Critical Data Literacies
and
New York City Schools
Collaborators: Matthew X. Curinga, Antonios Saravanos
Tech giants mine personal data to amass great wealth, while machine learning algorithms influence the next song we hear, how long we go to jail, and the interest rates on our loans (among many other things). Recent work in AI ethics and critical data studies sheds light on the ways that data systems and machine learning obscure political power and provide a sheen of legitimacy and progress to unjust and oppressive systems. The strong call for computer science education and the teaching of computational literacy offers some hope for people to reclaim power and push back against these systems: both by learning to design their own alternatives and discovering ways to form political solidarity to demand justice in technology.
The New York City Schools Critical Data Literacy project is both a technological platform and educational intervention designed to explore and push the limits of computing education. We offer a programming library, online data science platform, curated data set, and curriculum that challenges students to learn core computing competencies while using data to explore critical issues regarding public urban education in New York City. The project allows both new programmers and researchers to examine school segregation, admission policies, crowding and class size, spatial relationship of schools and the urban environment, education for new Americans and students with disabilities, charter vs public schools, standardized testing, and many other topics that have a direct impact on the lives of adolescents and young adults in our City.
As researchers, this work offers insight into the what makes open data a true public resource, what role computing education must serve for robust data governance and democracy in a technological society, and how theories of education and liberation may be interpreted in computing education.