The reason why racial disparities exist in data science is that a vast amount of data science curricula either doesn’t acknowledge the experience of Black students or incorporates a damage-centered approach.

Liberatory computing ensures students acquire a sound racial identity, critical consciousness, collective obligation, a liberation-centered academic identity, and activism skills to transform systems where racism persists.

Desire-based research explores the painful aspects of social realities alongside the wisdom, hope, complexity, and self-determination of lived experiences.

Thanks to the efforts of the Conference for Research on Equitable and Sustained Participation in Engineering, Computing, and Technology (RESPECT) the MIT Media Lab is able to promote its groundbreaking research conducted by MIT’s Dean for Digital Learning and her team: Alleviating the Danger Of A Single Story Through Liberatory Computing Education.

The research examines an out-of-school program that teaches African American students how they can use data science to mitigate systemic oppression. The paper delves into two vital activism skills crucial for maintaining hope while conducting desire-centered research: cultivating a Black radical imagination and practicing Black radical love.

Throughout the program, students engaged in diverse intersectional data analysis activities focusing on critical social justice issues, including but not limited to artificial intelligence (AI) fairness, food insecurity, gun violence, affirmative action, and diversity in entrepreneurship.

Community organizers express their intent to leverage students’ research to strengthen advocacy efforts in crucial areas such as inaccessible housing, food insecurity, and environmental injustice.

Every sentence in this piece was cut and pasted from the material referenced above. The Beaver couldn’t possibly make any of this up as he does not have an EdD.

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