Abstract:

When AI first entered the educational conversation, the New York City Public Schools (NYCPS) banned ChatGPT in January 2023, then reversed course months later. As the largest district in the USA, NYC had been notably absent from making public any AI guidance or policy until 24 March 2026, when NYCPS released Guidance on Artificial Intelligence (AI), the first step in developing an AI playbook (to be published in June 2026) and opened the guidance to public comment. The gap in time between the emergence of AI in schools and the publication of official guidance left using AI to individual educator and student discretion. These key events demonstrate a familiar narrative; the educational system’s response to technological change moves predictably from resistance to regulation toward acceptance to eventually championing the inevitable progression of technology and its positive influence on educational outcomes and the economy.

The perceived need for comprehensive AI policy is evident with large districts issuing AI policies and playbooks. The combination of embracing technology while attempting to contain it is still a common strategy used in K-12 environments. There is no national school system or oversight in the USA; local control of schools allows each state and local authority to set their own policies. The purpose of such guidance is ensuring sound pedagogical practices, ethical and legal compliance, and protections (“guardrails”) to prioritize student safety and wellbeing.

This presentation will examine challenges when planning for systemwide technology policy as well as considering a longer view of technological development and its role in education. The case study of New York City is a starting point for a story whose narrative is revealed in flashbacks and imagined futures. How can we plan for the future without having learned lessons from the impact of past technological revolutions? The works of Neil Postman can serve as a critical lens for considering the role of emerging technology and its impact on education. In The End of Education: Redefining the Value of School (1995), Postman argues that we must consider schooling using two meanings of the word “end.” In this presentation we discuss the ends, both the “purpose” and “finish” of education. AI is viewed as both an opportunity (“purpose”) and a threat (“finish”) to education.

A deeper analysis into the why of schooling invites a layered approach to AI policy to expand upon existing strategies and solutions which are structural or operational such as promoting “AI Literacy” or framing AI as skill development for career readiness. To design a more meaningful approach to using technology within it, we can critically unpack assumptions and narratives about technology and education including what purpose school serves. Designing a policy without adequately considering technological biases is itself a kind of hallucination; the output risks being performative.

The well known implications for data privacy include using AI where algorithmic bias can make life altering decisions for students. Can we reasonably expect any technology to announce its bias? How can institutions engage self-aware leaders as humans in the loop to make sense of AI? This session concludes with professional development recommendations to guide current and future technology innovation in the education sector.

Keywords:

AI, education, policy.