The epistemology of algorithmic risk assessment and the path towards a non-penology penology

Yoav Mehozay, Eran Fisher

Research output: Contribution to journalArticlepeer-review


Risk assessments are increasingly carried out through algorithmic analysis. In this article, we argue that algorithmic risk assessment cannot be understood merely as a technological advancement that improves the precision of previous methods. Instead, we look at algorithmic risk assessment as a new episteme, a new way of thinking and producing knowledge about the world. More precisely, we argue that the algorithmic episteme assumes a new conception of human nature, which has substantial social and moral ramifications. We seek to unravel the conception of the human that underlies algorithmic ways of knowing, specifically with regard to the type of penology it informs. To do so, we recall the history of criminological knowledge and analytically distinguish algorithmic knowledge from the two previous epistemes that dominated the field – the rational and pathological epistemes. Under the algorithmic episteme, consciousness, reason, and clinical diagnosis are replaced by a performative conception of humanness, which is a-theoretical, predictive, and non-reflexive. We argue that the new conceptualization assumed by the algorithmic episteme leads to a new type of penology which can be described as lacking a humanistic component, bringing Malcolm Feeley and Jonathan Simon’s “new penology” to fruition as a non-penology penology.

Original languageEnglish
Pages (from-to)523-541
Number of pages19
JournalPunishment and Society
Issue number5
StatePublished - 1 Dec 2019

Bibliographical note

Publisher Copyright:
© The Author(s) 2018.


  • algorithms
  • big data
  • episteme
  • managerial movement
  • penology
  • risk assessments


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