3 papers indexed
Chloe Hudson Prock, Enrico Bertini, Michael Correll
What do we value in our visualizations, and in the people who design them? Despite a growing body of work on critical data visualization, the conception of what it is to do ethical data visualization work can often be narrow (for instance, holding that our ethical duties are disc…
Michael Correll, Lucy Havens, Mahsan Nourani
The persuasive power of data visualizations can go awry: for instance, in an explainable AI (XAI) context, visualizations can produce over-trust of predictive models. In this paper, we use a crowdsourced study to show that providing accurate (but superfluous or irrelevant) data i…
Abhraneel Sarma, Matthew Kay, Sheng Long, Michael Correll, Alexander Lex
A perennial research question in visualization involves identifying which visual encodings for a particular dataset are most effective for users in performing a specific task. The relative effectiveness of the different encodings are commonly identified through controlled experim…