Social Justice

D-Lab & Graduate Division create inclusive data science summer program

August 9, 2023
Vanessa Navarro Rodriguez
by Vanessa Navarro Rodriguez. UC Berkeley's Social Sciences D-Lab and Graduate Division created the Data Science for Social Justice Program to address underrepresentation in data science. The program teaches diverse students critical data analysis and its applications in addressing societal injustices. The 8-week free summer course for admitted University of California students focuses on Python programming, Natural Language Processing, and value-informed data practices. It aims to empower students from underrepresented backgrounds and to bridge STEM with social justice. This blog post elaborates on the program's creation and features one of the DSSJ students, Robin López, and his reasons for participating.

My Summer Exploring Data Science for Social Justice: Learnings, Tensions & Recommendations

September 5, 2023
Genevieve Smith
by Genevieve Smith. This summer I joined the D-Lab hosted Data Science for Social Justice workshop at UC Berkeley diving into Python – including TF-IDF, sentiment analysis, word embeddings, and more – with a lens towards leveraging data science for social justice. My team explored a Reddit channel on abortion and used computational analysis to answer key questions related to abortion access from before versus after Roe vs. Wade was overturned. Computational social science is incredibly powerful, but I continue to grapple with tensions particularly as it relates to employing machine learning and large language in international research, and end with key recommendations for CSS practitioners.

Artificial Intelligence (AI) Systems, the Poor, and Consent: A Feminist Anti-Colonial Lens to Digitalized Surveillance

September 18, 2023
Alejandro Nuñez
By Alejandro Nuñez. Today’s digital age has created a sea of endless datafication where our everyday interactions, actions, and conversations are turned into data. The advancements of automated artificial intelligence (AI) systems, and their infrastructure in which they are created and trained on, have catapulted us into an era of consistent monitoring and surveillance.

Disaggregating Race and Ethnicity Categories in Census Data

November 1, 2022
Daniel Tan

The collection of race and ethnicity data by the United States Census Bureau has a long, complex, and problematic history. The Census claims that their racial categories generally reflect a social definition of race recognized in America, adhering to guidelines set by the U.S. Office of Management and Budget. In 1900, the Census recognized five racial categories: White, Black, Chinese, Japanese, and American Indian. Today, the Census collects more...