AI Article Synopsis

  • People often use data for decision-making, but biases can affect how they interpret that data.
  • Different visual representations of the same data can highlight varying patterns, leading viewers to notice different aspects as important.
  • In experiments, participants interpreted charts depicting two competing entities differently based on the visual presentation, influencing their predictions about which entity would win.

Article Abstract

People routinely rely on data to make decisions, but the process can be riddled with biases. We show that patterns in data might be noticed first or more strongly, depending on how the data is visually represented or what the viewer finds salient. We also demonstrate that viewer interpretation of data is similar to that of 'ambiguous figures' such that two people looking at the same data can come to different decisions. In our studies, participants read visualizations depicting competitions between two entities, where one has a historical lead (A) but the other has been gaining momentum (B) and predicted a winner, across two chart types and three annotation approaches. They either saw the historical lead as salient and predicted that A would win, or saw the increasing momentum as salient and predicted B to win. These results suggest that decisions can be influenced by both how data are presented and what patterns people find visually salient.

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Source
http://dx.doi.org/10.1109/TVCG.2024.3388515DOI Listing

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