Visualizing Uncertainty for Non-Expert End Users: The Challenge of the Deterministic Construal Error
Visualizing Uncertainty for Non-Expert End Users: The Challenge of the Deterministic Construal Error
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DOI：
10.3389/fcomp.2020.590232
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发表时间：
2021-01-27
影响因子：
2.6
通讯作者：
Savelli, Sonia
中科院分区：
文献类型：
--
作者：
Joslyn, Susan;Savelli, Sonia
越来越多的证据表明，非专家可以使用数字不确定性表达式来提高决策质量。此外，有一些证据表明，类似的优势也延伸到了不确定性的图形表达上。然而，将不确定性可视化也带来了挑战。在这里，我们讨论不确定性可视化可能产生的主要误解，特别是用户有时没有意识到图形描述了不确定性的证据。相反，他们倾向于将图像解释为代表某种确定性的量。我们把这称为确定性解释错误。尽管现在有越来越多的证据表明确定性的解释错误，但很少有研究被设计成直接检测它，因为它们预先告诉参与者，可视化表达了不确定性。在自然环境中，这样的线索是不存在的，或许会让确定性假设变得更有可能。在这里，我们讨论这一关键但未被认识到的误解的心理根源以及可能的解决方案。这是一个关键的问题，因为现在很明显，公众理解预测包含不确定性，如果将不确定性包括在内，他们会有更大的信任。此外，他们可以理解和使用不确定性预测，以适应自己的风险承受能力，只要仔细表达，并考虑到涉及的认知过程。
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.