AI is assisting teachers in the classroom by taking over repetitive tasks like grading and optimizing coursework, helping students with exam prep, and more
for so many reasons—would seem to be: JUST HIRE MORE TEACHERS! https://www.nytimes.com/... Raju Narisetti / @raju : A lot of journalistic naivety when it comes to loving #AI. This is how platforms-love was in tech journalism, until recently. @nytimes: The Machines Are Learning, and So Are the Students https://www.nytimes.com/...? Amy J. Ko / @amyjko : This is a very utopian view of AI in education. Some is appropriate—there are big opportunities for some aspects of learning—but it ignores the way that software can amplify disparities, helping students with strong self-regulation skills, harming others. https://www.nytimes.com/... Hoon / @hoonparadise : Every few times a year a puff piece like comes out that promises how education will be “revolutionized” by AI and other such nonsense. This is one such article. https://www.nytimes.com/...
Context & Ripple Effects
This 2019 New York Times piece was an early, upbeat account of AI taking over grading, coursework optimization, and exam prep — and it drew immediate pushback from commentators like Raju Narisetti, who called it journalistic naivety about platforms, and Amy J. Ko, who warned that software can amplify disparities by favoring students with strong self-regulation skills. The subsequent coverage arc vindicates both readings: schools did adopt the tools, but on vendors' terms.
Six years later, the same companies are buying distribution directly — Microsoft, OpenAI, and Anthropic are funding AI training hubs for 400,000 American Federation of Teachers members, while adoption surveys show tech firms investing across US schools and colleges. The equity critique Ko raised has also matured into a specific concern that AI short-circuits the learning processes students need to use it adeptly.
First-order effects
- Teachers gain automation of repetitive work — grading, coursework optimization, exam prep support — shifting their time toward instruction, with the tools positioned as assistance rather than replacement.
Second-order effects
- Vendors responded to slow organic adoption by paying for access: the Microsoft-OpenAI-Anthropic money behind the AFT hubs turns teachers' unions into the distribution channel for classroom AI, bypassing district-by-district sales.
Third-order effects
- If the pattern holds, classroom AI consolidates around a few foundation-model providers embedded in union-endorsed training, while the disparity critique pushes schools toward curricula that teach AI use rather than just deploy it — a fight over pedagogy, not just procurement.
The trend: Education AI is moving from optimistic press coverage to vendor-funded institutional capture, with unions and disparities debates now shaping who gets the tools and how they're taught.