Governments Keep Claiming AI Can Replace What Teachers Do. Parents and Educators Keep Pushing Back.

When Canadian Prime Minister Carney told voters that AI in education "can meet every child where they are,"[¹] the response from educators wasn't a policy debate — it was a collective wince. "You know who can meet children where they are really, really well? Teachers," wrote commentator Phil Moscovitch in a widely circulated piece. The line got traction not because it was clever but because it named something people in classrooms have been trying to articulate for months: that government enthusiasm for AI in education tends to treat teachers as a cost to be optimized rather than a skill to be funded.

Governments are showing up across nearly every contested corner of AI discourse right now, and they're often showing up badly. Education Secretary Linda McMahon posting an AI-generated image that inaccurately depicted Ida B. Wells[²] crystallized a specific failure mode — officials deploying AI tools in contexts that require historical care, without appearing to understand what those tools do or get wrong. The reaction wasn't primarily partisan; it was about competence. Critics pointed out that an image generator producing a factually incorrect depiction of a Black historical figure, posted approvingly by a government official, compresses several layers of the AI bias problem into a single shareable moment.

On the regulatory side, the picture is equally unsteady. xAI's lawsuit against Colorado's AI bias law[³] — filed while Grok's own documented history of racist outputs was circulating online — put state governments in the unusual position of being cast as free speech villains by the very companies whose products prompted the legislation. Colorado had moved faster than most governments to codify algorithmic accountability. The lawsuit's framing, that bias regulation is a First Amendment violation, reflects how quickly corporate AI interests have learned to use civil liberties language to resist oversight. Whether courts accept that framing will shape what any government can actually mandate.

The thread connecting these episodes isn't incompetence exactly — it's a gap between what governments say AI can do and what the people closest to those claims actually experience. Educators hearing that AI can personalize learning for every student know that their underfunded classrooms lack the infrastructure to run those tools reliably. Historians and educators who caught McMahon's Ida B. Wells post know that AI image generators carry the biases of their training data into every output. The public conversation governments are trying to lead on AI keeps getting interrupted by the public pointing at the specific ways those claims fall apart. That pattern is unlikely to stop — and the politicians who figure out how to speak from inside that gap, rather than above it, will be the ones who actually move policy forward.