Data is a powerful tool for making claims - claims that can advance equity and social justice, as well as claims that can misrepresent civic issues and marginalize communities. This course examines how power operates in and through the production, analysis, and presentation of data, while helping students develop skill in approaching data science work in more ethical and equitable ways.
In this course, students will examine the sociopolitical forces that impact the availability, structure, and governance of data regarding various social justice issues. Students will also learn techniques for presenting data in ways that foreground the contexts of data production and remain accountable to diverse communities. Datasets about health equity, housing justice, environmental justice, and carceral justice will be studied, analyzed, and visualized. In doing so, students will learn to identify the diverse institutions and stakeholders involved in data production, unpack the cultural histories and vested interests animating data semantics, consider what people and problems gets erased in data structuring, and evaluate the ethical tradeoffs that data scientists grapple with as they plan for the presentation of data. See course syllabus.