Michael Correll on the use of “visualization literacy” in research:
If people (and, by some definitions, many or even most people) are chart illiterates, then we may feel tempted to write those groups off. We may prioritize the design of visualizations to help the creators of, say, machine learning models, from whom we can presume a sufficient level of visual and statistical literacy, rather than the populations who may be impacted by these models (sometimes unjustly). If what we mean by “visualization literacy” is narrow enough, or rare enough, then we’re already setting ourselves mental upper bounds for the number of people we’ll impact with our work.
This was an interesting perspective. I’m used to listening to or reading from people on the presentation side of visualization, in which case it’s your job to raise literacy. You should imagine what others are thinking and explain any points of possible confusion with annotation and intuitive visual encodings.
Don’t ever use “people won’t understand it” as a crutch.
