Incident 40: COMPAS Algorithm Performs Poorly in Crime Recidivism Prediction

Description: Correctional Offender Management Profiling for Alternative Sanctions (COMPAS), a recidivism risk-assessment algorithmic tool used in the judicial system to assess likelihood of defendants' recidivism, is found to be less accurate than random untrained human evaluators.

Tools

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Alleged: Equivant developed and deployed an AI system, which harmed Accused People.

Incident Stats

Incident ID
40
Report Count
22
Incident Date
2016-05-23
Editors
Sean McGregor

CSET Taxonomy Classifications

Taxonomy Details

Full Description

In 2018, researchers at Dartmouth College conducted a study comparing the Correctional Offender Management Profiling for Alternative Sanctions' (COMPAS), a recidivism risk-assessment algorithmic tool, and 462 random untrained human subjects' ability to predict criminals' risk of recidivism. Researchers gave the subjects descriptions of defendents, highlighting seven pieces of information, and asked subjects to rate the risk of a defendant's recidivism from 1-10. The pooled judgment of these untrained subjects' was accurate 67% of the time, compared to COMPAS's accuracy rate of 65%.

Short Description

Correctional Offender Management Profiling for Alternative Sanctions (COMPAS), a recidivism risk-assessment algorithmic tool used in the judicial system to assess likelihood of defendants' recidivism, is found to be less accurate than random untrained human evaluators.

Severity

Minor

Harm Type

Harm to social or political systems

AI System Description

predictive self-assessment algorithm that produces scores correlating to subject's recidivism risk

System Developer

Equivant

Sector of Deployment

Public administration and defence

Relevant AI functions

Perception, Cognition, Action

AI Techniques

law enforcement algorithm

AI Applications

risk assessment

Location

USA

Named Entities

Dartmouth College, Equivant

Technology Purveyor

Equivant

Beginning Date

2018-01-17T08:00:00.000Z

Ending Date

2018-01-17T08:00:00.000Z

Near Miss

Near miss

Intent

Accident

Lives Lost

No

Infrastructure Sectors

Government facilities

Data Inputs

Questionnaire consisting of 137 factors like age, prior convictions, criminal records

Inspecting Algorithms for Bias

Inspecting Algorithms for Bias

technologyreview.com

Variants

A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.

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