{"title":"消费者公正世界信念对人工智能推荐的影响:感知仁慈和自私的中介作用","authors":"Jungyong Ahn,Eunseo Kim","doi":"10.1089/cyber.2024.0513","DOIUrl":null,"url":null,"abstract":"This study investigated the effect of users' \"belief in a just world\" (BJW) on the persuasiveness of artificial intelligence (AI) agents' recommendations. Our prediction that users' preferences for human or AI agents vary according to their BJW levels was tested experimentally. The results revealed that individuals with high BJW rated human agents' recommendations more favorably than those of AI agents, whereas those with low BJW preferred AI agents' ones. This interaction was mediated by the perceptions of the agents' benevolence and selfishness, which varied depending on the BJW levels and agent type. High-BJW individuals perceived human agents as more benevolent and less selfish, whereas low-BJW individuals showed the opposite pattern. In contrast, AI agents' benevolence and selfishness perceptions were not influenced by BJW levels. This study provides theoretical insights by identifying BJW as a key factor affecting AI agents' persuasive effects and suggests that perceived benevolence and selfishness are the psychological mechanisms behind these effects. These findings also offer practical guidance for designing more effective AI agent strategies tailored to consumer BJW levels.","PeriodicalId":10872,"journal":{"name":"Cyberpsychology, behavior and social networking","volume":"6 1","pages":""},"PeriodicalIF":4.2000,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effects of Consumers' Belief in a Just World on Artificial Intelligence Recommendations: Mediating Effects of Perceived Benevolence and Selfishness.\",\"authors\":\"Jungyong Ahn,Eunseo Kim\",\"doi\":\"10.1089/cyber.2024.0513\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study investigated the effect of users' \\\"belief in a just world\\\" (BJW) on the persuasiveness of artificial intelligence (AI) agents' recommendations. Our prediction that users' preferences for human or AI agents vary according to their BJW levels was tested experimentally. The results revealed that individuals with high BJW rated human agents' recommendations more favorably than those of AI agents, whereas those with low BJW preferred AI agents' ones. This interaction was mediated by the perceptions of the agents' benevolence and selfishness, which varied depending on the BJW levels and agent type. High-BJW individuals perceived human agents as more benevolent and less selfish, whereas low-BJW individuals showed the opposite pattern. In contrast, AI agents' benevolence and selfishness perceptions were not influenced by BJW levels. This study provides theoretical insights by identifying BJW as a key factor affecting AI agents' persuasive effects and suggests that perceived benevolence and selfishness are the psychological mechanisms behind these effects. These findings also offer practical guidance for designing more effective AI agent strategies tailored to consumer BJW levels.\",\"PeriodicalId\":10872,\"journal\":{\"name\":\"Cyberpsychology, behavior and social networking\",\"volume\":\"6 1\",\"pages\":\"\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2025-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cyberpsychology, behavior and social networking\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1089/cyber.2024.0513\",\"RegionNum\":2,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, SOCIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cyberpsychology, behavior and social networking","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1089/cyber.2024.0513","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, SOCIAL","Score":null,"Total":0}
Effects of Consumers' Belief in a Just World on Artificial Intelligence Recommendations: Mediating Effects of Perceived Benevolence and Selfishness.
This study investigated the effect of users' "belief in a just world" (BJW) on the persuasiveness of artificial intelligence (AI) agents' recommendations. Our prediction that users' preferences for human or AI agents vary according to their BJW levels was tested experimentally. The results revealed that individuals with high BJW rated human agents' recommendations more favorably than those of AI agents, whereas those with low BJW preferred AI agents' ones. This interaction was mediated by the perceptions of the agents' benevolence and selfishness, which varied depending on the BJW levels and agent type. High-BJW individuals perceived human agents as more benevolent and less selfish, whereas low-BJW individuals showed the opposite pattern. In contrast, AI agents' benevolence and selfishness perceptions were not influenced by BJW levels. This study provides theoretical insights by identifying BJW as a key factor affecting AI agents' persuasive effects and suggests that perceived benevolence and selfishness are the psychological mechanisms behind these effects. These findings also offer practical guidance for designing more effective AI agent strategies tailored to consumer BJW levels.
期刊介绍:
Cyberpsychology, Behavior, and Social Networking is a leading peer-reviewed journal that is recognized for its authoritative research on the social, behavioral, and psychological impacts of contemporary social networking practices. The journal covers a wide range of platforms, including Twitter, Facebook, internet gaming, and e-commerce, and examines how these digital environments shape human interaction and societal norms.
For over two decades, this journal has been a pioneering voice in the exploration of social networking and virtual reality, establishing itself as an indispensable resource for professionals and academics in the field. It is particularly celebrated for its swift dissemination of findings through rapid communication articles, alongside comprehensive, in-depth studies that delve into the multifaceted effects of interactive technologies on both individual behavior and broader societal trends.
The journal's scope encompasses the full spectrum of impacts—highlighting not only the potential benefits but also the challenges that arise as a result of these technologies. By providing a platform for rigorous research and critical discussions, it fosters a deeper understanding of the complex interplay between technology and human behavior.