Communicating the use of artificial intelligence in agricultural and environmental research

Author:

Daigh Aaron Lee M.123ORCID,Daroub Samira H.45,Kyveryga Peter M.67,Sorrells Mark E.8,Rajan Nithya9,Ippolito James A.10,Kailer Endy11,Booth Christine S.1213,Acharya Umesh1415,Ghimire Deepak1ORCID,Das Saurav116,Maharjan Bijesh1ORCID,Ge Yufeng217

Affiliation:

1. Agronomy & Horticulture University of Nebraska Lincoln Nebraska USA

2. Biological Systems Engineering University of Nebraska Lincoln Nebraska USA

3. Environmental, Agricultural, and Occupational Health University of Nebraska Medical Center Omaha Nebraska USA

4. Soil, Water, and Ecosystem Sciences University of Florida Gainesville Florida USA

5. Everglades Research and Education Center University of Florida Belle Glade Florida USA

6. John Deere, Science Agronomy Johnston Iowa USA

7. Department of Agronomy Iowa State University Ames Iowa USA

8. School of Integrative Plant Science Cornell University Ithaca New York USA

9. Soil and Crop Sciences Texas A&M University College Station Texas USA

10. School of Environment and Natural Resources The Ohio State University Columbus Ohio USA

11. Department of Agronomy Kansas State University Manhattan Kansas USA

12. College of Agricultural Sciences and Natural Resources University of Nebraska Lincoln Nebraska USA

13. Agricultural Research Division University of Nebraska Lincoln Nebraska USA

14. John Deere Technology Innovation Center Champaign Illinois USA

15. United States Department of Agriculture's Agricultural Research Service Soil Drainage Research Unit Columbus Ohio USA

16. Rodale Institute Kutztown Pennsylvania USA

17. Center for Plant Science Innovation University of Nebraska Lincoln Nebraska USA

Abstract

AbstractTransformative technologies such as artificial intelligence (AI) make difficult tasks more accessible and convenient. Since 2018, the use of AI in research has increased drastically, with annual publication rates of 3–5 times higher than pre‐2017. Currently, >100,000 manuscripts using AI are published annually within science and engineering, and >20,000 of these belong to the agricultural and environmental fields. Given the magnitude of use, clear communication on how AI is used and how it helps advance scientific knowledge is essential. Clear communication is perhaps more necessary with AI than previous technologies due to its broad and flexible spectrum of uses, the “black‐box” nature of deep‐learning algorithms, and ongoing debates regarding AI's predictive power versus knowledge of first‐principles mechanistic and process‐based theories and models. In this commentary, we provide guidelines and discussion points to the scientific community to ensure transparent and effective communication of AI research in agricultural and environmental research publications.

Publisher

Wiley

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