Economics of the Adoption of Artificial Intelligence-Based Digital Technologies in Agriculture

被引:1
作者
Khanna, Madhu [1 ]
Atallah, Shady S. [1 ]
Heckelei, Thomas [2 ]
Wu, Linghui [1 ]
Storm, Hugo [2 ]
机构
[1] Univ Illinois, Dept Agr & Consumer Econ, Urbana, IL 61801 USA
[2] Univ Bonn, Inst Food & Resource Econ, Bonn, Germany
基金
美国食品与农业研究所; 美国国家科学基金会;
关键词
machine learning; precision farming; economic models; incentives; BIOECONOMIC MODEL; MANAGEMENT; BEHAVIOR; DISEASE; RESILIENCE; DIFFUSION; SYSTEMS; LEVEL; RISK; KEY;
D O I
10.1146/annurev-resource-101623-092515
中图分类号
F3 [农业经济];
学科分类号
0202 ; 020205 ; 1203 ;
摘要
Rapid advances and diffusion of artificial intelligence (AI) technologies have the potential to transform agriculture globally by improving measurement, prediction, and site-specific management on the farm, enabling autonomous equipment that is trained to mimic human behavior and developing recommendation systems designed to autonomously achieve various tasks. Here, we discuss the applications of AI-enabled technologies in agriculture, including those that are capable of on-farm reinforcement learning and key attributes that distinguish them from precision technologies currently available. We then describe various ways through which AI-driven technologies are likely to change the decision space for farmers and require changes to the theoretical and empirical economic models that seek to understand the incentives for their adoption. We conclude with a discussion of areas for future research on the economic, environmental, and equity implications of AI-enabled technology adoption for the agricultural sector.
引用
收藏
页码:41 / 61
页数:21
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