New York City bans generative AI for elementary and middle school students

New York City has enacted a moratorium on the use of generative AI by elementary and middle school students during the 2026-2027 school year. The policy aims to foster critical thinking and problem-solving skills among children by limiting their dependence on AI tools. Public school students from preschool to eighth grade are prohibited from using student-facing generative AI, while high school students can only use approved tools in supervised pilot or career-readiness programs. All high school students will receive twice-yearly AI-literacy lessons.

The policy also imposes limitations on individual screen time for younger students, allowing a maximum of 45 minutes in class for middle schoolers and 30 minutes for elementary school students. Exceptions are made for accessibility tools, assessments, remote learning, and approved activities such as coding and robotics. Teachers are permitted to use approved AI for lesson planning but cannot utilize it for grading, behavior monitoring, or critical decisions about students.

Schools Chancellor Kamar Samuels emphasized the importance of preserving human connection, curiosity, and creativity in education. Mayor Zohran Mamdani echoed these sentiments, stating that the policy aims to protect the well-being of students. This is not the first instance of New York banning AI in its public schools, as a similar restriction was in place at the beginning of 2023 but was later lifted due to concerns about overemphasis on risks such as cheating and inaccurate information.

The Los Angeles school district has also temporarily blocked access to generative AI tools on student devices. There is growing concern about the potential negative effects of overreliance on AI on young minds, with studies suggesting that unsupervised AI can weaken independent learning and create emotional or trust-related risks.

Cheating by students, particularly among older children, is a significant concern. Various strategies have been employed to address this issue, including handwritten work, oral tests, and AI-generated questions designed to be challenging for students to answer using large language models.