found to have an edge in handling complex, context-dependent tasks and maintaining high-quality translations. However, LLM’s ability to quickly produce translations makes it a competitive alternative, especially for large-scale, general-purpose translation tasks. The study concludes with recommendations for translators to adapt by developing specialized skills, embracing continuous learning, and leveraging AI tools to enhance their work. Keywords: Large Language Model, AI translation, translation quality, human translators, natural language processing