Introduction: A Growing Accessibility Gap
Artificial intelligence and facial recognition technology are transforming how people access essential services—from financial platforms to government portals. But for individuals with facial differences or disabilities, these technologies can inadvertently create new barriers to inclusion.
Kathleen Bogart, a psychology professor at Oregon State University who specializes in disability research, puts it succinctly:
“If you don’t include people with disabilities or people with facial differences in the development of these processes, no one’s going to think of these issues.”
These systemic gaps are not new—they are rooted in long-standing underrepresentation and societal bias that AI has now amplified on a larger scale.
The Real-World Impact of Facial Recognition Barriers
When face verification systems fail, it often leaves individuals stranded with few or no alternatives. Noor Al-Khaled, a Maryland resident living with Ablepheron Macrostomia, has spent months trying to create an online account with the U.S. Social Security Administration (SSA).
“I don’t drive because of my vision; I should be able to rely on the site,” Al-Khaled explains. But the system repeatedly rejects her selfie because it doesn’t match the ID photo, locking her out of essential digital services.
This lack of reliable access doesn’t just inconvenience users—it deepens emotional and social exclusion. Al-Khaled notes, “On an emotional level, it just makes me feel shut out from society.”
When Technology Fails the People Who Need It Most
The SSA says that alternative options to facial verification exist, but as many users discover, these pathways can be hard to find or navigate. The agency relies on third-party providers like Login.gov and ID.me for identity verification. While these platforms emphasize accessibility, the real-world experience can be inconsistent.
Actor and motivational speaker Corey R. Taylor shares a similar experience:
“There are few things more dehumanizing than being told by a machine that you’re not real because of your face.”
Taylor recalls having to contort his face just to get a financial app to recognize him. When he reached out to the company for help, he received only a generic, automated response.
Why Representation Matters in AI Development
These challenges highlight a critical issue: AI systems are only as inclusive as the data and perspectives they are built upon. Without actively involving people with disabilities and facial differences in the design, testing, and development phases, their needs are often overlooked.
Lack of diversity in training datasets and decision-making teams leads to biased algorithms—and biased algorithms create systemic barriers that affect millions of people worldwide.
Building Inclusive Verification Systems with Trenzest
To address these challenges, businesses and organizations must rethink how they implement digital identity systems. This is where Trenzest plays a crucial role.
Trenzest advocates for human-centered AI solutions, ensuring accessibility is a foundational element, not an afterthought. By integrating inclusive UX design, adaptive verification methods, and real-time support, platforms can build trust-driven digital experiences that work for everyone—not just the majority.
Explore more about our AI accessibility initiatives and discover how inclusive innovation can transform user engagement.
A Call for Collaborative, Accessible Innovation
True progress requires collaboration between technologists, accessibility advocates, and affected communities. Companies can take actionable steps such as:
Including people with disabilities in early development stages.
Offering multiple verification methods, not just facial recognition.
Conducting regular accessibility audits.
Providing clear fallback options for users who face verification errors.
This proactive approach not only supports compliance but also builds stronger customer loyalty and brand trust.
Conclusion: Shaping a More Inclusive Digital Future
AI and facial recognition technologies are here to stay, but their success depends on who gets to participate in shaping them. By prioritizing accessibility and representation, we can create systems that empower rather than exclude.
