A Survey of Human-Centered Evaluations in Human-Centered Machine Learning

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dc.contributor.authorSperrle, Fabianen_US
dc.contributor.authorEl-Assady, Mennatallahen_US
dc.contributor.authorGuo, Graceen_US
dc.contributor.authorBorgo, Ritaen_US
dc.contributor.authorChau, Duen Horngen_US
dc.contributor.authorEndert, Alexen_US
dc.contributor.authorKeim, Danielen_US
dc.contributor.editorSmit, Noeska and Vrotsou, Katerina and Wang, Beien_US
dc.date.accessioned2021-06-12T11:12:41Z
dc.date.available2021-06-12T11:12:41Z
dc.date.issued2021
dc.description.abstractVisual analytics systems integrate interactive visualizations and machine learning to enable expert users to solve complex analysis tasks. Applications combine techniques from various fields of research and are consequently not trivial to evaluate. The result is a lack of structure and comparability between evaluations. In this survey, we provide a comprehensive overview of evaluations in the field of human-centered machine learning. We particularly focus on human-related factors that influence trust, interpretability, and explainability. We analyze the evaluations presented in papers from top conferences and journals in information visualization and human-computer interaction to provide a systematic review of their setup and findings. From this survey, we distill design dimensions for structured evaluations, identify evaluation gaps, and derive future research opportunities.en_US
dc.description.documenttypestar
dc.description.number3
dc.description.sectionheadersMachine Learning and Networks
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume40
dc.identifier.doi10.1111/cgf.14329
dc.identifier.issn1467-8659
dc.identifier.pages543-567
dc.identifier.urihttps://doi.org/10.1111/cgf.14329
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14329
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.titleA Survey of Human-Centered Evaluations in Human-Centered Machine Learningen_US
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