Visualizing Uncertainty for Non-Expert End Users: The Challenge of the Deterministic Construal Error
There is a growing body of evidence that numerical uncertainty expressions can be used by non-experts to improve decision quality. Moreover, there is some evidence that similar advantages extend to graphic expressions of uncertainty. However, visualizing uncertainty introduces challenges as well. He...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2021-01-01
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| Series: | Frontiers in Computer Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fcomp.2020.590232/full |
| _version_ | 1811190743004348416 |
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| author | Susan Joslyn Sonia Savelli |
| author_facet | Susan Joslyn Sonia Savelli |
| author_sort | Susan Joslyn |
| collection | DOAJ |
| description | There is a growing body of evidence that numerical uncertainty expressions can be used by non-experts to improve decision quality. Moreover, there is some evidence that similar advantages extend to graphic expressions of uncertainty. However, visualizing uncertainty introduces challenges as well. Here, we discuss key misunderstandings that may arise from uncertainty visualizations, in particular the evidence that users sometimes fail to realize that the graphic depicts uncertainty. Instead they have a tendency to interpret the image as representing some deterministic quantity. We refer to this as the deterministic construal error. Although there is now growing evidence for the deterministic construal error, few studies are designed to detect it directly because they inform participants upfront that the visualization expresses uncertainty. In a natural setting such cues would be absent, perhaps making the deterministic assumption more likely. Here we discuss the psychological roots of this key but underappreciated misunderstanding as well as possible solutions. This is a critical question because it is now clear that members of the public understand that predictions involve uncertainty and have greater trust when uncertainty is included. Moreover, they can understand and use uncertainty predictions to tailor decisions to their own risk tolerance, as long as they are carefully expressed, taking into account the cognitive processes involved. |
| first_indexed | 2024-04-11T14:54:17Z |
| format | Article |
| id | doaj.art-cebd478f05b948179153ebeecab55cf7 |
| institution | Directory Open Access Journal |
| issn | 2624-9898 |
| language | English |
| last_indexed | 2024-04-11T14:54:17Z |
| publishDate | 2021-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computer Science |
| spelling | doaj.art-cebd478f05b948179153ebeecab55cf72022-12-22T04:17:18ZengFrontiers Media S.A.Frontiers in Computer Science2624-98982021-01-01210.3389/fcomp.2020.590232590232Visualizing Uncertainty for Non-Expert End Users: The Challenge of the Deterministic Construal ErrorSusan Joslyn0Sonia Savelli1Department of Psychology, University of Washington, Seattle, WA, United StatesHuman Centered Design and Engineering, University of Washington, Seattle, WA, United StatesThere is a growing body of evidence that numerical uncertainty expressions can be used by non-experts to improve decision quality. Moreover, there is some evidence that similar advantages extend to graphic expressions of uncertainty. However, visualizing uncertainty introduces challenges as well. Here, we discuss key misunderstandings that may arise from uncertainty visualizations, in particular the evidence that users sometimes fail to realize that the graphic depicts uncertainty. Instead they have a tendency to interpret the image as representing some deterministic quantity. We refer to this as the deterministic construal error. Although there is now growing evidence for the deterministic construal error, few studies are designed to detect it directly because they inform participants upfront that the visualization expresses uncertainty. In a natural setting such cues would be absent, perhaps making the deterministic assumption more likely. Here we discuss the psychological roots of this key but underappreciated misunderstanding as well as possible solutions. This is a critical question because it is now clear that members of the public understand that predictions involve uncertainty and have greater trust when uncertainty is included. Moreover, they can understand and use uncertainty predictions to tailor decisions to their own risk tolerance, as long as they are carefully expressed, taking into account the cognitive processes involved.https://www.frontiersin.org/articles/10.3389/fcomp.2020.590232/fullvisualizationsuncertaintydecision makingrisk perceptionjudgmentexperimental psychology |
| spellingShingle | Susan Joslyn Sonia Savelli Visualizing Uncertainty for Non-Expert End Users: The Challenge of the Deterministic Construal Error Frontiers in Computer Science visualizations uncertainty decision making risk perception judgment experimental psychology |
| title | Visualizing Uncertainty for Non-Expert End Users: The Challenge of the Deterministic Construal Error |
| title_full | Visualizing Uncertainty for Non-Expert End Users: The Challenge of the Deterministic Construal Error |
| title_fullStr | Visualizing Uncertainty for Non-Expert End Users: The Challenge of the Deterministic Construal Error |
| title_full_unstemmed | Visualizing Uncertainty for Non-Expert End Users: The Challenge of the Deterministic Construal Error |
| title_short | Visualizing Uncertainty for Non-Expert End Users: The Challenge of the Deterministic Construal Error |
| title_sort | visualizing uncertainty for non expert end users the challenge of the deterministic construal error |
| topic | visualizations uncertainty decision making risk perception judgment experimental psychology |
| url | https://www.frontiersin.org/articles/10.3389/fcomp.2020.590232/full |
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