Predictive insights for improving the resilience of global food security using artificial intelligence

• Main Authors: HOW, Meng Leong, CHAN, Yong Jiet, CHEAH, Sin Mei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Artificial intelligence; Global food security index; Predictive modeling; Machine learning; AI for social good; Sustainability; Resilience; Bayesian; Cognitive scaffolding; Counterfactual; Agribusiness; Artificial Intelligence and Robotics
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/6720; https://ink.library.smu.edu.sg/context/lkcsb_research/article/7719/viewcontent/sustainability_12_06272.pdf
• Institution: Singapore Management University

Unabated pressures on food systems affect food security on a global scale. A human-centric artificial intelligence-based probabilistic approach is used in this paper to perform a unified analysis of data from the Global Food Security Index (GFSI). The significance of this intuitive probabilistic rea...