By: Rachel Ruff
As part of the Inequality Studies Minor, the Samuel DuBois Cook Center on Social Equity offers a methods course, “How To Study Inequality,” dedicated to examining different research methodologies through the lens of inequality. This interdisciplinary course equips students with both quantitative and qualitative research methods, helping them critically engage with how research can inform and perpetuate disparity.
On February 24, the students in this course had the opportunity to hear from Dr. Quran Karriem, a Postdoctoral Associate at the Cook Center, who delivered a presentation on “Participatory Design and Artificial Intelligence.” The discussion followed a section on biases and misuses of quantitative methods in perpetuating inequality, led by co-instructor Dr. Elizabeth Degefe, who encouraged students to “be careful not to always trust [these methods].”
Cook Center Postdoctoral Associate, Quran Karriem
Karriem’s presentation focused on the evolving role of participation in research and how artificial intelligence is reshaping ethical considerations in participatory design.
“Participatory design is a set of theories and practices related to end-users as full participants,” explained Dr. Karriem. “Its goal is to include the wider public in the development and deployment of systems.”
Dr. Karriem highlighted several case studies illustrating the complexities of participation. For example, in New Zealand, Maori communities have resisted open-source sharing of their cultural data to prevent European countries from using it to train AI models. An African case study demonstrated an alternative approach—open-sourcing cultural data but requiring that it be used in ways that benefit the community.
These examples, Dr. Karriem noted to the class, underscored the power dynamics inherent in data collection and how participation can either empower or exploit marginalized groups.
However, despite the potential benefits of participatory research, it has significant limitations. In some cases, participation is merely decorative, serving to legitimize pre-determined research outcomes rather than genuinely engaging communities. Algorithms can also play a role in reinforcing systemic biases, Dr. Karriem explained, cautioning that AI-generated content does not exist in isolation: Rather, it influences perceptions and power structures in ways that often go unnoticed.
“It is important, as researchers, software developers, or service providers, to think about what participatory engagements are for, and what participants get out of them. It is a good opportunity to really explore and center those concerns", notes Karriem. "Otherwise, you can easily get into situations where participatory methods don’t add much to a project, or are extractive.”
Image from S-1 Lab "Nothing Is Possible" Presentation at Frontier, Research Triangle Park, North Carolina, February 25, 2020. Photograph: Kate Alexandrite, 2020.
As the class grappled with these ideas, the discussion advanced into a consideration of some of the complexities of participation in research: notably, how social media does or does not count as participation. Dr. Karriem then showcased two of his past projects, Nothing is Possible and Minecraft Block Party, which examine participation through the intersection of art, media, and theory.
Minecraft Block Party Collage by Duke University's Speculative Sensation Lab, 2020.
For many students, Dr. Karriem’s lecture reinforced key lessons from the methods course, particularly the ethical considerations surrounding research methods. Ana Herndon, a senior majoring in Public Policy with minors in Economics and Psychology, reflected on how the class has deepened her understanding of methodological choices and their implications.
“The most valuable lesson I’ve learned in this course is the importance of selecting the right statistical tools for the questions I want to answer,” said Herndon. “I’ve become much more thoughtful about how I recruit and sample participants, ensuring that my research is intentional and inclusive.”
Similarly, Henry Stephens IV, a junior studying Sociology with a minor in Political Science, emphasized how the course has expanded his perspective on research applications.
“What sets this course apart is the opportunity to not only learn about research methods but also their practical application and societal implications,” said Stephens, such as “learning how algorithms, often seen as neutral, can actually reinforce systemic biases due to their reliance on flawed data that reflect historical inequalities. As a result, they can perpetuate discrimination while appearing objective.”
As students finish their midterm projects, the course will transition to studying qualitative research methods under the guidance of co-instructor Dr. Javier Wallace, a Race and Sport Postdoctoral Associate in Duke’s Program in Education. Wallace’s work focuses on race, class, gender, labor migration, nationality, and transnationalism, particularly in relation to athletes from the U.S., Latin America, and the Caribbean.
Learn more about the Inequality Studies Minor here.
