Generative AI, Pragmatics, and Authenticity in Second Language Learning
This highlights a critical problem for educators and learners in second language acquisition and intercultural communication, as it points out inherent flaws in AI's ability to replicate human social awareness, making it an incremental critique of existing AI applications.
The paper addresses the limitations of generative AI in second language learning, noting that AI systems like ChatGPT often fail to produce pragmatically appropriate language due to lack of lived experience and biases from English-dominated training data, which restricts their suitability for authentic language interactions.
There are obvious benefits to integrating generative AI (artificial intelligence) into language learning and teaching. Those include using AI as a language tutor, creating learning materials, or assessing learner output. However, due to how AI systems under-stand human language, based on a mathematical model using statistical probability, they lack the lived experience to be able to use language with the same social aware-ness as humans. Additionally, there are built-in linguistic and cultural biases based on their training data which is mostly in English and predominantly from Western sources. Those facts limit AI suitability for some language learning interactions. Stud-ies have clearly shown that systems such as ChatGPT often do not produce language that is pragmatically appropriate. The lack of linguistic and cultural authenticity has important implications for how AI is integrated into second language acquisition as well as in instruction targeting development of intercultural communication compe-tence.