How Bad Design Perpetuates Harmful Stereotypes

Specialized solutions for disadvantaged people often have more to do with negative perceptions than actual needs

Kat Holmes
Oct 3, 2018 · 9 min read
Photo by Bill O’Leary/The Washington Post via Getty Images

There’s a rise in interest in designs that have a positive social impact. A number of projects are focused on “designing for” a community of people that’s presumed to be disadvantaged. New technologies for students in developing countries. Design contests to create solutions for elderly people or people with disabilities.

While these are often well-intentioned, there are some potential pitfalls to designing for people with this superhero-victim or benefactor-beneficiary mindset. It can lead to specialized solutions that cater to stereotypes about people.

To illustrate the problem, let’s consider the Dodge La Femme — a car designed specifically for women, brought to market in 1955, and canceled in 1956. The car was pink, inside and out, and decorated with small roses. It featured a fully equipped matching purse that fit into the back of the passenger side headrest. It was marketed with the headline “By Special Appointment to Her Majesty… the American Woman.”

While it’s somewhat easy to dismiss this as an artifact of a bygone era of male chauvinism, let’s also consider the failed launch of Bic for Her in 2012. This was a line of pens designed specifically for women that were thinner than standard pens and available in pastel shades of pink, purple, and turquoise. It was marketed on Amazon as having an “elegant design — just for her!” and a “thin barrel to fit a woman’s hand.”

Thin barrel or not, the pens are now a hallmark example of how not to design and market your product to women, thanks to writer Margaret Hartman, who sparked thousands of people to write entertainingly sarcastic reviews on Amazon. The product was quickly removed from the market.

In the pursuit of innovation, it’s common for teams to focus solely on the functional elements of design. It’s equally important to understand the emotional considerations.

In a more serious example, the automotive industry conducts safety testing with models of humans, also known as crash-test dummies. For decades, these models were made to match the average male body type, though it was widely known that women were significantly more likely to be injured in a car crash.

In 2011, the federal government started an initiative to reduce demographic disparities in public health. Car accidents ranked high on the list of public health risks. Passenger-side safety ratings plummeted as cars were tested with a petite female crash-test model that was 4 feet 11 inches tall and 108 pounds. That year, studies revealed that a female driver wearing a seatbelt faced a 47 percent higher risk of death or serious injury than a male driver.

Decades of design choices where made based on average male-sized testing standards. Engineers and designers were trained to optimize to these standards. It wasn’t that the cars were suddenly less safe. They had always been less safe. It just hadn’t been recognized as a problem.

This wasn’t a sex-specific disparity. The average male crash-test model is 5 feet 9 inches tall and 172 pounds. Once the industry started using a range of body types in its safety testing, there was an improvement for any person whose body didn’t match the design of the male crash-test model, across all genders, sizes, and ages.

We can see from these examples how the perceptions people have about one another can be manifested in the design of products and environments.

An unspoken hierarchy also appears when attempting to design solutions for groups that are perceived as needing help. Without an authentic and meaningful understanding of a person’s life experiences, stereotypes can prevail. All too often, designers and architects perceive the recipients of their solutions as “other people.” This mindset distances the designers from people they perceive as disadvantaged beneficiaries of their design.

The problem is separation. It’s rooted in the ways we categorize human diversity. The most common ways that we group people by diversity are single dimensions like ability, gender, race, ethnicity, income, sexual orientation, and age. Even if we know people are more complex than a single dimension, businesses regularly try to solve problems based on these monolithic groupings.

How we categorize people shapes how we make. With a growing interest in participatory design methods across many professional fields, how is that participation to be facilitated? What kinds of questions do you lead with? Do you meet people in their homes or require them to visit your office? What tools do you ask them to use when providing input to the design, and are they comfortable using them? Meaningful inclusion is much more than hosting listening tours, focus groups, or interviewing people on the street.

One way to start is by building an extended community of “exclusion experts” who contribute to your design process. These are people who experience the greatest mismatch when using your solution or who might be the most negatively affected. Develop meaningful relationships with communities that contribute to a design. Designing with, not for, excluded communities is how we put the inclusive in inclusive design.

In the pursuit of innovation, it’s common for teams to focus solely on the functional elements of design. It’s equally important to understand the emotional considerations of a design, in particular the familiarity people have already developed with an existing solution. What are their patterns of using a solution? What makes these patterns important to their lives?

Consider a person who takes a carefully planned path through a city to make it on time to work every day. Or the ways they organize important files in their personal computing devices. Something as simple as changing the name of a feature in a software application or a street name in a city could be disorienting for them.

This exclusion habit is often motivated by economic factors. Change for the sake of newness. Growth for the sake of progress. Delight for the sake of differentiation. Fixing perceived disorder into order. Along the way, design changes can disrupt human patterns and relationships. Especially when the problem solver, whether that’s an architect, designer, engineer, or business leader, presumes that their own professional expertise supersedes the life expertise of people who are affected by those changes.

The same thing happens in digital spaces when we change products that people are familiar with. Each time we change a design, by adding new features or moving things around, we require people to learn something new. They have to form new relationships and new patterns of behavior.

The problem is that everyone adapts in their own ways. Not everyone solves problems or learns through the same approaches. But when designers make changes to a product or space, their ability biases can lead the way.

As an example, while at Microsoft, I received a phone call one evening from a product leader who was concerned that there were far fewer women using their product than they expected. He was also concerned by the early solutions that teams were proposing to address this issue.

We took a closer look at the patterns of behavior that were happening in the product. We studied the research of Oregon State University professor Margaret Burnett, who has spent more than a decade studying the relationship between gender and software. In her GenderMag Project, Burnett identified a set of facets that consistently lead to differences in how software is used by people identifying as women or men.

With technology, many customers have a tendency to blame themselves for not being able to figure out the changes on their own… In essence, they feel excluded. The impact on people can be deeply emotional.

One facet in particular stood out to us: how people prefer to learn. Burnett also refers to this as a person’s willingness to tinker with new software. She found a spectrum that spans between two approaches to learning new technology. On one end is a preference to learn through a guided approach, or with the assistance of a human being. On the other end is a high willingness to explore a software interface through trial and error.

The research showed that women distributed relatively evenly across this spectrum. There was a wide range of learning styles that different women used when learning new software. Men, however, clustered heavily toward the end of the spectrum for tinkering and troubleshooting solutions.

This insight helped us reframe the problem. Was it possible that our product favored a particular learning style? We restructured our research to recruit people by learning style and interviewed people from multiple genders, including transgender participants.

We found that people who preferred a guided learning approach, regardless of gender, felt alienated and confused by recent changes we made in the product. They were concerned that important programs had disappeared. Or they couldn’t figure out how to complete tasks they’d known how to do for years, because the interface had changed.

It turned out that when we updated our product, we required people to learn something new. But we did so in a way that reflected our own internal learning styles. This differed from how many of our customers learned. After all, what percentage of the general population is trained to think like engineers? Design decisions were made with the assumption that people would just hunt around and try things until they found what they needed, reflecting our team’s own learning styles and disproportionately benefitting men.

Disruptive changes can especially be an issue for people with disabilities who might depend on a particular technology to complete essential tasks in their lives. If a software program or website is updated but the right steps aren’t taken to ensure the updates are compatible with assistive tools like screen readers, the resulting changes can literally prohibit someone from doing their job. Or prevent them from using a form of transit that they need to get to work on time. A change to a payment system can affect a person’s livelihood.

These learning biases can be further reinforced by feedback from customers. Many companies depend on their most engaged users, people who love products as much as the people who make them, to spend time providing feedback.

How feedback is collected reflects the preferences of the team that builds the product. As you might imagine, if you take only online feedback or provide customer support only in English, the only people you’ll hear from are people who match this profile. This has a profound impact on which feedback makes its way to the design team.

These feedback channels can also be a signal to customers that they either do or don’t belong with the product. With technology, many customers have a tendency to blame themselves for being unable to figure out the changes on their own. Common indicators are customers who say, “I feel like technology is moving so much faster than I am,” or, “I’m probably not smart enough to figure this out.” In essence, they feel excluded. The impact on people can be deeply emotional.

Shifting that sense of exclusion requires careful attention to who’s missing from a solution and from feedback channels. Whose voices are the loudest, and whose are missing? Seek out who’s missing, and learn about their existing patterns of behavior. Design solutions that bring them successfully through your changes. Provide diverse ways to receive guidance on what’s new, and help customers become reoriented with a product they’ve known and used for years.

We can also shift the sense of belonging by opening up the ways that people can contribute to the design process itself. Contributing to the design of a product or environment, even in the smallest ways, increases the emotional connection between a person and that solution.

The push to accelerate growth and change, for cities or software, is often necessary. But how it is implemented is vitally important.

People create emotional connections to a design that make a place or a product feel like their own. Introducing change isn’t just about breaking apart concrete or bits of code. It’s breaking apart human relationships. The result may be that people will leave and never return.

Making a change without disrupting a sense of belonging can be difficult. It’s a challenge because it’s an emotional choice, not just a rational one. Those emotional considerations are best described by people who are the most excluded from your solution. Or those who stand to lose the most during times of change, including kids who will interact with the next generation of designs. Their contributions will be one of your greatest resources in designing where to go next.

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Excerpted from Mismatch: How Inclusion Shapes Design, by Kat Holmes, with a foreword by John Maeda, published by The MIT Press. All rights reserved.

Written by

Founder | Author of Mismatch: How Inclusion Shapes Design @MITPress | UX Design Director @Google | Prev: #InclusiveDesign Director @Microsoft |

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