Same Data, Diverging Perspectives: The Power of Visualizations to Elicit Competing Interpretations

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.