Journal des citations pour l'incident 808

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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Présumé : un système d'IA développé par Infinite Campus et mis en œuvre par Nevada Department of Education, endommagé Low-income students in Nevada , Nevada school districts , Mater Academy of Nevada and Somerset Academy.

Statistiques d'incidents

808

Nombre de rapports

Date de l'incident

2024-10-11

Editeurs

Daniel Atherton

Rapports d'incidents

Chronologie du rapport

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

nytimes.com

nytimes.com · 2024

Traduit par IA

translated-fr-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 s…

Variantes

Une "Variante" est un incident qui partage les mêmes facteurs de causalité, produit des dommages similaires et implique les mêmes systèmes intelligents qu'un incident d'IA connu. Plutôt que d'indexer les variantes comme des incidents entièrement distincts, nous listons les variations d'incidents sous le premier incident similaire soumis à la base de données. Contrairement aux autres types de soumission à la base de données des incidents, les variantes ne sont pas tenues d'avoir des rapports en preuve externes à la base de données des incidents. En savoir plus sur le document de recherche.