The Impact of Large Language Models in Academia: from Writing to Speaking (2025)

Abstract: Large language models (LLMs) are increasingly impacting human society, particularly in textual information. Based on more than 30,000 papers and 1,000 presentations from machine learning conferences, we examined and compared the words used in writing and speaking, representing the first large-scale study of how LLMs influence the two main modes of verbal communication and expression within the same group of people. Our empirical results show that LLM-style words such as significant have been used more frequently in abstracts and oral presentations. The implicit impact on human expression like writing and speaking is beginning to emerge and is likely to grow in the future. We take the first step in building an automated monitoring platform to record its longitudinal changes to call attention to the implicit influence and ripple effect of LLMs on human society.

## introduction the development and popularity of large language models (llms) @xcite @xcite have alerted more researchers to the impact of llms on human society. in this paper, we focus on the impact of llms in academia, especially on writing and speaking. while the rapid increase in usage and impact of llms have been demonstrated in academic papers @xcite , few studies have addressed the influence of llms beyond writing. shortly before we submitted the preprint of this paper to arxiv, another preprint pointed out the impact of llms on the words used in speaking, as collected in youtube videos @xcite . the similarities and differences in how writing and speaking are influenced, particularly for the same population, have not been explored. ## discussions and conclusions our paper is the first to estimate the effect of llms on the same group of people in writing and speaking and one of the first to analyze the impact on human communication and beyond text. our findings demonstrate the impact of llms in the abstracts of papers at top machine learning conferences. we also found that the words used in the talks were also influenced by llms, although this effect was less than in the abstracts. speech is one of the scenarios in which llms have an implicit impact (broadly), for it is usually safe to assume that the speaker is not using an llm while presenting. in addition, because of the difference between written and spoken language, it is actually difficult to directly compare llm impact on writing and speaking. detectors of machine-generated text face many challenges when applied to real-world data. analyzing linguistic features may therefore provide valuable insights into the impacts of llms, such as the monitoring platform presented in appendix a. the rapid increase in ai-generated content requires us to pay more attention, as synthetic data can lead to model collapse @xcite and even knowledge collapse @xcite . in the near future, a paper considered likely to be the product of llms may be so only because the authors have read too many papers containing llmstyle sentences. the implicit impact of llms on human seems unstoppable.