Liberatory Computing Framework: Empowering High School Students to Mitigate Systemic Oppression Through Data Activism (Poster 6)

• In Event: Perspectives on Promoting Algorithmic Justice in Artificial Intelligence and Machine Learning Education in K–12

Abstract

Objectives: One reason for the underrepresentation of African Americans in the field of computing is the lack of opportunities to engage with data science, particularly in ways that empower their communities. Current computing curricula do not teach students how to leverage technical skills in service of projects that are more authentic and relevant to the African Americans they are claiming to assist. While computing has the potential to change the world and has become increasingly integrated into our daily lives, the longstanding reality remains that minoritized groups, including African Americans, are underrepresented in computing fields.
Theoretical framework: I highlight Dr. El-Amin’s “liberation tools,” which state how a sound racial identity, critical consciousness, liberation centered achievement identity, collective obligation, along with essential activism skills prepare African Americans to “fight for” racial liberation. By expanding the liberation tools, I coin the term, “liberatory computing,” to reveal how computing curricula can motivate and provide African American students with practical skills to address racism embedded in society.
Methods & Data Sources: I propose two high school curricula that focus on data activism, integrating lessons on racism with the practical application of robust data science skills to support community organizers in their efforts. In the first data activism program, students utilize their data science and social justice skills to address systemic racism through an independent capstone project. In the second data activism program, students collaborate with community partners to work on a data activism project aimed at supporting minoritized groups in the Greater Boston area. We employed the Mann-Whitney U test and the Kruskal-Wallis test to assess the statistical significance of the differences between the pre- and post-survey results. Furthermore, after the program concluded, I conducted a comprehensive thematic analysis of the qualitative data collected from the interviews.
Results: This research project encompasses various essential components, such as analyzing student projects, conducting surveys and interviews, and seeking insights from community organizers. Notably, all community organizers expressed their intention to utilize the students’ data activism projects as a valuable resource to enhance their advocacy efforts. For example, one community organization plans to leverage the student’s intersectional data visualizations to advocate for policies and laws that address the issue of inland flooding in predominantly African American and low-income communities in Boston. In the second program, surveys indicated a significant increase in the number of students who now acknowledge the impact of data science in combating racism. Furthermore, interviews conducted with students who participated in the second program revealed a unanimous desire to incorporate data activism into their future endeavors. Impressively, twelve out of seventeen students discussed specific ideas on how they plan to utilize data science and social justice principles in their forthcoming pursuits.
Significance: My thesis advances the field of computing education by introducing an innovative framework for curriculum development that integrates liberation tools, known as liberatory computing. The incorporation of data activism curricula plays a vital role in empowering African American students with essential skills to confront power inequalities and drive social change through data science.

Authors

• Raechel Walker, Massachusetts Institute of Technology

• Cynthia L. Breazeal, Massachusetts Institute of Technology