When more is less: The other side of artificial intelligence recommendation

Abstract Based on consumers' preferences, AI (artificial intelligence) recommendation automatically filters information, which provokes scholars' debate. Supporters believe that by analyzing the consumers' preferences, AI recommendation enables consumers to choose products more quickly and with lower cost. Critics deem that consumers are more easily trapped in information cocoons because of the use of AI recommendation. This reduces the possibility of consumers contacting with a variety of commodities, thus lowering the consumer decision quality. Based on experiments, this paper discusses the moderating role of AI recommendation on the relationship of consumers' preferences and information cocoons. Moreover, it examines the relationship between information cocoons and consumer decision quality. The findings are: AI recommendation strengthens consumers' preferences; consumers' preferences are positively correlated with information cocoons and further leads to the decline of consumers’ decision quality. In the AI era, this paper contributes to revealing the dark sides of AI recommendation and provides empirical evidence for the regulation of AI behaviors.