Economics research seminar: Nathan Kettlewell, University of Technology Sydney

Large language models (LLMs) have altered the nature of academic writing. While the influence of LLMs on academic writing is not uncontroversial, one promise for this technology is to bridge language barriers faced by nonnative English-speaking researchers.

This study empirically demonstrates that LLMs have led to convergence in the lexical diversity of native and nonnative speakers, potentially helping to level the playing field. There has also been an increase in language complexity for nonnatives.

We classify over one million authors as native or nonnative English speakers based on the etymological origins of their names and analyze over one million abstracts from arXiv.org (2018–2024), evaluating changes in lexical diversity and readability before and after ChatGPT’s release in November 2022. The results demonstrate a sharp increase in writing sophistication among all researchers, with nonnative English speakers showing the greatest gains across all writing metrics.

Moreover, we find that the adoption of LLM technology in academic writing is significantly more prevalent among computer scientists compared to researchers in other disciplines. Our findings provide empirical evidence on the impact of LLMs in academic writing, supporting recent speculations about their potential to bridge language barriers.

Presenter: Nathan Kettlewell