{"title":"Examining generative AI user addiction from a C-A-C perspective","authors":"Tao Zhou, Chunlei Zhang","doi":"10.1016/j.techsoc.2024.102653","DOIUrl":null,"url":null,"abstract":"<div><p>The rapid development of generative AI represented by ChatGPT has attracted a large number of users, but also brings problems such as user addiction, which may undermine its sustainable development. Drawing on a cognition-affect-conation (C-A-C) perspective, this research examined generative AI user addiction. We used a mixed method of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to conduct data analysis. The results show that perceived anthropomorphism, perceived interactivity, perceived intelligence, and perceived personalization influence flow experience and attachment, both of which further affect user addiction. The fsQCA revealed three configurations triggering user addiction, among which flow experience and attachment are the common core conditions. The results imply that generative AI companies need to prevent user addiction and ensure a sustainable development.</p></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"78 ","pages":"Article 102653"},"PeriodicalIF":10.1000,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technology in Society","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0160791X2400201X","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL ISSUES","Score":null,"Total":0}
引用次数: 0
Abstract
The rapid development of generative AI represented by ChatGPT has attracted a large number of users, but also brings problems such as user addiction, which may undermine its sustainable development. Drawing on a cognition-affect-conation (C-A-C) perspective, this research examined generative AI user addiction. We used a mixed method of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to conduct data analysis. The results show that perceived anthropomorphism, perceived interactivity, perceived intelligence, and perceived personalization influence flow experience and attachment, both of which further affect user addiction. The fsQCA revealed three configurations triggering user addiction, among which flow experience and attachment are the common core conditions. The results imply that generative AI companies need to prevent user addiction and ensure a sustainable development.
期刊介绍：
Technology in Society is a global journal dedicated to fostering discourse at the crossroads of technological change and the social, economic, business, and philosophical transformation of our world. The journal aims to provide scholarly contributions that empower decision-makers to thoughtfully and intentionally navigate the decisions shaping this dynamic landscape. A common thread across these fields is the role of technology in society, influencing economic, political, and cultural dynamics. Scholarly work in Technology in Society delves into the social forces shaping technological decisions and the societal choices regarding technology use. This encompasses scholarly and theoretical approaches (history and philosophy of science and technology, technology forecasting, economic growth, and policy, ethics), applied approaches (business innovation, technology management, legal and engineering), and developmental perspectives (technology transfer, technology assessment, and economic development). Detailed information about the journal's aims and scope on specific topics can be found in Technology in Society Briefings, accessible via our Special Issues and Article Collections.
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