Potential Abstract: This study delves into the anti-racist affordances of data science within educational contexts through a Foucauldian lens. Drawing on critical race theory and Foucault’s concepts of power, knowledge, and regime, we explore how data-driven practices can perpetuate or challenge existing power structures and racial biases in education. By examining the ways in which data science is employed in educational settings, we seek to uncover opportunities for dismantling systemic racism and promoting equity. Our analysis reveals the complex interplay between technology, ideology, and social control in shaping educational regimes and highlights the potential for leveraging data science as a tool for anti-racist practices. Through a nuanced examination of data practices and discourses, this research contributes to ongoing discussions on the intersection of technology, race, and education, offering insights for educators, policymakers, and researchers striving to create more just and equitable learning environments.
Potential References:
- The democratic, anti-racist genome? Technoscience at the limits of liberalism
- Ethical data curation for ai: An approach based on feminist epistemology and critical theories of race
- Transverse Disciplines: Queer-Feminist, Anti-racist, and Decolonial Approaches to the University
- On Racism: An Interrogation of the Canonical Theory of Knowledge of Anti-Racism Politics
- Big Data: Inequality by Design?
