Inequality, Justice, & Human Rights

STS.047 Quantifying People: A History of Social Science

Author: Will Deringer

Lecture module: “Quantify and Punish: Data, Race and Policing from the Burgess Method to Big Data”

Keywords: ​​policing; criminal justice; race; racism; actuarial techniques; risk assessments; big data; surveillance

Questions addressed:

  • What role have quantitative data, computational methods, and social science played in the construction of modern systems of criminal justice?
  • How has quantification contributed to the injustices of modern policing and punishment—to the creation and maintenance of a system that disproportionately and unjustly targets, punishes, incarcerates, and kills people of color, especially Black citizens?
  • What can history tell us about the role that data and computation should—or should not—play in efforts to create a more just system of justice in the future?

MIT Case Studies in Social and Ethical Responsibilities of Computing

Brief, specially commissioned and peer-reviewed cases intended to be effective for undergraduate instruction across a range of classes and fields of study. Some cases are paired with active learning projects developed by students at MIT and reviewed by faculty and senior researchers.

Hacking Technology, Hacking Communities: Codes of Conduct and Community Standards in Open Source, by Christina Dunbar-Hester (University of Southern California)

Keywords: open source software; diversity and inclusion; community governance; gender; race; values in computing; codes of conduct

The Dangers of Risk Prediction in the Criminal Justice System, by Julia Dressel (Dartmouth College) and Hany Farid (University of California, Berkeley)

Keywords: algorithmic risk prediction, algorithmic bias, algorithmic fairness, algorithmic transparency, criminal justice

The Bias in the Machine: Facial Recognition Technology and Racial Disparities, by Sidney Perkowitz (Emory University)

Keywords: facial recognition, justice system, racial equity, false arrest

Who Collects the Data? A Tale of Three Maps, by Catherine D’Ignazio (MIT) and Lauren Klein (Emory University)

Keywords: redlining, social inequality and oppression, missing data, counterdata, matrix of domination, who questions

Protections for Human Subjects in Research: Old Models, New Needs?, by Laura Stark (Vanderbilt University)

Keywords: human-subjects research, informed consent, institutional review boards, big data

Algorithmic Redistricting and Black Representation in US Elections, by Zachary Schutzman (MIT)

Keywords: redistricting, algorithms, race, politics, elections

Active Learning Projects Developed at MIT

Active Learning Project: Active Learning Project on Developing Codes on Conduct (PDF) (DOCX)

An exercise in developing a code of conduct for a team-based course in Github-hosted project repositories. 

  • Associated case study: Dunbar-Hester, C. (2021). “Hacking Technology, Hacking Communities: Codes of Conduct and Community Standards in Open Source.” MIT Case Studies in Social and Ethical Responsibilities of Computing, (Summer 2021). https://doi.org/10.21428/2c646de5.07bc6308

Course Info

Learning Resource Types

notes Lecture Notes
co_present Instructor Insights
assignment Multiple Assignment Types