In the digital age, big data algorithms are used to determine whether people get jobs, receive loans, or are convicted of a crime. Unfortunately, many of these algorithms reinforce racial and gender discrimination and are disproportionately affecting marginalized populations. As a result, it is critical for young people to have a deep understanding of data science and be empowered to enact change in their communities. However, few data science educational programs exist, particularly those that focus on algorithm bias, and there is little research on how young people learn and engage with such topics.
Co-Designing with Community Partners
In this project, we used community-based participatory design methods to co-design a data science education program for youth in after-school programs in Greenville, SC. This particular program focused on algorithm bias issues that are of interest and of importance to youth and their communities. Participants included middle-school aged youth, parents, after-school counselors and directors, and other involved members of the community center. To learn more about the community's values and approaches to digital technologies, we interviewed participants and engaged with them in existing algorithm bias curricular activities. We also asked participants to provide feedback on activities and imagine alternative approaches for educational experiences for youth. This data will be used to inform the design and implementation of a critical data science education program for youth in informal learning environments.
Arastoopour Irgens, G., Adisa, Ibrahim, Bailey, C., & Vega, Hazel. Designing with and for Youth: A Participatory Design Research Approach for Critical Machine Learning Education. Education Technology & Society. 25(4).
Bailey, C. S., Adisa, I., Vega, H., & Arastoopour Irgens, G. (2021, May). "Cognitive, Affective, and Politicized Trust in a Community Youth Program: A Participatory Design Research Project." Poster presented at the 2021 RESPECT Virtual Conference.