了解用户的人工智能操作意图：人工智能推荐算法背景下的前因实证调查

IF 8.2 2区管理学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information & Management Pub Date : 2024-11-14 DOI:10.1016/j.im.2024.104061

Taeyoung Kim, Il Im

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引用次数: 0

摘要

本研究探讨了促使平台用户操纵人工智能（AI）推荐算法的前因。基于说服知识模型（PKM），从YouTube和Instagram用户收集的调查数据显示，人工智能操作意愿受到人工智能说服知识和感知互动性的积极影响。感知互动性与人工智能操作的较高感知收益和较低感知成本相关，从而影响操作意图。多变量方差分析显示，不同说服知识水平的用户使用不同类型人工智能操纵行为的意愿存在差异。这项研究对 PKM 和人工智能与人的互动文献有所贡献。

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Understanding users’ AI manipulation intention: An empirical investigation of the antecedents in the context of AI recommendation algorithms

This study examines antecedents that drive platform users to manipulate artificial intelligence (AI) recommendation algorithms. Based on the persuasion knowledge model (PKM), survey data collected from YouTube and Instagram users reveal that AI manipulation intentions are positively affected by persuasion knowledge about AI and perceived interactivity. Perceived interactivity is associated with higher perceived benefits and lower perceived costs of AI manipulation, consequently affecting manipulation intentions. A multivariate analysis of variance shows variations in intentions to use different types of AI manipulation behaviors among users with varying levels of persuasion knowledge. The research contributes to the PKM and AI-human interaction literature.

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来源期刊

Information & Management 工程技术-计算机：信息系统

CiteScore

17.90

自引率

6.10%

发文量

123

审稿时长

1 months

期刊介绍： Information & Management is a publication that caters to researchers in the field of information systems as well as managers, professionals, administrators, and senior executives involved in designing, implementing, and managing Information Systems Applications.