Communicating the use of artificial intelligence in agricultural and environmental research

被引:0
|
作者
Daigh, Aaron Lee M. [1 ,2 ,3 ]
Daroub, Samira H. [4 ,5 ]
Kyveryga, Peter M. [6 ,7 ]
Sorrells, Mark E. [8 ]
Rajan, Nithya [9 ]
Ippolito, James A. [10 ]
Kailer, Endy [11 ]
Booth, Christine S. [12 ,13 ]
Acharya, Umesh [14 ,15 ]
Ghimire, Deepak [1 ]
Das, Saurav [1 ,16 ]
Maharjan, Bijesh [1 ]
Ge, Yufeng [2 ,17 ]
机构
[1] Univ Nebraska, Agron & Hort, Lincoln, NE 68588 USA
[2] Univ Nebraska, Biol Syst Engn, Lincoln, NE USA
[3] Univ Nebraska Med Ctr, Environm Agr & Occupat Hlth, Omaha, NE USA
[4] Univ Florida, Soil Water & Ecosyst Sci, Gainesville, FL USA
[5] Univ Florida, Everglades Res & Educ Ctr, Belle Glade, FL USA
[6] John Deere, Sci Agron, Johnston, IA USA
[7] Iowa State Univ, Dept Agron, Ames, IA USA
[8] Cornell Univ, Sch Integrat Plant Sci, Ithaca, NY USA
[9] Texas A&M Univ, Soil & Crop Sci, College Stn, TX USA
[10] Ohio State Univ, Sch Environm & Nat Resources, Columbus, OH USA
[11] Kansas State Univ, Dept Agron, Manhattan, KS USA
[12] Univ Nebraska, Coll Agr Sci & Nat Resources, Lincoln, NE USA
[13] Univ Nebraska, Agr Res Div, Lincoln, NE USA
[14] John Deere Technol Innovat Ctr, Champaign, IL USA
[15] ARS, USDA, Soil Drainage Res Unit, Columbus, OH USA
[16] Rodale Inst, Kutztown, PA USA
[17] Univ Nebraska, Ctr Plant Sci Innovat, Lincoln, NE USA
关键词
D O I
10.1002/ael2.20144
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Transformative 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.
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页数:7
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