Should I Follow this Model? The Effect of Uncertainty Visualization on the Acceptance of Time Series Forecasts
Should I Follow this Model? The Effect of Uncertainty Visualization on the Acceptance of Time Series Forecasts
复制标题
我应该遵循这个模型吗？
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Oliver Müller
中科院分区：
文献类型：
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作者：
Dirk Leffrang;Oliver Müller
时间序列预测无处不在，从每日天气预报到COVID-19等流行病的预测。传达与此类预测相关的不确定性非常重要，因为它可能会影响用户对预测模型的信任，进而影响基于模型做出的决策。虽然存在着越来越多的可视化不确定性的研究一般，可视化预测的不确定性在时间序列预测的重要情况下，研究不足。在此背景下，我们研究了预测不确定性的不同可视化如何影响人们遵循时间序列预测模型预测的程度。更具体地说，我们进行了一项在线实验，预测因COVID-19大流行而占用的医院床位，测量算法预测的不确定性可视化对参与者自己预测的影响。与之前的研究相比，我们的实证结果表明，更突出的不确定性可视化会导致遵循算法预测的意愿下降。
Time series forecasts are ubiquitous, ranging from daily weather forecasts to projections of pandemics such as COVID-19. Communicating the uncertainty associated with such forecasts is important, because it may affect users’ trust in a forecasting model and, in turn, the decisions made based on the model. Although there exists a growing body of research on visualizing uncertainty in general, the important case of visualizing prediction uncertainty in time series forecasting is under-researched. Against this background, we investigated how different visualizations of predictive uncertainty affect the extent to which people follow predictions of a time series forecasting model. More specifically, we conducted an online experiment on forecasting occupied hospital beds due to the COVID-19 pandemic, measuring the influence of uncertainty visualization of algorithmic predictions on participants’ own predictions. In contrast to prior studies, our empirical results suggest that more salient visualizations of uncertainty lead to decreased willingness to follow algorithmic forecasts.
DOI：
10.1109/tvcg.2020.3030335
发表时间：
2021-02-01
影响因子：
5.2
作者：
Kale, Alex;Kay, Matthew;Hullman, Jessica
通讯作者：
Hullman, Jessica