Incident 808: Infinite Campus AI-Driven Student Risk Model Leads to Cuts in Support for Nevada's Low-Income Schools

Description: An AI system developed by Infinite Campus and deployed by Nevada to identify at-risk students led to a sharp reduction in the number classified as needing support, dropping from 270,000 to 65,000. The reclassification caused significant budget cuts in schools serving low-income populations. The drastic reduction in identified at-risk students reportedly left thousands of vulnerable children without resources and support.

Editor Notes: Timeline notes and clarification: Before 2023, Nevada identified at-risk students mostly by income, using free or reduced-price lunch eligibility as the key measure. In 2022, this system classified over 270,000 students as at-risk. Looking to improve the process, Nevada partnered with Infinite Campus in 2023 to introduce an AI system that used more factors like GPA, attendance, household structure, and home language. The new system was meant to better predict which students might struggle in school. However, during the 2023-2024 school year, the AI cut the number of at-risk students to less than 65,000. This reclassification caused budget cuts in schools that depended on the funding tied to at-risk students, especially those serving low-income populations. By October 2024, the problem gained national attention.

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Alleged: Infinite Campus developed an AI system deployed by Nevada Department of Education, which harmed Low-income students in Nevada , Nevada school districts , Mater Academy of Nevada and Somerset Academy.

Incident Stats

Incident ID

808

Report Count

Incident Date

2024-10-11

Editors

Daniel Atherton

Incident Reports

Reports Timeline

Nevada Asked A.I. Which Students Need Help. The Answer Caused an Outcry.

nytimes.com

nytimes.com · 2024

Nevada has long had the most lopsided school funding in the country. Low-income districts there have nearly 35 percent less money to spend per pupil than wealthier ones do --- the largest gap of any state.

A year ago, Nevada set out to impr…

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.