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.
Entités
Voir toutes les entitésAlleged: 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 et Somerset Academy.
Statistiques d'incidents
ID
808
Nombre de rapports
1
Date de l'incident
2024-10-11
Editeurs
Daniel Atherton
Rapports d'incidents
Chronologie du rapport
nytimes.com · 2024
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Le Nevada a longtemps eu le financement scolaire le plus déséquilibré du pays. Les districts à faible revenu ont près de 35 % d'argent en moins à dépenser par élève que les plus riches --- le écart le plus important de tous les États.
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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.
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