Incident 9: NY City School Teacher Evaluation Algorithm Contested

Description: An algorithm used to rate the effectiveness of school teachers in New York has resulted in thousands of disputes of its results.


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Alleged: New York city Dept. of Education developed and deployed an AI system, which harmed Teachers.

Incident Stats

Incident ID
Report Count
Incident Date
Sean McGregor

CSET Taxonomy Classifications

Taxonomy Details

Full Description

A value-added measurement based algorithm used to calculate the effectiveness of school teachers is being challenged for its lack of apparent accuracy and real-world relevance. In Rochester, New York approximately 600 teachers are disputing the results, and in Syracuse between 400-500 are disputing the results. The VAM score can be used to give raises to teachers deemed "effective" or "highly effective", but can also be used to fire teachers who are given two "ineffective" ratings in a row. Teachers criticize the algorithm for including only Math and English in the evaluation (even for teachers of other subjects as the algorithm only covers those two subjects), using school averages to calculate a single student's expected average, and high-grade-earning students being predicted to grow at literally impossible rates (to score grades higher than 100% on tests).

Short Description

An algorithm used to rate the effectiveness of school teachers in New York has resulted in thousands of disputes of its results.



Harm Distribution Basis

Other:School Teachers

Harm Type

Financial harm

AI System Description

value-added analysis algorithm used for evaluating a school teacher's effectiveness of teaching

System Developer

New York city Dept. of Education

Sector of Deployment


Relevant AI functions


AI Techniques

value-added mesaurements

AI Applications

data processing, data prediction


New York, United States of America

Named Entities

New York Department of Education, United Federation of Teachers, Sheri Lederman, Common Core, Governor Andrew Cuomo

Technology Purveyor

New York Department of Education

Beginning Date


Ending Date


Near Miss

Harm caused



Lives Lost


Data Inputs

School grades, student grades, predicted grades


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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