“In the 9 months of working with Eli, I always felt that my voice was heard and my design decisions were respected. His problem definition and communication skills led us to produce some great work and push the Product forward by leaps & bounds! As a remote Designer, it can at times be difficult to be sure that Design has a voice at the table once the video conferencing goes off, but I always felt like Eli had my back. It was a pleasure working with him!”
About
Product founder / manager / maker, passionate about data-centric products as a lens into…
Experience
Education
Publications
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Polarizing Political Polls: How Visualization Design Choices Can Shape Public Opinion and Increase Political Polarization
IEEE Transactions on Visualization and Computer Graphics
While we typically focus on data visualization as a tool for facilitating cognitive tasks (e.g. learning facts, making decisions), we know relatively little about their second-order impacts on our opinions, attitudes, and values. For example, could design or framing choices interact with viewers' social cognitive biases in ways that promote political polarization? When reporting on U.S. attitudes toward public policies, it is popular to highlight the gap between Democrats and Republicans (e.g…
While we typically focus on data visualization as a tool for facilitating cognitive tasks (e.g. learning facts, making decisions), we know relatively little about their second-order impacts on our opinions, attitudes, and values. For example, could design or framing choices interact with viewers' social cognitive biases in ways that promote political polarization? When reporting on U.S. attitudes toward public policies, it is popular to highlight the gap between Democrats and Republicans (e.g. with blue vs red connected dot plots). But these charts may encourage social-normative conformity, influencing viewers' attitudes to match the divided opinions shown in the visualization. We conducted three experiments examining visualization framing in the context of social conformity and polarization. Crowdworkers viewed charts showing simulated polling results for public policy proposals. We varied framing (aggregating data as non-partisan “All US Adults,” or partisan “Democrat” / “Republican”) and the visualized groups' support levels. Participants then reported their own support for each policy. We found that participants' attitudes biased significantly toward the group attitudes shown in the stimuli and this can increase inter-party attitude divergence. These results demonstrate that data visualizations can induce social conformity and accelerate political polarization. Choosing to visualize partisan divisions can divide us further.
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Dispersion vs Disparity: Hiding Variability Can Encourage Stereotyping When Visualizing Social Outcomes
IEEE Transactions on Visualization and Computer Graphics
Visualization research often focuses on perceptual accuracy or helping readers interpret key messages. However, we know very little about how chart designs might influence readers' perceptions of the people behind the data. Specifically, could designs interact with readers' social cognitive biases in ways that perpetuate harmful stereotypes? For example, when analyzing social inequality, bar charts are a popular choice to present outcome disparities between race, gender, or other groups. But…
Visualization research often focuses on perceptual accuracy or helping readers interpret key messages. However, we know very little about how chart designs might influence readers' perceptions of the people behind the data. Specifically, could designs interact with readers' social cognitive biases in ways that perpetuate harmful stereotypes? For example, when analyzing social inequality, bar charts are a popular choice to present outcome disparities between race, gender, or other groups. But bar charts may encourage deficit thinking, the perception that outcome disparities are caused by groups' personal strengths or deficiencies, rather than external factors. These faulty personal attributions can then reinforce stereotypes about the groups being visualized. We conducted four experiments examining design choices that influence attribution biases (and therefore deficit thinking). Crowdworkers viewed visualizations depicting social outcomes that either mask variability in data, such as bar charts or dot plots, or emphasize variability in data, such as jitter plots or prediction intervals. They reported their agreement with both personal and external explanations for the visualized disparities. Overall, when participants saw visualizations that hide within-group variability, they agreed more with personal explanations. When they saw visualizations that emphasize within-group variability, they agreed less with personal explanations. These results demonstrate that data visualizations about social inequity can be misinterpreted in harmful ways and lead to stereotyping. Design choices can influence these biases: Hiding variability tends to increase stereotyping while emphasizing variability reduces it.
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Inspiring Change
Nightingale Magazine
Data journalists, with their colorful choropleths and fancy scrollytellers, get all the attention. And every book on dataviz says that’s how it should be: the purpose of dataviz is nothing short of enlightenment! Just like Snow’s cholera maps, Nightingale's mortality roses, Playfair’s trade balance streams, or Du Bois’ World’s Fair Exhibition, the paragons of data visualization reveal epic truths from big blocks of intractable data, like Michelangelo revealed David from an otherwise…
Data journalists, with their colorful choropleths and fancy scrollytellers, get all the attention. And every book on dataviz says that’s how it should be: the purpose of dataviz is nothing short of enlightenment! Just like Snow’s cholera maps, Nightingale's mortality roses, Playfair’s trade balance streams, or Du Bois’ World’s Fair Exhibition, the paragons of data visualization reveal epic truths from big blocks of intractable data, like Michelangelo revealed David from an otherwise unremarkable block of marble.
But visualizations don’t need to reveal the secrets of the universe to be impactful.
Projects
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Good Questions, Good Products Talk
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Talk given at various product-related events around NYC (e.g. Product School, Digital Product Design, Product Council)
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