Artificial Intelligence and Translation

Since the concept of artificial intelligence (AI) was first proposed in 1956, more than half a century has passed. In the 21st century, AI has been widely applied across various fields such as healthcare, finance, and education, becoming an indispensable part of people's lives. With the rapid development of AI, the future of human translation has also become a hot topic, with many discussing whether "artificial intelligence will replace human translation." But is this really the case?

It is undeniable that as AI continues to evolve, machine translation systems appear to be becoming increasingly sophisticated. Tools like Baidu Translate, Youdao Translate, and Sogou Translate keep emerging, allowing users to easily switch between languages with just a smartphone. In a modern society characterized by a fast-paced lifestyle and increasing financial pressures, these tools, which are free and time-saving, are undoubtedly the preferred choice for certain groups of people and businesses.

However, while AI brings convenience and speed, it also comes with its own set of problems. The primary issue lies in the accuracy of translations. The most noticeable feature of AI is that it is a machine, and this is also its greatest weakness. Unlike humans, machines lack practical abilities, sources of experience, and the ability to contextualize their translations, which poses significant challenges to their accuracy. For example, in Japanese, "いいです" is commonly translated by machines as "can" or "good." However, in a specific dining context, its meaning can change. When A asks, “ビールも飲みますか” (Are you also drinking beer?), and B replies, “いいです,” the actual implication is "no, thank you" or "that's enough." This illustrates that the same sentence can convey completely different meanings depending on the context. While human translators rely on common knowledge and the specific context for their translations, machines can only provide rigid translations, which have considerable limitations.

Furthermore, machines lack the ability to discern and create beauty compared to human translators, resulting in a lesser quality in translation. Yan Fu, a famous translator, once proposed three standards for translation: "faithfulness, expressiveness, and elegance." This means that the translated text should be accurate, without deviations or omissions, coherent, and elegant in word choice, pursuing the inherent grace of the text itself. While machines can generally meet the requirements of faithfulness and expressiveness, achieving a level of elegance is significantly more challenging. In other words, machines can only perform literal translations; reaching the standards of interpretive translations still requires skilled human translators.

Lastly, the backbone of machine language translation is the vast existing corpus of data. However, with the accelerating pace of globalization, the demand for minority languages and the specialized translation standards of some industries are areas where machine translation falls short.

Many people believe that the emergence of AI will inevitably replace human labor, leading to increased unemployment and impacting certain industries. However, every situation has its pros and cons; the rise of AI can be seen as both an opportunity and a challenge. While machine translation offers its own conveniences, human translation possesses irreplaceable qualities. Translators can leverage machines to handle simpler translation tasks, saving time and improving efficiency, and thereby focus more energy on professional translations, ultimately achieving a win-win situation.

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