Journal Article

Generative AI and academic scientists in US universities: Perception, experience, and adoption intentions

Ma, Jinghuan, Johnson, Timothy P., Chen, Tipeng, Islam, Shaika, Welch, Eric, Arroyo-Machado, Wenceslao, Michalegko, Lesley

2025

Overview

The integration of generative Artificial Intelligence (AI) into academia has sparked interest and debate among academic scientists. This paper explores the early adoption and perceptions of US academic scientists regarding the use of generative AI in teaching and research activities. To do so, this analysis focuses exclusively on STEM fields due to their high exposure to rapid technological advancements. Drawing from a nationally representative survey of 232 respondents, we examine academic scientists’ attitudes, experiences, and intentions regarding AI adoption. Results indicate that 65% of respondents have utilized generative AI in teaching or research activities, with 20% applying it in both areas. Among those currently using AI, 84% intend to continue its application, indicating a high level of confidence in its perceived benefits. AI is most frequently used in teaching to develop pedagogical materials (51%) and in research for writing, reviewing, and editing tasks (40%). Despite concerns about misinformation, with 78% of respondents indicating it as their top concern regarding AI, there is broad recognition of AI’s potential impact on society. Most academic scientists have already integrated AI into their academic activities, demonstrating cautious yet optimistic adoption due to perceived risks. Furthermore, there is strong support for academic-led regulation of AI, highlighting the need for responsible governance to maximize benefits while minimizing risks in educational and research settings.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Artificial Intelligence / Attitude / Automation / Beliefs, opinions and attitudes / Bias / Biology and Life Sciences / Chatbots / Colleges & universities / Computer and Information Sciences / Creativity / Critical thinking / Data analysis / Data collection / Education / Educational aspects / Educational objectives / Efficiency / False information / Female / Generative artificial intelligence / Higher education / Humans / Intention / Large language models / Learning / Male / Medicine and Health Sciences / Methods / People and Places / Perception / Perceptions / Plagiarism / Public opinion / Research and Analysis Methods / Research methodology / Research Personnel - psychology / Risk reduction / Scholars / Science Policy / Scientists / Social Sciences / Student retention / Surveys and Questionnaires / Teaching methods / Technology application / United States / Universities / Universities and colleges