Using data storytelling to disrupt white supremacy culture

To say that when I first saw the 13 characteristics of white supremacy culture (from the research-based Dismantling Racism: A Workbook for Social Change Groups by Kenneth Jones and Tema Okun) it was a major lightbulb moment for me is putting it too lightly. I was immediately drawn to it for three important reasons:

  1. They recognize that white supremacy isn’t about a group of radical individuals, or even one race in particular. It’s about all of us and the cultural norms we’ve accepted that affect us all.

  2. They point to why we are so slow to change systemic racism: These cultural beliefs are often unconscious. We can try to say and even do things differently, but the old thinking is much harder to shift.

  3. They bring deeply rooted (and deeply problematic) issues to light and provide some guidance on how we can use this consciousness to shift our behaviors, on both individual and group levels.

As I let the light they cast on my life penetrate my understanding of myself, my relationships, and my work, my appreciation deepened for some things I’ve long held dear. For example, I’ve long sought to use the clarity of data and the power of visuals to balance one another, recognizing that each struggles with its own potential weaknesses. I’ve also sought to always engage people, to use human-centered philosophies and practices, to keep it real.

But, admittedly, it’s taken me too long to get this article written. It made me uncomfortable to look at where white supremacy runs rampant in my life, and it made me anxious to think about talking about that more publicly.

As always, my values won out. I realized all the potential good that might come of sharing about how data storytelling in particular is arrested by these cultural norms and simultaneously is equipped to disrupt them. I also was inspired by listening to some other professionals who I think are bravely doing their part, whom I’ll mention here.

Since I like to keep things simple and sweet, I’ve grouped the 13 characteristics into five themes related to data storytelling. For each summarized characteristic, I’ve identified where I think data storytelling can help offer or support some of the proposed anecdotes, and where there may be some opportunities for growth as well. Please forgive me for not going into great detail as my goal is to merely introduce these ideas, however imperfectly. I highly recommend checking out the full list for your own exploration and discovery.

Presentation

Perfectionism - Commonly pointing out how the person or work is inadequate

Strength: I think data storytelling is key to developing a learning organization, where it is expected that everyone will make mistakes and that those mistakes offer opportunities for learning.

Opportunity: When it comes to how data and designs are presented, it’s easy to offer criticism. I think often we can work on focusing more on what’s working well.

Worship of the Written Word - Devaluing other ways in which information gets shared; Believing that once people “see the light” they will adopt “right” ways

Strength: If you want to tell effective stories with data, it is important to consistently look at different ways of doing so and how you might improve your own approach.

Opportunity: Unfortunately, too often data storytelling is done in isolation, and the creator assumes they know what's best for their audience without establishing meaningful relationships with them. I think we can also challenge ourselves further to come up with new, innovative ways to document findings (for example, I’m a big fan of things like this and this.)

Data

Objectivity - Believing one can be objective, that emotions should not play a role in decision-making; Requiring people to think linearly and ignoring or invalidating those who think differently

Strength: Data storytellers already understand that our job is to fully understand the point being made, the worldview it is connected to, and how to use storytelling to elicit emotions that enable smart decisions.

Opportunity: What we don’t always understand is that sometimes we won’t understand. Like everyone, we must be willing to be uncomfortable, recognizing that everyone has their own perspective and that we will be more familiar with some perspectives than with others.

Quantity Over Quality - Valuing things that can be measured more than things that cannot, like relationships, processes, emotions and feelings

Strength: Data storytellers value process. We want to use smart processes that lead to the best outcomes. Some of us also value emotions and feelings, knowing they drive creative storytelling.

Opportunity: We can help our collaborators and audiences if we think about outcomes more broadly, not limiting them to products and projects but also changes in attitude and behavior, which can be more difficult to measure.

“We tend not to think of visualizations as things that should make us feel things, right? [A feminist visualization] uses a different way of knowing, it doesn’t use necessarily objective information, something that is perceived to be a neutral method of conveying what the date really has to say. The only reason why we feel that emotional knowledge is less good than other forms of knowledge like statistical or factual evidence is because we have this entrenched hierarchy of forms of knowledge and this is a gendered hierarchy.” - Lauren Klein, co-author of Data Feminism

Progress is Bigger, More - Determining success based on increases in what’s being measured

Strength: I think we do seek analyses that include many factors, big picture and small, costs and benefits.

Opportunity: We can think about our own goals more broadly too, taking into account not just what we’re creating but how we’re creating it. Are we asking those we work with to evaluate our process and performance?

“Data always creates a certain amount of distance, in some ways that can be positive, but at the same time if you’re always dealing with the numbers, especially at a distance, it’s really easy to overlook human costs . . . Through daily calculations people become inert to the horrors of the systems, they become desensitized to what they’re doing . . . People just get used to the numbers, it’s really easy to ignore what the numbers represent, I think it’s a constant danger of scale and of distance.” - Caitlin Rosenthal, author of Accounting for Slavery: Masters and Management

Process

Sense of Urgency - Refusing to take the time to be inclusive and democratic, to consider long-term consequences

Strength: I would like to think that we want our work plans to be realistic, especially since that’s the only way we can juggle the multiple projects we tend to.

Opportunity: I think many of us could stretch ourselves by making a point to discuss with our collaborators how we might adjust our plans to ensure we can include diverse perspectives.

Either/Or Thinking - Taking little or no time to consider alternatives; Having no sense that things can be both/and

Strength: Data storytellers can be important advocates for deep analysis of complex issues.

Opportunity: We can also advocate for the consideration and employment of many alternatives.

Fear of Open Conflict - Avoiding issues that may be causing problems; Blaming those who raise them and valuing politeness

Strength: Again, we can be powerful team assets because of our willingness to look at hard issues. Sometimes by presenting data we are able to present these issues in a less personal, less threatening way.

Opportunity: Some of us take the blame for this more than others, so we need to support one another, especially when there are power dynamics at work. We can also look at our own bias for data and be willing to accept feedback when it may not be data-driven.

Audience

Paternalism - Believing those with power are capable of making decisions for and in the interests of those without power, without necessarily understand their viewpoints or experiences

Strength: Data storytellers love transparency. We can use our skills to help those without power understand how decisions get made.

Opportunity: Again, we can work harder to include people who are affected by the decisions we are making. I think it’s important to recognize that having access to, being able to understand, and even creating data, as well as being able to create meaningful stories are tools of power, so keep this in mind when thinking about the characteristics concerning use of power.

Power Hoarding - Assuming that those without power, those wanting change are stupid or inexperienced, that one has their “best interests at heart”

Strength: We appreciate that data stories can present new information that may lead to challenges or changes that are healthy and productive.

Opportunity: Data storytellers often think their audience is limited to those whom their boss or client is looking to inform or influence, but why can’t our bosses or clients be audiences too? We can also do more than inform others, we can lead them by helping to develop their data and storytelling skills and thus their power.

“It’s okay to push people. You don’t always have to give people what they want, you can give them what you think is going to be better . . . When you establish trust you have this social currency that you can spend on asking somebody ‘Trust me, you’re eventually going to get it.’ And you’d better be right more often than not. You can’t just establish trust once and then you have it forever.” - Elijah Meeks (whose projects include, among many, network models of the Roman Empire and noteworthy Britains)

Collaboration

Individualism - Seeking individual recognition and credit; Spending little time or resources on developing collaboration skills

Strength: The data visualization field tends to be supportive of mutual growth.

Opportunity: We not only need more discussion of best practices when it comes to collaboration but also more ways to evaluate our ability to work on a team and rewards/recognition for doing so.

Defensiveness - Responding in a way that makes it very difficult to raise new or challenging ideas

Strength: By creating meaningful, data-driven stories, we are able to raise new or challenging ideas in ways that feel more useful than threatening.

Opportunity: As we raise these ideas, we can also open the door to discussion about how resistance to new ideas may be preventing individuals and teams from reaching important goals.

Right to Comfort - Scapegoating those who cause discomfort

Strength: Data storytellers are accustomed to uncertainty. We can help others deepen their analysis and take things less personally.

Opportunity: Welcoming and understanding our own discomfort, as a way of embracing growth and learning, must come first. We cannot share what we ourselves don’t have, and we cannot take people where we’re unwilling to go.

Now that you’ve had a chance to review the ways data storytelling can help disrupt white supremacy, and the ways data storytellers must challenge themselves to be able to so, what do you think? Where might you grow? What makes you uncomfortable? Please leave a comment to help other readers relate and understand.

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