The Secret Language of Maps: How To Tell Visual Stories With Data
Carissa Carter
180 pages, Ten Speed Press, 2022
As human beings, it’s natural to be strongly affected by the visual, and across professions, people collect, work with, and share all kinds of visual data. Because we are all biased—based on our life experiences, culture, and context—it’s important to learn to detect the various forces that influence how these visual representations are used to push an agenda or distort the facts. Even more so, we must uncover our own biases that shape how we perceive and interpret those facts. Exploring bias—even your own—means investigating human behavior, motivations, and values.
In The Secret Language of Maps: How To Tell Visual Stories With Data, I examine how to view the many maps, infographics, and other visual representations of data that swirl around our daily lives with a critical eye. By addressing the inevitable bias present in both the creator and viewer of these visual tools, I hope to impart clarity for determining if the bias is hidden or obvious, harmful or harmless, explicit or implicit. Regardless of the type of bias behind them, maps harbor and expose our assumptions. While this is not a new phenomenon, the current power of visual data to quickly influence massive numbers of people has created a world that’s full of misinformation and a population that is not great at discerning it. To make sense of this world, literacy in interpreting these visual tools is an essential skill for an informed society. And if you are a creator of any type of visual representation of data, you have a great responsibility to thoughtfully consider your bias in how you present the information to your audience.—Carissa Carter
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There’s an ambiguous force at play in every map—it can feel like an unease in the center of the chest. What’s included and what isn’t? How is it depicted? Taken in? Is it useful? Enlightening? Dangerous or empowering? This force is bias. Your bias is your preference. It’s your intuition. It’s shaped by your perspective. It’s born from your culture, your lived experiences, and your current context. Your bias is the lens through which you view the world. Sometimes that lens is sharp. Other times it’s blurry. But you and me—odds are we don’t wear the same prescription.
As a viewer of a map, you need to be aware of your own biases, as well as those of the mapmaker. With each map you examine, consider the intent of its creator. What is the point of the map? Does it have a baked-in agenda? Did they aim to create a map that puts a specific topic in focus for a certain type of person? Are they hoping to get you lost in a house of mirrors? To steer your attention in a certain direction? Have they forgotten that they even wear lenses?
Bias is an undercurrent to both craft and data. The latter two are the ways in which bias manifests in a map. Sometimes a mapmaker has a clear bias, a point they want to make, something they choose to prioritize. This is their agenda. That agenda comes to life through their craft and data decisions.
Bias’s raw materials: Bias is tricky. It’s an interconnected web, and the elements aren’t sequential. When you deconstruct a map for bias, pay attention to these three elements: the viewer’s reaction, the creator’s intent, and the bias’s “cloud”—the qualities that make up bias itself.
Viewer’s reaction: What’s the impact of the map on the viewer? What is the viewer’s reaction to the map? What emotions does it evoke? Why?
Creator’s intent: Does the map have an agenda? A point it is trying to make? A specific context or target audience?
Bias cloud: What are the features or qualities of the bias? Is it explicit or implicit? Harmful or harmless? Hidden or obvious?
Bias in the viewer’s reaction: If you are the viewer, what’s your relationship to the topic of the map? What parts of your worldview affect your interpretation of the map?
We’re all experts on ourselves, and it’s both hardest and easiest to start there. It’s hard to see beyond our own experiences. It’s easy to talk about our own preferences. Consider your preferences around color. Do you prefer bright red or light pink? Why?
I like the bright red. It feels like it has guts and likes to go out and have fun. The light pink seems too gentle. It’s not a color I want to wear. It won’t look good on me. It feels too cutesy and stereotypically girly. These are my preferences, my biases. They are based on my lived experiences. I’ve never identified with light pink because it was considered a “girl” color. I never liked dolls or a lot of the toys that were dressed in light pink. It doesn’t represent me, but a lot of society says that it should, so my reaction is to challenge it. I have experienced gender bias, and I always notice it and want to challenge it to the tiniest detail. This means light pink to me. The bright red feels more like how I want to be—bold and exciting. It’s aspirational. It doesn’t feel like a gendered color. My experiences, my culture, and my context all shape my bias and my preference for the bright red. Your reaction is likely just as nuanced in its own way.
There’s no map here. These are just colors. Put these colors on a map, and they bring the baked-in biases with them. Color adds a layer of meaning, but that meaning will vary from person to person.
Articulate your bias
When deconstructing a map for bias, take in the content, then make sense of your gut reaction. At first, this reaction might be blobby and amorphous.
Let yourself react, then force yourself to articulate where that reaction originates. Is the map shocking because it’s showing you something you never expected? Are you skeptical because you are an expert in the field it’s depicting, and you have insider knowledge? Do you have personal experience with one of the themes in the map that might cause you to react in one way or another? Your reaction is valid. But be aware that the specifics and limitations of your own lived experience will color your interpretations.
Bias in the creator’s intent
Who is the mapmaker? What is the agenda of their map? Is there an insight, something the mapmaker discovered that they are trying to show? A hook? Are the mapmaker’s biases well known to the world? Do you have a hunch? Can you find them out? In other words, if you know the person who created the map, or an organization they are part of, you might be able to figure out their values and their biases.
Every map has an agenda
The intent behind a map can vary.
Some maps are made to invite a viewer to explore a topic, to plant a seed of an idea. Others are made to tell the viewer about a topic with a degree of confidence, but the viewer can draw their own conclusions. Others are made to reveal an idea that might be otherwise unknown. And of course, some maps are made with a goal of manipulation.
Bias clouds
Bias can be anywhere on the continuum from harmless to dangerous. Ask three questions to pinpoint which features are at play:
- Is the creator aware of the bias?
- Is it announced on the map?
- Does it hurt people?
Explicit biases may or may not be shown in a bold, obvious way, though. They could be subtle.
Explicit biases aren’t necessarily bad things, either.
An implicit bias by the mapmaker is a specific belief that gets assimilated into both the data and the craft. This is muscle memory and automatic—do something enough, and it’s second nature.
Always making female things pink and male things blue shows an implicit bias, both for gender norms and colors, but also for two—and only two—genders. Pink is a reinforcing signal that there is a specific way for women to express themselves. For many people, this would be harmless. But we should be wary because it’s not. For people who are gender nonconforming, it’s another reminder of being outsiders. Taken as a one-off, it might not hurt too much. Taken in aggregate from all of society, it’s a full body of pain.
As always, whether a bias is harmful or not has a lot to do with the full context of how it plays out. There is a big difference between saying “I like the color green” and “I hire only green people.” Racism, sexism, classism, and ableism are all part of the many existing systems of oppression. It’s important to know that these institutionalized biases affect different people in different ways.
The cultural context and lived experiences of the creator and viewer matter. Creators should take seriously what they make because of the impact on others and the norms created or reinforced, whether intentionally or not.
Our biases are ever-present. They’re expressed in how we craft our maps, and they’re part of our decision-making as we collect and use the data that powers them.
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Reprinted with permission from The Secret Language of Maps: How to Tell Visual Stories with Data by Carissa Carter and the Stanford d.school, copyright © 2022. Published by Ten Speed Press, an imprint of Penguin Random House.