How Are Academic Scientists Using AI in Teaching and Research? Our Latest Study Investigates.
Since the launch of ChatGPT in late 2022, generative AI tools have become widely accessible, sparking rapid adoption across sectors—including higher education and scientific research. But how exactly are academic scientists integrating these new technologies into their professional practices?
Our latest study sheds light on this question by examining how STEM faculty at U.S. universities are engaging with generative AI in both teaching and research contexts.
What We Found
Based on a nationally representative survey of 232 STEM faculty members, we uncovered several key insights:
65% of respondents reported using generative AI in either teaching or research—and 20% have integrated it into both areas.
Among current users, 84% plan to continue using AI, indicating a strong belief in its value and utility.
In teaching, AI is most commonly used to develop course materials (51%), while in research, it's often used for writing, reviewing, or editing tasks (40%).
Despite high adoption, 78% of respondents cited misinformation as a top concern when using AI tools.
When it comes to governance, a majority (88%) expressed a preference for academic-led regulation of AI, rather than leaving oversight solely to government agencies.
Why This Matters
While our study contributes to a growing body of literature on generative AI adoption in academia, it also raises important questions about ethics, data integrity, and long-term impacts. Concerns such as bias in AI models, challenges in plagiarism detection, and data privacy remain underexplored and deserve critical attention.
Understanding how academic scientists are navigating this technological shift not only informs best practices but also helps us reflect on AI’s broader implications for scientific knowledge-building and ethical research practices.
🧠 Want to dive deeper into our findings?
Read the full study here ➝ https://doi.org/10.1371/journal.pone.0330416