A common example, have you ever noticed that the queues for women's toilets are often much longer than those for men? Have you ever wondered why this happens? Generally, the same amount of space is allocated for male and female toilets for the purpose of gender equality. At first glance, this seems fair, but it is far from equitable. This decision ignores the real needs of users.
In the case of bathrooms, even though they may have the same space, the designs ignore the specific needs of women, who, on average, spend three times more time in the bathroom due to iran telegram data factors such as menstruation, pregnancy, among others. This seemingly minor detail generates frustrating experiences that are often dismissed as “that’s just the way things are,” ignoring real needs.
Algorithms are not impartial, and neither are we.
If something as simple as a bathroom can reflect such deep bias, how does this translate into digital spaces dominated by design?
Decisions about what data to include, which variables to prioritize, and how to categorize information are all influenced by human choices. This can be especially problematic when algorithms are used for critical decisions.
Designing for “everyone” versus designing for real people
Many products are created with the goal of being “for everyone.” However, as Kat Holmes argues in Mismatch: How Inclusion Shapes Design :
“When we design for the average, we exclude the margins.”
Designing for the “average user” often ignores the needs of other groups.
Towards inclusive design
What can we do as designers to mitigate these biases? Some key steps include:
Audit your data: Ask yourself if your data represents all users or if there are gaps that could skew your results.
Collaborate with diverse perspectives: Include voices from different genders, ethnicities, and disciplines to identify blind spots.
Test with marginalized groups: Go beyond standard usability testing and actively seek feedback from often excluded people.
Iterate and improve: Inclusion is not a one-time goal, it requires an ongoing process of learning and refinement.
Conclusion
Understanding implicit bias in design is a responsibility. Every decision we make has the potential to reinforce inequalities or combat them. When approaching each project, we must ask ourselves: “Who might this exclude?” and “How can I make it more inclusive for everyone?”
Recognizing these biases and taking steps to address them not only improves design, but also contributes to a more just and inclusive world.