PhilSci Archive

Understanding risk with FOTRES?

Räz, Tim (2022) Understanding risk with FOTRES? AI and Ethics.

[img]
Preview
Text
s43681-022-00223-y.pdf - Published Version
Available under License Creative Commons Attribution.

Download (729kB) | Preview

Abstract

The present paper examines the recidivism risk assessment instrument FOTRES, addressing the questions whether FOTRES provides us with an adequate understanding of risk, whether we actually understand FOTRES itself, and whether FOTRES is fair. The evaluation of FOTRES uses the criteria of empirical accuracy, representational accuracy, domain of validity, intelligibility, and fairness. This evaluation is compared to that of COMPAS, a different, much-discussed risk assessment instrument. The paper argues that FOTRES performs poorly in comparison to COMPAS with respect to some of the criteria, and that both FOTRES and COMPAS do not show a satisfactory performance with respect to other criteria.


Export/Citation: EndNote | BibTeX | Dublin Core | ASCII/Text Citation (Chicago) | HTML Citation | OpenURL
Social Networking:
Share |

Item Type: Published Article or Volume
Creators:
CreatorsEmailORCID
Räz, Timtim.raez@gmail.com
Subjects: Specific Sciences > Artificial Intelligence > AI and Ethics
Specific Sciences > Computer Science
General Issues > Ethical Issues
General Issues > Explanation
Specific Sciences > Artificial Intelligence > Machine Learning
Specific Sciences > Medicine > Psychiatry
General Issues > Science and Society
General Issues > Technology
Depositing User: Tim Räz
Date Deposited: 31 Oct 2022 17:57
Last Modified: 31 Oct 2022 17:57
Item ID: 21315
Journal or Publication Title: AI and Ethics
Publisher: Springer
Official URL: https://link.springer.com/article/10.1007/s43681-0...
DOI or Unique Handle: https://doi.org/10.1007/s43681-022-00223-y
Subjects: Specific Sciences > Artificial Intelligence > AI and Ethics
Specific Sciences > Computer Science
General Issues > Ethical Issues
General Issues > Explanation
Specific Sciences > Artificial Intelligence > Machine Learning
Specific Sciences > Medicine > Psychiatry
General Issues > Science and Society
General Issues > Technology
Date: 6 October 2022
URI: https://philsci-archive.pitt.edu/id/eprint/21315

Monthly Views for the past 3 years

Monthly Downloads for the past 3 years

Plum Analytics

Altmetric.com

Actions (login required)

View Item View Item