Boston is embracing AI in its public schools, unlike NYC and LA

TEXT START: Los Angeles barred artificial intelligence from all public school classrooms this year.

The Dissection

This article converts a structural surrender into a classroom-management dispute. Boston is presented as the “responsible” middle path: teach children to use AI with guardrails, sourcing exercises, teacher supervision, and rhetoric about preserving foundational skills. New York and Los Angeles are cast as temporary quarantine zones.

The deeper function is normalization. The article assumes AI will govern the future and asks only how quickly schools should onboard children. The donor, employer expectations, and “AI Educator Ambassador” program expose the pipeline: public education is being adjusted to supply workers who can operate inside an AI-mediated economy.

The safeguards manage immediate abuse and public anxiety. They do not address ownership, concentration, surveillance, dependency, or what happens when the systems students are trained to use outperform the people being trained.

The Core Fallacy

The article mistakes AI fluency for economic sovereignty.

Learning to navigate a chatbot may make a student more employable during the transition. It does not make the student an owner or controller of AI capital. Under the Discontinuity Thesis, most students are being prepared to become more efficient Servitors, not Sovereigns.

The article also treats uncertainty about educational outcomes as uncertainty about the structural trajectory. Whether AI improves or damages writing instruction is a real local question. It does not alter P1: durable AI superiority in cognitive work; P2: the inability of institutions to preserve human-only economic domains at scale; or P3: the collapse of productive participation for the majority.

“Use AI as a thinking partner” is especially unstable. Once the machine is cheaper, faster, and more reliable at the cognitive task, the partner becomes the substitute. The human role shrinks from thinker to verifier, operator, and permission layer.

Hidden Assumptions

• Employer demand for AI-capable workers is treated as evidence of public benefit rather than evidence that schools are adapting to corporate power.
• Controlled classroom use is assumed to preserve cognition despite widespread unsupervised use outside school.
• Human judgment and critical thinking are treated as permanent complements rather than capabilities that AI can progressively absorb.
• Privacy rules and approved tools are assumed to prevent dependency and data extraction.
• AI skills are assumed to translate into durable employment rather than merely intensify competition among shrinking numbers of workers.
• The meaningful choice is framed as “teach AI” versus “ban AI,” concealing the decisive choice: own the productive systems or remain subordinate to their owners.
• Temporary bans are treated as policy alternatives rather than delay mechanisms.

Social Function

Primary classification: transition management and ideological anesthetic.

The article prepares parents, educators, and students to accept AI as inevitable while allowing institutions to debate the least frightening delivery method. It also provides elite self-exoneration: if children are taught to use the technology “responsibly,” future displacement can be framed as an education or skills problem instead of an ownership problem.

It contains a partial truth: school bans cannot permanently prevent students from encountering AI, and some operational literacy may be useful. But that truth is used to smuggle in a false conclusion—that adapting to AI is equivalent to retaining economic agency.

The Verdict

Boston is not preserving education from AI. It is converting education into an onboarding system for AI dependence. New York and Los Angeles are buying time, but without an ownership strategy their bans are hospice care, not resistance.

Both approaches converge on the same DT outcome: schools remain open while the mass employment-to-consumption circuit is dismantled around them. Boston may produce more adaptable Servitors. The bans may preserve human practice for a few more years. Neither changes who owns the machine, and therefore neither reverses the system’s obsolescence.