Mitigating Confirmation Bias through Hand-Drawing Videos
This work introduces a novel interface design to mitigate confirmation bias for data visualization users, though the effect is demonstrated in a single controlled study.
The authors investigated whether hand-drawing videos of bar charts can reduce confirmation bias in data interpretation. Results showed that hand-drawn videos improved interpretation accuracy and reduced belief-consistent errors compared to static charts.
Understanding data visualizations is essential for informed decision-making, yet interpretation is often shaped and even distorted by prior beliefs. We investigate whether an embodied pedagogical approach, in which viewers observe the dynamic hand-drawing of a visualization, can mitigate confirmation bias and improve interpretation accuracy. We conducted a study comparing static bar charts to videos in which charts are constructed through hand-drawing, across contexts that either align with or challenge participants' prior beliefs. The results indicate that hand-drawn videos helped participants accurately interpret data, even when the data conflicted with their prior beliefs. This approach also reduced belief-consistent errors and increased belief-overriding responses. These findings suggest that exposing the construction process of a visualization supports more accurate reasoning and mitigates the influence of confirmation bias. Consequently, this work introduces a promising design space for bias-mitigating data interfaces.