对工作、医疗保健和教育中人工智能态度的经济衡量(ATTARI-WHE)

Timo Gnambs , Jan-Philipp Stein , Markus Appel , Florian Griese , Sabine Zinn
{"title":"对工作、医疗保健和教育中人工智能态度的经济衡量(ATTARI-WHE)","authors":"Timo Gnambs ,&nbsp;Jan-Philipp Stein ,&nbsp;Markus Appel ,&nbsp;Florian Griese ,&nbsp;Sabine Zinn","doi":"10.1016/j.chbah.2024.100106","DOIUrl":null,"url":null,"abstract":"<div><div>Artificial intelligence (AI) has profoundly transformed numerous facets of both private and professional life. Understanding how people evaluate AI is crucial for predicting its future adoption and addressing potential barriers. However, existing instruments measuring attitudes towards AI often focus on specific technologies or cross-domain evaluations, while domain-specific measurement instruments are scarce. Therefore, this study introduces the nine-item <em>Attitudes towards Artificial Intelligence in Work, Healthcare, and Education</em> (ATTARI-WHE) scale. Using a diverse sample of <em>N</em> = 1083 respondents from Germany, the psychometric properties of the instrument were evaluated. The results demonstrated low rates of missing responses, minimal response biases, and a robust measurement model that was invariant across sex, age, education, and employment status. These findings support the use of the ATTARI-WHE to assess AI attitudes in the work, healthcare, and education domains, with three items each. Its brevity makes it particularly well-suited for use in social surveys, web-based studies, or longitudinal research where assessment time is limited.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"3 ","pages":"Article 100106"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An economical measure of attitudes towards artificial intelligence in work, healthcare, and education (ATTARI-WHE)\",\"authors\":\"Timo Gnambs ,&nbsp;Jan-Philipp Stein ,&nbsp;Markus Appel ,&nbsp;Florian Griese ,&nbsp;Sabine Zinn\",\"doi\":\"10.1016/j.chbah.2024.100106\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Artificial intelligence (AI) has profoundly transformed numerous facets of both private and professional life. Understanding how people evaluate AI is crucial for predicting its future adoption and addressing potential barriers. However, existing instruments measuring attitudes towards AI often focus on specific technologies or cross-domain evaluations, while domain-specific measurement instruments are scarce. Therefore, this study introduces the nine-item <em>Attitudes towards Artificial Intelligence in Work, Healthcare, and Education</em> (ATTARI-WHE) scale. Using a diverse sample of <em>N</em> = 1083 respondents from Germany, the psychometric properties of the instrument were evaluated. The results demonstrated low rates of missing responses, minimal response biases, and a robust measurement model that was invariant across sex, age, education, and employment status. These findings support the use of the ATTARI-WHE to assess AI attitudes in the work, healthcare, and education domains, with three items each. Its brevity makes it particularly well-suited for use in social surveys, web-based studies, or longitudinal research where assessment time is limited.</div></div>\",\"PeriodicalId\":100324,\"journal\":{\"name\":\"Computers in Human Behavior: Artificial Humans\",\"volume\":\"3 \",\"pages\":\"Article 100106\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers in Human Behavior: Artificial Humans\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949882124000665\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in Human Behavior: Artificial Humans","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949882124000665","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

人工智能(AI)已经深刻地改变了私人和职业生活的许多方面。了解人们如何评估人工智能对于预测其未来的采用和解决潜在的障碍至关重要。然而,现有的测量对人工智能态度的工具往往侧重于特定技术或跨领域评估,而特定领域的测量工具很少。因此,本研究引入了工作、医疗和教育中对人工智能的态度(ATTARI-WHE)量表。使用来自德国的N = 1083名受访者的不同样本,对该工具的心理测量特性进行了评估。结果表明,缺失应答率低,应答偏差最小,并且具有跨性别、年龄、教育程度和就业状况不变的稳健测量模型。这些发现支持使用ATTARI-WHE来评估工作、医疗保健和教育领域的人工智能态度,每个领域有三个项目。它的简洁性使其特别适合用于社会调查、基于网络的研究或纵向研究,其中评估时间有限。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An economical measure of attitudes towards artificial intelligence in work, healthcare, and education (ATTARI-WHE)
Artificial intelligence (AI) has profoundly transformed numerous facets of both private and professional life. Understanding how people evaluate AI is crucial for predicting its future adoption and addressing potential barriers. However, existing instruments measuring attitudes towards AI often focus on specific technologies or cross-domain evaluations, while domain-specific measurement instruments are scarce. Therefore, this study introduces the nine-item Attitudes towards Artificial Intelligence in Work, Healthcare, and Education (ATTARI-WHE) scale. Using a diverse sample of N = 1083 respondents from Germany, the psychometric properties of the instrument were evaluated. The results demonstrated low rates of missing responses, minimal response biases, and a robust measurement model that was invariant across sex, age, education, and employment status. These findings support the use of the ATTARI-WHE to assess AI attitudes in the work, healthcare, and education domains, with three items each. Its brevity makes it particularly well-suited for use in social surveys, web-based studies, or longitudinal research where assessment time is limited.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信