When AI enters translation classroom: The ethical questions we cannot ignore (1-2) - Egyptian Gazette

By Mahmoud Kamel

Artificial intelligence (AI) is changing how translation is taught. It is not just because AI can translate texts. It is also changing how students learn, how teachers assess their work and how universities understand academic honesty. Tools such as ChatGPT are becoming better at producing smooth, natural translations. This raises an important question: How can we prepare future translators to use AI well without losing the skills, good judgment and sense of responsibility they need as professionals?

Chapter 10 of Translation Studies in the Age of Artificial Intelligence, written by Bo Li and Yuan Liu, explores this question from an ethical point of view. Instead of treating AI as just another tool that students need to learn, the authors examine the wider problems it creates for translation education. These include academic honesty, fair assessment, unequal access to technology, being open about AI use and translators taking responsibility for the texts they produce.

The chapter makes an important point. The main challenge is not simply deciding whether students should be allowed to use AI. It is creating clear rules that protect the value of education while preparing students for a profession where technology is becoming more and more important.

When translation assignments are no longer what they seem

For many years, translation teachers have tested students by asking them to translate a text from one language into another. The finished translation was expected to show that the student understood the original text, had good language skills, could do research and could make suitable choices.

Generative AI has made this process more difficult. Students can now hand in smooth translations created partly or entirely by AI. Teachers may find it hard to tell how much of the work shows the student's own ability and how much was produced by the machine.

This creates problems for both teaching and assessment. If a student hands in a translation made almost entirely by AI, the finished text may not show what the student has actually learned. However, it would also be wrong to say that every use of AI is cheating. Translators have always used dictionaries, reference books, databases of specialist terms and computer-assisted translation tools.

The key question is where to draw the line between using a tool to help with learning and letting that tool do the learning for the student. A student who uses AI to compare different translations, explore a difficult expression or find weaknesses in a draft may learn useful skills. But a student who simply hands in the machine's work without checking it may finish the assignment without learning the skills they need.

For this reason, general rules about plagiarism may not be enough. Translation courses need clear guidance that considers the special nature of translation work and the different goals of classroom exercises, exams and graduation projects.

The problem with simply banning AI

Some universities have responded to generative AI by limiting or banning its use in student assignments. This may seem like a simple solution, especially when teachers are worried about academic dishonesty.

However, a complete ban can create its own problems. AI is already becoming part of professional translation, and graduates will need to know how to work with it. If students cannot use these tools during their studies, they may leave university without the knowledge they need to work well in a profession that is changing.

The authors describe a gradual move towards more balanced policies in higher education. Instead of treating every use of AI as wrongdoing, universities can set clear conditions for using it responsibly. These rules should explain which tasks allow AI help, which tasks students must complete on their own and what students need to say about how they used these tools.

Translation education needs this kind of clear, practical approach. Students should understand not only what they are allowed to do, but also why some kinds of help are acceptable while others defeat the purpose of an assignment.

AI should not become an easy way for students to avoid learning. At the same time, universities should not ignore a technology that is already changing the professional world they are preparing their students to enter.

Dr Mahmoud Kamel is Professor at the Academy of Arts