用户对人工智能产品的算法厌恶研究述评及展望

Consumers’ Algorithm Aversion to AI Products:A Literature Review and Prospect

通过文献回顾的方法,系统梳理以用户对人工智能产品的算法厌恶为对象的相关研究。研究发现:既有文献主要围绕算法厌恶的定义和测量,以及算法属性、任务类型和个体差异等方面,分析了引发算法厌恶的影响因素,并探讨算法厌恶的发生机制和应对策略;同时,上述研究通常基于自我服务偏差、社会认同理论与常人理论,提出各自关于算法厌恶的理论解释。基于此,未来可以从算法厌恶的边界探究、算法厌恶的心理根源挖掘、算法厌恶的应对策略研究,以及算法厌恶的动态演化研究等4个方面进一步拓展算法厌恶相关研究。

This study systematically reviews the related research on users’ algorithm aversion to artificial intelligence products.The existing literature mainly focuses on the definition and measurement of algorithm aversion,including analyzing the influencing factors of algorithm aversion from algorithm attributes,task types and individual differences,and discussing the mechanism and coping strategies of algorithm aversion.Moreover,they usually propose their own theoretical explanations for algorithm aversion based on self-serving bias,social identity theory and ordinary people theory.Accordingly,in the future,the researches on algorithm aversion can be further expanded from four aspects:the boundary exploration of algorithm aversion,the psychological root mining of algorithm aversion,the coping strategy of algorithm aversion,and the dynamic evolution of algorithm aversion.