Trust in Prediction Models: a Mixed-Methods Pilot Study on the Impact of Domain Expertise

Jeroen Ooge, K. Verbert
{"title":"Trust in Prediction Models: a Mixed-Methods Pilot Study on the Impact of Domain Expertise","authors":"Jeroen Ooge, K. Verbert","doi":"10.1109/TREX53765.2021.00007","DOIUrl":null,"url":null,"abstract":"People’s trust in prediction models can be affected by many factors, including domain expertise like knowledge about the application domain and experience with predictive modelling. However, to what extent and why domain expertise impacts people’s trust is not entirely clear. In addition, accurately measuring people’s trust remains challenging. We share our results and experiences of an exploratory pilot study in which four people experienced with predictive modelling systematically explore a visual analytics system with an unknown prediction model. Through a mixed-methods approach involving Likert-type questions and a semi-structured interview, we investigate how people’s trust evolves during their exploration, and we distil six themes that affect their trust in the prediction model. Our results underline the multi-faceted nature of trust, and suggest that domain expertise alone cannot fully predict people’s trust perceptions.","PeriodicalId":345585,"journal":{"name":"2021 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TREX53765.2021.00007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

People’s trust in prediction models can be affected by many factors, including domain expertise like knowledge about the application domain and experience with predictive modelling. However, to what extent and why domain expertise impacts people’s trust is not entirely clear. In addition, accurately measuring people’s trust remains challenging. We share our results and experiences of an exploratory pilot study in which four people experienced with predictive modelling systematically explore a visual analytics system with an unknown prediction model. Through a mixed-methods approach involving Likert-type questions and a semi-structured interview, we investigate how people’s trust evolves during their exploration, and we distil six themes that affect their trust in the prediction model. Our results underline the multi-faceted nature of trust, and suggest that domain expertise alone cannot fully predict people’s trust perceptions.
对预测模型的信任:领域专长影响的混合方法试点研究
人们对预测模型的信任可能受到许多因素的影响,包括领域专业知识,如应用领域的知识和预测建模的经验。然而,领域专业知识影响人们信任的程度和原因尚不完全清楚。此外,准确测量人们的信任仍然具有挑战性。我们分享了一项探索性试点研究的结果和经验,在这项研究中,四名有预测建模经验的人系统地探索了一个具有未知预测模型的可视化分析系统。通过包括李克特型问题和半结构化访谈在内的混合方法,我们研究了人们的信任在探索过程中是如何演变的,并在预测模型中提炼出影响他们信任的六个主题。我们的研究结果强调了信任的多面性,并表明仅凭领域专业知识不能完全预测人们的信任感知。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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:481959085
Book学术官方微信