United States history includes the founding sin of the transatlantic slave trade. White people historically contrived biological supremacy narratives based on obsolete theories of biological race derived from cranial features and anthropometric measurements. The lie of racecraft is also normalized though various aspects of technology, design, music, film, sport, fashion, law, politics, education, and economics.
Racists have engineered society for 400 years. Now, we have to engineer it the other way.
As human-centered designers, we encounter every user in their authentic context— at a Bank, in an Uber, on a train, donating to a charity, in an office.
UNCOVERING DESIGN BIAS
Design can have a profound impact on social change, both positive and negative. As a UX and technology company, we recognize that our work can contribute to the perpetuation of racial bias, whether we intend to or not. At Useagility, we strive to advocate for the user and use a human-centered approach in all aspects of our work. However, we know that even with the best intentions, unconscious bias can creep in, and there is always room to improve. One way we’re trying to educate ourselves is to examine bias within our own industry. By understanding where bias exists, we can better train ourselves to uncover and work to overcome our own unconscious biases.
Here are some examples where bias in the design process has failed to adequately solve for inclusivity:
FAILING TO RECOGNIZE DARK SKIN TONE IN DESIGN
There are several instances where technology has failed to recognize and respond consistently to darker skin tones. Wearable fitness trackers such as Fitbit and Apple Watch have been known to not properly work on dark or tattooed skin and AI for self-driving cars has issues recognizing Black individuals as pedestrians. The way these tools are programmed and built, are not designed to accommodate for marginalized populations.
FACIAL RECOGNITION BIAS
Facial recognition technology has been fraught with issues since its inception. In 2015, Google’s facial recognition categorized two African American individuals as gorillas. The “solution?” Removing ‘gorillas’ from the recognition software. Google, you can do better than that.
According to a study by the The National Institute of Standards and Technology, “Asian and African American people were up to 100 times more likely to be misidentified than white men… Native Americans had the highest false-positive rate of all ethnicities.” A MIT researcher found similar results, and added that women are mis-identified more frequently than men. This is especially problematic as facial recognition software has become one of the fastest growing tools in identifying criminal suspects and witnesses in law enforcement.
While some companies have called for national legislation to regulate use of facial recognition, cities such as Boston and San Francisco have banned use of this technology by law enforcement. Congress has yet to pass comprehensive legislation to regulate this technology which has incredible potential for human rights violations.
UPHOLDING BIAS ‘NORMS’ IN FEATURE DESIGN
Instagram’s photo filters were designed to enhance images. However, when ‘enhancing’ photos, the filters lighten skin tone. This functionality, knowingly or not, is catering to long-standing bias in photographic standards. In the 1960s, Kodak used white skin tones as the standard to measure film quality and accuracy of light – this design bias has morphed into the current digital ecosystem.
HOW DID THIS HAPPEN AND HOW CAN COMPANIES DO BETTER?
The root cause of much of this can be connected to a lack of diversity and inclusion among designers, as well as missed opportunities for real-world application through research and testing while in development. By including diverse populations in our research, design, and testing processes, we can create better solutions for everyone.
MOVING FORWARD
Design is not a perfect science, and there is no easy solution. But we can and will do better. We must all strive to continue to uncover our own biases and become more inclusive and aware of who may be underrepresented in our work, as well as how to design for them.
At Useagility, we are educating ourselves through our community, listening to and elevating BIPOC content and viewpoints. Here are some resources we are using to continue to educate ourselves.
- A brief history of how racism manifests itself in design and how we can learn from it by Amrutha Pal
- How UX design can counter racial bias by Ann Quito
- How Racial Bias Works and How to Disrupt It by Jennifer L. Eberhardt
- The racial implications of AI and UX by Jesse Childs
- On Racism and sexism in branding, user interface and tech by Adam Fard
- How UX allies can support Black Lives Matter by Oz Chen
- Harvard Implicit Bias Test