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RES.TLL-008 | Fall 2022 | Non-Credit

# Social and Ethical Responsibilities of Computing (SERC)

> Related Topics: Privacy and Surveillance, Inequality, Justice, & Human Rights

Author: Will Deringer

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?

### Resources:

Lecture Module: Quantifying People: A History of Social Science Lecture (PDF) PPTX - 5.8MB)

### Additional Reading:

Ernest Burgess, “Factors Determining Success or Failure on Parole,” in Andrew A. Bruce et al., A Study of the Indeterminate Sentence and Parole in the State of Illinois (Chicago: Northwestern University Press for the American Institute of Criminal Law and Criminology, 1928), 241-286.

Raymond Dussault, “Jack Maple: Betting on Intelligence: Former NYPD Map Master Puts His Money Where His Crimes Stats Are,” Government Technology (March 31, 1999).

Yeshimabeit Milner (founder of Data for Black Lives), “Abolish Big Data,” talk at Data Intersections 2020, University of Miami Institute for Data Science and Computing (February 21, 2020). [45 minutes]

Julia Dressel and Hany Farid, “The Dangers of Risk Prediction in the Criminal Justice System,” MIT Case Studies in Social and Ethical Responsibilities of Computing (February 2021).

## Course Info

##### Instructors

- Prof. Julie Shah
- Prof. David Kaiser

##### Departments

- Supplemental Resources

##### As Taught In

Fall 2022

##### Level

Non-Credit

##### Topics

- Engineering
  - Computer Science
    - Artificial Intelligence
- Teaching and Education
  - Curriculum and Teaching
  - Higher Education

##### Learning Resource Types

notes Lecture Notes
co_present Instructor Insights
assignment Multiple Assignment Types

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