人工智能知识:通过人工授权改进人工智能授权

Marc Pinski, Martin Adam, Alexander Benlian
{"title":"人工智能知识:通过人工授权改进人工智能授权","authors":"Marc Pinski, Martin Adam, Alexander Benlian","doi":"10.1145/3544548.3580794","DOIUrl":null,"url":null,"abstract":"When collaborating with artificial intelligence (AI), humans can often delegate tasks to leverage complementary AI competencies. However, humans often delegate inefficiently. Enabling humans with knowledge about AI can potentially improve inefficient AI delegation. We conducted a between-subjects experiment (two groups, n = 111) to examine how enabling humans with AI knowledge can improve AI delegation in human-AI collaboration. We find that AI knowledge-enabled humans align their delegation decisions more closely with their assessment of how suitable a task is for humans or AI (i.e., task appraisal). We show that delegation decisions closely aligned with task appraisal increase task performance. However, we also find that AI knowledge lowers future intentions to use AI, suggesting that AI knowledge is not strictly positive for human-AI collaboration. Our study contributes to HCI design guidelines with a new perspective on AI features, educating humans regarding general AI functioning and their own (human) performance and biases.","PeriodicalId":314098,"journal":{"name":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","volume":"198 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI Knowledge: Improving AI Delegation through Human Enablement\",\"authors\":\"Marc Pinski, Martin Adam, Alexander Benlian\",\"doi\":\"10.1145/3544548.3580794\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"When collaborating with artificial intelligence (AI), humans can often delegate tasks to leverage complementary AI competencies. However, humans often delegate inefficiently. Enabling humans with knowledge about AI can potentially improve inefficient AI delegation. We conducted a between-subjects experiment (two groups, n = 111) to examine how enabling humans with AI knowledge can improve AI delegation in human-AI collaboration. We find that AI knowledge-enabled humans align their delegation decisions more closely with their assessment of how suitable a task is for humans or AI (i.e., task appraisal). We show that delegation decisions closely aligned with task appraisal increase task performance. However, we also find that AI knowledge lowers future intentions to use AI, suggesting that AI knowledge is not strictly positive for human-AI collaboration. Our study contributes to HCI design guidelines with a new perspective on AI features, educating humans regarding general AI functioning and their own (human) performance and biases.\",\"PeriodicalId\":314098,\"journal\":{\"name\":\"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems\",\"volume\":\"198 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3544548.3580794\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3544548.3580794","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

当与人工智能(AI)合作时,人类通常可以委派任务来利用互补的人工智能能力。然而,人类经常低效地委派工作。让人类了解人工智能可以潜在地改善低效的人工智能授权。我们进行了一项受试者之间的实验(两组,n = 111),以研究如何让人类拥有人工智能知识,从而改善人类与人工智能协作中的人工智能授权。我们发现,人工智能知识支持的人类更紧密地将他们的授权决策与他们对任务对人类或人工智能的适合程度的评估(即任务评估)联系起来。我们表明,与任务评估密切相关的授权决策可以提高任务绩效。然而,我们也发现人工智能知识降低了未来使用人工智能的意愿,这表明人工智能知识对人类与人工智能的协作并不是严格积极的。我们的研究为人工智能设计指南提供了一个新的视角,让人们了解人工智能的一般功能以及他们自己(人类)的表现和偏见。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
AI Knowledge: Improving AI Delegation through Human Enablement
When collaborating with artificial intelligence (AI), humans can often delegate tasks to leverage complementary AI competencies. However, humans often delegate inefficiently. Enabling humans with knowledge about AI can potentially improve inefficient AI delegation. We conducted a between-subjects experiment (two groups, n = 111) to examine how enabling humans with AI knowledge can improve AI delegation in human-AI collaboration. We find that AI knowledge-enabled humans align their delegation decisions more closely with their assessment of how suitable a task is for humans or AI (i.e., task appraisal). We show that delegation decisions closely aligned with task appraisal increase task performance. However, we also find that AI knowledge lowers future intentions to use AI, suggesting that AI knowledge is not strictly positive for human-AI collaboration. Our study contributes to HCI design guidelines with a new perspective on AI features, educating humans regarding general AI functioning and their own (human) performance and biases.
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
期刊最新文献
Characterizing the Technology Needs of Vulnerable Populations for Participation in Research and Design by Adopting Maslow’s Hierarchy of Needs Playing with Power Tools: Design Toolkits and the Framing of Equity "It’s like With the Pregnancy Tests": Co-design of Speculative Technology for Public HIV-related Stigma and its Implications for Social Media Potential and Challenges of DIY Smart Homes with an ML-intensive Camera Sensor Understanding People’s Concerns and Attitudes Toward Smart Cities
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1