Artificial intelligence and prevention of panic buying during disasters

ABSTRACT

Panic buying occurs when unusually excess amounts of goods are bought in an anticipation of a crisis, perceived crisis, or in the aftermath of a crisis. Especially during the ongoing COVID-19 crisis, it was influenced by individuals' threat perception, fear of uncertainty, maladaptive coping, and social modeling. Artificial intelligence (AI) is an ever-evolving field, and its role in mental health has been widely studied. The traditional aspects of AI, namely, probability, linguistics, learning, reasoning, knowledge representation, and perception, may all be helpful in targeting various correlates of panic buying. Even though literature on the use of AI and machine learning to prevent panic buying is very limited, the existing models in healthcare can be extrapolated to that effect. Predicting buying patterns during crisis, personalizing supplies, warning signals for optimal threshold of buying, surveillance in markets, and ensuring enough resources of essential items are some of the areas that can be helped by AI. However, specific research, understanding, funding, standardization, and technical optimization are needed in this area before the promising field of AI helps prevent panic buying. This chapter provides a bird's-eye view related to the intersections of AI and panic buying as well as the directions ahead. (PsycInfo Database Record (c) 2022 APA, all rights reserved)