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

Nevada deployed an AI system provided by Infinite Campus to identify at-risk students for state funding allocation. The machine learning system analyzed over six dozen student characteristics including GPA, attendance, discipline incidents, guardian portal usage, household composition, and home language to generate 'grad scores' from 50 to 150 for each student. Students scoring in the bottom 20 percent were classified as medium to high risk. The system reduced Nevada's at-risk student count from over 270,000 in 2022 to less than 65,000, causing many schools to lose significant funding they had relied upon. Schools like Somerset Academy's Stephanie Campus in Henderson, which serves over 250 low-income children including about a dozen homeless students, had zero students identified as at-risk under the new system. Mater Academy of Nevada saw its at-risk population drop from over 2,000 to 70 students. The system initially considered race, gender, and birth country as factors before removing them due to political pressure. Schools now receive about $2,900 per at-risk student compared to $303 under the previous system, but the dramatic reduction in identified students left many districts scrambling to slash programs and redo budgets.