Panel: Economic Policy and Governance during Pandemics using AI

TL;DR

This paper discusses how AI can improve understanding and decision-making in managing the global food supply chain during pandemics and other outlier events, enhancing policy responses and supply chain resilience.

Contribution

It introduces the application of AI methods to analyze and address disruptions in the food supply chain caused by pandemics and other outliers, offering new insights for policy and operational decisions.

Findings

AI helps identify regular and irregular supply chain patterns

AI-guided policies can improve welfare outcomes

Enhanced decision-making during outlier events

Abstract

The global food supply chain (starting at farms and ending with consumers) has been seriously disrupted by many outlier events such as trade wars, the China demand shock, natural disasters, and pandemics. Outlier events create uncertainty along the entire supply chain in addition to intervening policy responses to mitigate their adverse effects. Artificial Intelligence (AI) methods (i.e. machine/reinforcement/deep learning) provide an opportunity to better understand outcomes during outlier events by identifying regular, irregular and contextual components. Employing AI can provide guidance to decision making suppliers, farmers, processors, wholesalers, and retailers along the supply chain, and policy makers to facilitate welfare-improving outcomes. This panel discusses these issues.