How Technology Has Harmed Black Communities in the United States
Dr. Kai Dupe • January 8, 2025
Technology is often seen as neutral, but history shows it can reflect and amplify systemic biases.
Technology is often seen as neutral, but history shows it can reflect and amplify systemic biases. Black communities in the United States have faced harm from technologies designed or deployed in ways that reinforced discrimination. From surveillance to housing, these examples show how technological tools have been weaponized against marginalized groups.
Surveillance and Policing
Modern facial recognition technology has higher error rates when identifying Black faces, leading to false arrests. A 2019 study by the National Institute of Standards and Technology (NIST) found that African Americans were disproportionately misidentified. Historically, surveillance technology was weaponized through the FBI’s COINTELPRO program, which targeted Civil Rights leaders like Martin Luther King Jr., as
documented by the National Archives.
Redlining and Housing
In the 1930s, the Homeowners’ Loan Corporation (HOLC) created redlining maps that systematically denied Black families access to home loans. This practice is detailed in a study by the University of Richmond’s Mapping Inequality project. Algorithmic redlining persists today. A 2020 report by the National Fair Housing Alliance revealed how digital platforms reinforce historical housing discrimination.
Medical Exploitation
The Tuskegee Syphilis Study (1932–1972) denied treatment to Black men with syphilis to study the disease. This unethical use of medical technology is well-documented in a Centers for Disease Control and Prevention (CDC) report. Similarly, the cells of Henrietta Lacks, taken without her consent, became foundational for medical advancements. Her story is explored in-depth by Johns Hopkins University.
Education and Employment
Black communities face unequal access to educational technology. A 2020
Pew Research study found that Black students were less likely to have reliable internet for remote learning. In hiring, algorithms replicate biases. A 2018 MIT study revealed that automated systems often penalized Black applicants.
Environmental Racism
Urban planning technologies displaced Black communities through mid-20th-century highway construction, such as Detroit’s Black Bottom neighborhood. This is detailed in the Federal Highway Administration’s report on highway history. Today, polluting industries disproportionately affect Black neighborhoods, as shown in a 2021 Environmental Protection Agency (EPA) study.
Social Media and Misinformation
Platforms like Facebook were exploited during the 2016 election to suppress Black voter turnout through targeted misinformation campaigns. This tactic is outlined in a 2018 Senate Intelligence Committee report.
Moving Forward
These examples reveal that technology is not neutral. It reflects societal values and power structures. Acknowledging this history is essential to creating technologies that serve all communities fairly. Equity, accountability, and inclusive design must be at the forefront of technological innovation.
Representation alone will not solve the persistent racial disparities in computing.
The truth is that most software applications exist to manage information.
Artificial intelligence has become the newest member of nearly every software development team.
The true promise of computing is not found in the machines we build, but in the human potential we unlock when knowledge becomes accessible to everyone.
One of the reasons I value the MCT program so highly is that it represents more than technical knowledge.
Software engineering is not simply coding.
Companies often promote the idea that technical skill alone determines success.
Hackathons also strengthen teamwork and communication skills.
Stepping onto the campus of Morehouse College this past weekend for Admitted Students Day was more than a visit—it was a moment of reflection. As I watched young Black men walk with purpose across the yard, I found myself asking a simple but profound question: What would it have been like for me to study computer science here? My journey into computing was shaped in environments where I was often the only Black man in the room. That reality brings with it an unspoken weight—the need to prove you belong, the awareness of being watched, and sometimes, the quiet isolation that comes with underrepresentation. Standing at Morehouse, I realized that this burden is not a given. It is a condition of the environment. At Morehouse, the environment is different by design. Here, Black men are not anomalies—they are the standard. I imagined what it would feel like to learn algorithms, data structures, and software development in a space where my identity was not questioned but affirmed. Where excellence is expected, not in spite of who you are, but because of it. As a computer science professor, I understand the academic rigor required to succeed in this field. There is no shortcut through recursion, no bypass around debugging, no substitute for disciplined problem-solving. But what struck me during my visit is how much context matters. When students are free from the psychological burden of proving they belong, they can redirect that energy toward mastering the material. They can collaborate more openly, ask questions more freely, and take intellectual risks without fear. I also thought about legacy. At Morehouse, students walk the same grounds as Martin Luther King Jr.. That kind of history does something to a person. It raises the bar—not just academically, but personally. It invites students to see their education not just as a pathway to a career, but as preparation for impact. Leaving campus, I felt inspired—but also reflective. I cannot rewrite my journey, but I can appreciate what spaces like Morehouse offer the next generation. For a Black male pursuing computer science, it is more than a degree. It is an opportunity to develop skill, confidence, and identity in alignment. And that combination is powerful.
If you walk into most computer science classrooms today, you might assume that computing has always been a male-dominated field. As someone who has spent decades in the industry and now teaches the next generation of developers, I can tell you—that assumption is not only common, it’s historically inaccurate. In the early days of computing, many of the first programmers were women. Ada Lovelace is widely recognized as the first computer programmer, having written what we would now call an algorithm for Charles Babbage’s Analytical Engine. Fast forward to the 1940s, and women were programming some of the first electronic computers, including ENIAC. These were not peripheral roles. These women were solving complex computational problems, often inventing programming techniques as they went (Abbate, 2012). So what happened? From a systems perspective, the answer is not mysterious—it’s structural. In its early stages, programming was considered clerical work. It required precision, patience, and attention to detail—qualities that, at the time, were socially assigned to women. But as computing became more central to business, government, and innovation, its status changed. What was once seen as routine work became prestigious and lucrative. And when that shift happened, the demographics shifted with it. By the 1980s, we see a clear inflection point. Personal computers entered the home—but they were marketed primarily to boys. This created an early access gap that translated into confidence, experience, and eventually career pathways. At the same time, hiring practices and workplace cultures began to favor men, reinforcing a feedback loop that pushed women out of the field (Hicks, 2017). Over time, the narrative changed. Computing was no longer something women had built—it became something they were seen as entering late. But that narrative is not just incomplete—it’s a distortion. Understanding this history is not about nostalgia; it’s about accuracy. When students learn that women were foundational to computing, it reshapes how they think about the field. Diversity is no longer framed as a modern intervention—it is recognized as part of computing’s original DNA. In my classroom, I’ve seen what happens when students encounter this truth. It disrupts assumptions. It broadens participation. And perhaps most importantly, it changes who students believe belongs in this space. So, if women were the original programmers, what happened? Part of the answer lies in systems—education, marketing, hiring, and culture. But another part lies in storytelling. The stories we tell about computing shape who feels invited to participate in it. As educators, technologists, and leaders, we have an opportunity—and a responsibility—to tell that story more accurately. References Abbate, J. (2012). Recoding Gender: Women’s Changing Participation in Computing. MIT Press. Hicks, M. (2017). Programmed Inequality: How Britain Discarded Women Technologists and Lost Its Edge in Computing. MIT Press. Evans, C. L. (2018). Broad Band: The Untold Story of the Women Who Made the Internet. Portfolio. Shetterly, M. L. (2016). Hidden Figures. HarperCollins.