.png){kind=icon}
.png){kind=icon}
Return
Perspectives on the use of artificial intelligence in entomology
.png){kind=icon}
PRE
AI
R
R
A
J
E
T
E
G
DOI：10.1093/aesa/saag006.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Artificial intelligence (AI) is rapidly transforming the practice of science, including the field of entomology. Once viewed primarily as a tool for data analysis, AI is now reshaping publishing, research, and teaching in ways that raise both opportunities and concerns. To capture this pivotal moment, we organized a symposium at the 2024 Annual Meeting of the Entomological Society of America titled Artificial Intelligence (AI) in Entomology: An Aid to Publishing, Research, and Teaching. Presentations highlighted diverse applications of AI, from generative models that translate Extension materials for underserved audiences, to computer vision systems detecting stored product pests, to tools accelerating the digitization of insect collections, and to experimental manipulations of dominance hierarchies in social insects. Collectively, these case studies illustrate how AI can enhance efficiency, expand the scope of questions that can be asked, and democratize access to advanced research tools. At the same time, they emphasize the importance of careful oversight, given risks such as mistranslations, misclassifications, and overreliance on generative outputs. Beyond research, AI is already reshaping scientific publishing. Drawing on symposium discussions and a review of current policies, we propose baseline recommendations for authors, reviewers, and editors that are now integrated into Entomological Society of America publishing policies. These include transparent disclosure of AI use in acknowledgments and methods, alongside clear boundaries on acceptable applications. Our synthesis underscores that while AI can accelerate entomological science, ongoing dialogue, validation, and ethical guardrails are essential to ensuring trust, integrity, and creativity in the discipline.
Keywords:
machine learning
computer vision
generative AI
scientific publishing
pest monitoring
Journal
A
IF:
1.8
Papers:
3.0K
Citations:
5.9K
Organization
Cited Papers