Assistant Prof of Data Visualization & Civic Media, Journalism Dept, Emerson College, Boston (USA) ; kanarinka.com.
While there is a lot of hype about data visualization, and a lot of new tools for doing it (my colleague Rahul Bhargava and I have counted over 500!), fewer people are thinking critically about the politics and ethics of representation. This, combined with a chart-scared general public, means that data visualizations wield a tremendous amount of rhetorical power. Even when we rationally know that data visualizations do not represent “the whole world”, we forget that fact and accept charts as facts because they are generalized, scientific and seem to present an expert, neutral point of view.
What’s the issue? Feminist standpoint theory would say that the issue is that all knowledge is socially situated and that the perspectives of oppressed groups including women, minorities and others are systematically excluded from “general” knowledge. Critical cartography would say that maps are sites of power and produce worlds that are intimately bound up with that power. As Denis Wood and John Krygier note, the choice of what to put on a map “… surfaces the problem of knowledge in an inescapable fashion as do symbolization, generalization and classification”. Until we acknowledge and recognize that power of inclusion and exclusion, and develop some visual language for it, we must acknowledge data visualization as one more powerful and flawed tool of oppression.
Can we say this more vividly? Donna Haraway, in her seminal essay on Situated Knowledges, offers a brilliant tour-de-force critiquing not just visual representation but the extreme and perverse privileging of the eyes over the body that has dominated Western thought. If you could, dear reader, read this quote aloud as it truly functions as a piece of performance art:
The eyes have been used to signify a perverse capacity — honed to perfection in the history of science tied to militarism, capitalism, colonialism, and male supremacy — to distance the knowing subject from everybody and everything in the interests of unfettered power. The instruments of visualization in multinationalist, postmodernist culture have compounded these meanings of disembodiment.
The visualizing technologies are without apparent limit. The eye of any ordinary primate like us can be endlessly enhanced by sonography systems, magnetic resonance imaging, artificial intelligence-linked graphic manipulation systems, scanning electron microscopes, computed tomography scanners, color-enhancement techniques, satellite surveillance systems, home and office video display terminals, cameras for every purpose from filming the mucous membrane lining the gut cavity of a marine worm living in the vent gases on a fault between continental plates to mapping a planetary hemisphere elsewhere in the solar system.
Vision in this technological feast becomes unregulated gluttony; all seems not just mythically about the god trick of seeing everything from nowhere, but to have put the myth into ordinary practice. And like the god trick, this eye fucks the world to make techno-monsters.”
Donna Haraway in “Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective/Feminist Studies” (1988)
The God Trick! Is this not the rhetorical premise and the seductive promise of most data visualization? To see from the perspective of no person, no body? Our appetite for such perspectives is fierce, “gluttonous”, as Haraway characterizes it.
And yet, there are ways to do more responsible representation. There are ways to “situate” data visualization and locate it in concrete bodies and geographies. Critical cartographers, counter-mapping artists, indigenous mappers and others have experimented for years with these methods and we can learn from them.
1. Invent new ways to represent uncertainty, outsides, missing data, and flawed methods
While visualizations — particularly popular, public ones — are great at presenting wholly contained worlds, they are not so good at visually representing their limitations. Where are the places that the visualization does not go and cannot go? Can we put those in? How do we represent the data that is missing? Andy Kirk has an incredible talk about the Design of Nothing that surveys the field in regards to how designers make decisions about representing uncertainty, including zeros, nulls and blanks. Can we push more designers to take these methods into consideration? Can we ask of our data that it point to its own outsides?