Loading...
Paper Number
ICIS2025-1064
Paper Type
Complete
Abstract
Large language models (LLMs) have drawn attention for their potential to enhance knowledge workers’ productivity. Using data on 4,582 computer science scholars from 194 top U.S. universities and 218,723 papers (2019–2024), we provide the first large-scale empirical assessment of LLMs’ effects on research productivity. Following their introduction, publication rates rose by about 8%, with growth accelerating to 3.2% in 2023 and 12.8% in 2024. Junior scholars benefited more than seniors, with the productivity gain declining roughly 1% per year of experience. Yet, these benefits were not evenly distributed: difference-in-differences and generalized synthetic control analyses show that native English-speaking (NES) researchers published more than their non-native English-speaking (NNES) peers, widening linguistic disparities. Overall, LLMs boost scholarly productivity and lower barriers for early-career researchers, while also reinforcing inequities rooted in language proficiency.
Recommended Citation
Kwon, YoungJin and Yang, Agnes, "Large Language Models in Academia: Boosting Productivity but Reinforcing Inequality" (2025). ICIS 2025 Proceedings. 2.
https://aisel.aisnet.org/icis2025/gen_ai/gen_ai/2
Large Language Models in Academia: Boosting Productivity but Reinforcing Inequality
Large language models (LLMs) have drawn attention for their potential to enhance knowledge workers’ productivity. Using data on 4,582 computer science scholars from 194 top U.S. universities and 218,723 papers (2019–2024), we provide the first large-scale empirical assessment of LLMs’ effects on research productivity. Following their introduction, publication rates rose by about 8%, with growth accelerating to 3.2% in 2023 and 12.8% in 2024. Junior scholars benefited more than seniors, with the productivity gain declining roughly 1% per year of experience. Yet, these benefits were not evenly distributed: difference-in-differences and generalized synthetic control analyses show that native English-speaking (NES) researchers published more than their non-native English-speaking (NNES) peers, widening linguistic disparities. Overall, LLMs boost scholarly productivity and lower barriers for early-career researchers, while also reinforcing inequities rooted in language proficiency.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
12-GenAI