# Generative AI, Pragmatics, and Authenticity in Second Language Learning

arXiv: https://arxiv.org/abs/2410.14395 · HTML: https://mlsanity.com/paper/2410.14395/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 69 references that are in the map.
- First posted on arXiv 18 Oct 2024.

## Builds on (most cited first, 10 of 10)

- [Role-Play with Large Language Models](https://mlsanity.com/paper/2305.16367/) (2023)
- [Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study](https://mlsanity.com/paper/2303.17466/) (2023)
- [Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://mlsanity.com/paper/2305.14456/) (2023)
- [Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions](https://mlsanity.com/paper/2309.12342/) (2023)
- [The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs](https://mlsanity.com/paper/2210.14986/) (2022)
- [Not All Countries Celebrate Thanksgiving: On the Cultural Dominance in Large Language Models](https://mlsanity.com/paper/2310.12481/) (2023)
- [How do you Converse with an Analytical Chatbot? Revisiting Gricean Maxims for Designing Analytical Conversational Behavior](https://mlsanity.com/paper/2203.08420/) (2022)
- [Language Writ Large: LLMs, ChatGPT, Grounding, Meaning and Understanding](https://mlsanity.com/paper/2402.02243/) (2024)
- [ChatGPT Role-play Dataset: Analysis of User Motives and Model Naturalness](https://mlsanity.com/paper/2403.18121/) (2024)
- [The Human and the Mechanical: logos, truthfulness, and ChatGPT](https://mlsanity.com/paper/2402.01267/) (2024)

## Abstract (arXiv)

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.