Ethics Lab partners with danah boyd on “Data and the Politics of Evidence” course offered this spring

This spring, Postdoctoral Fellow Alicia Patterson is embedded in Visiting Distinguished Professor danah boyd’s CCT course, Data and the Politics of Evidence.

The course integrates literature from STS, sociology, and critical data studies to examine the work of data and algorithms in organizational contexts, with a particular eye to the ecosystem of U.S. federal statistics. Students are learning why data and algorithms are never neutral and, thus, how to detect when data and algorithms are being politicized, manipulated, and weaponized. 

Together with Professor boyd and other colleagues from Ethics Lab, Patterson is crafting exercises each week for students to engage with the ethical considerations of how data is created and used in today’s world. These exercises are designed to enable students to confront how data is managed and the biases with which data is widely perceived. 

“This class is exploring how data is often created and questioning the categories used to study data. The class also invites students to ask questions such as: Who gets ownership over data? How might they do violence? If we're going to analyze data, why is objectivity often prized?” Patterson said. 

For a class tackling objectivity in data, Patterson facilitated an exercise that helped students think through what it means for data to be objective, and whether it is necessarily a beneficial quality. The students formed small groups and analyzed two different approaches to eviction data, using the Anti-Eviction Mapping Project and Eviction Lab as case studies. (The choice of case studies was inspired by a comparison in Catherine D’Ignazio & Lauren Klein’s book, Data Feminism.)

Students considered the various data sources each group uses and sorted them according to their perceived degrees of objectivity and informativeness. Reflecting on their initial sorting, they proceeded to outline criteria for determining whether a source is objective and whether it is informative.

Patterson commented on the exercise being helpful in enabling students to “weigh the differences between various data and the purposes they might serve. For example, while the local interviews might not meet typical notions of objectivity, they can provide a rich account of evictions that occur in that community.”

The exercise generated engaging discussion amongst the students as they explored their assumptions about what counts as a good source of information, and what may be lost when standardization is the priority. Students had to think through the manner in which data is categorized, and how that can play an important role in shaping its implications. In addition students were made to revisit their own perceptions of objectivity.