Why does the machine punish?

Why does the machine punish?: The effects of the use of machine learning in criminal sentencing on the application of the theories of punishment

de Lange, Matthijs (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Intelligent Systems)

Lagendijk, R.L. (mentor)
Aizenberg, E. (graduation committee)
Hung, H.S. (graduation committee)

Delft University of Technology

Computer Science and Engineering

CSE3000 Research Project

2021-07-02

In recent years, the practice of risk-assessment has started to utilize machine learning to take in larger data sets and improve prediction accuracy. Simultaneously, it has expanded into the sentencing stage of the criminal justice system. This paper analyzes the effect of these developments on the consideration of the theories of punishment during sentencing. After first going over key characteristics of both the theories of punishment and the practice of risk-assessment, it presents a series of connections between aspects of machine learning enabled risk-assessment and each of the theories of punishment. It then provides developers of such systems with both general advice and advice aimed specifically at the highlighted effects, rooted in various design methodologies such as Systemic Design and Value-Sensitive Design, in order to better account for these effects. Future research can expand upon this paper both in depth and in scope: in depth by carrying out the empirical research needed to verify and improve upon the ideas in this paper; in scope by extending this research to other ethical debates surrounding machine learning in criminal justice.

machine learning
criminal justice
risk assessment
theories of punishment
sentencing

http://resolver.tudelft.nl/uuid:efc816c3-3a32-4325-a19a-aea15b3757e6

Student theses

bachelor thesis

© 2021 Matthijs de Lange