Beyond Trust Building - Calibrating Trust in Visual Analytics

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Trust is a fundamental factor in how users engage in interactions with Visual Analytics (VA) systems. While the importance of building trust to this end has been pointed out in research, the aspect that trust can also be misplaced is largely ignored in VA so far. This position paper addresses this aspect by putting trust calibration in focus - i.e., the process of aligning the user's trust with the actual trustworthiness of the VA system. To this end, we present the trust continuum in the context of VA, dissect important trust issues in both VA systems and users, as well as discuss possible approaches that can build and calibrate trust.
Original languageEnglish
Title of host publication2020 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX) : Proceedings
Number of pages7
PublisherIEEE
Publication year2020
Pages9-15
ISBN (print)978-1-7281-8514-9
DOIs
Publication statusPublished - 2020
EventIEEE Workshop on TRust and EXpertise in Visual Analytics - Salt Lake City, United States
Duration: 25 Oct 202030 Oct 2020
https://trexvis.github.io/Workshop2020/

Conference

ConferenceIEEE Workshop on TRust and EXpertise in Visual Analytics
LandUnited States
BySalt Lake City
Periode25/10/202030/10/2020
Internetadresse

    Research areas

  • HCI theory, Human-centered computing, Visualization, Visualization design and evaluation methods, Visualization theory, concepts and models, concepts and paradigms; Human-centered computing

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