Research
Why Teaching Resists Automation in an AI-Inundated Era: Human Judgment and Non-Modular Work
Argues that claims about AI automating teaching depend on falsely treating it as modular, procedural work that can be decomposed and delegated to technology. The paper identifies specific characteristics of teaching — contextual judgment, relational dynamics, real-time adaptation — that resist decomposition into automatable subtasks. Relevant to the broader AI labor displacement debate: identifies structural features that make certain knowledge work resistant to automation regardless of model capability.
Source
↳ Follow the thread