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 In Current Events, Data Storytelling, Experts, How To, Viz

I’ve talked in the past about the importance of recognizing bias in your data. I’ve worked hard to teach people how to avoid racism in data analysis and visualization. Recently, I was able to attend an event that approached the subject of casual racism from another angle: how not to design like a racist.

But I’m not a racist!

I am not, for a single moment, leveling any accusations of racism. The people I partner with — and by and large, the people who read this blog — are out to help their fellow humans, regardless of race, gender, or any other factors.

But inclusivity in design is about more than just not being actively racist. Bias is in our data, and in our design, is everywhere. In most cases, unintentionally. But it’s there. And if we don’t want to perpetuate racism — even accidental racism — we need to embrace inclusivity in design. (This applies particularly to the social sector, where bias can harm the very groups you’re trying to help.)

So let’s take a closer look at biases and inclusivity in design and how it relates to our data.


Bias is Built Right In

The origins of contemporary design are in modernism, a European movement that sought to obliterate historical and cultural traditions in its search for something novel. What’s wrong with that?

Viewed through a lens of colonialism, erasing ethnic identities and histories isn’t progress. Quite the opposite, in fact.

“In the modernist project, it’s not about respecting diversity. It’s everyone give up your differences and become part of Universal Man.”

~ Dori Tunstall, the world’s first black female design faculty dean


The event I mentioned earlier was held at OCAD University and featured Kelly Walters and Ramon Tejada talking about the importance of creating space for decolonized design. (He has generously made the slides from his presentation publicly available.)

“As a designer, I have come to terms with the fact that what and who design history has been interested in canonizing, up to this point, does not reflect me, my cultures, my values, and many of the tenets that make me a citizen, a designer, and a teacher.”

~ Ramon Tejada, independent Dominican/American designer and teacher


Tejada’s argument — and mine too, in this post — is that we must actively create spaces for design that respects cultures, values, and histories that are not our own.


Why Inclusivity in Design Matters

Our focus at Datassist is helping journalists and social sector organizations tell their data stories in a way that engages, educates, and energizes. But it’s critical that the story we tell is an accurate reflection of the world. If we don’t embrace inclusivity in our design, our stories will be limited; perhaps even twisted.

Novelist Chimamanda Adichie provides a wealth of examples of the dangers of telling only a single story. As a young black girl in Nigeria, she dreamed of being a writer and wove tales of blue-eyed, blond children playing in snow she’d never seen and eating foods she’d never tasted.

This past summer, Barclays bank experienced some online heat for a redesign of their website that used a stock photo of a black woman for their regular accounts and one of a white woman for their premium services. Nastya Grebneva of Icons8 delved into the situation… and reached an interesting conclusion.

  • Was it the bank’s fault that they chose the stock photos they did? A quick search revealed that stock images of “wealthy black women” are hard to come by…
  • So are the stock photo suppliers failing at inclusivity in design? Perhaps, but stock photo sites rarely produce their own images, so…
  • Could it be that photographers were perpetuating racial stereotypes? But photographers are simply producing the images they have demand for, which means…

All of us are responsible. We are all responsible for creating spaces that encourage inclusivity in design.


So What Can We Do?

At the OCAD event I mentioned earlier, Ramon Tejada made some great suggestions for questions we can ask ourselves to ensure inclusivity in our designs.

  • Who or what do we show as examples?
  • Which themes do we present?
  • What language do we use?

Eliminating bias in our design isn’t just about not actively excluding other perspectives or ideas. We must make room for designs that differ from our own, and be ready to accept they have something to teach us.

Want help eliminating bias in your data analysis or visualization? Drop us a line to discuss your project now.

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