August 8, 2026 - 00:34

While artificial intelligence is being pitched as the next big thing in classrooms, from personalized tutoring to automated grading, there is a growing argument that the technology will not solve the core problems plaguing American education. Sonia Murrow, a professor of education, makes the case that the current enthusiasm for AI overlooks the deep, structural inequalities that determine student outcomes long before they ever log into a software program.
Murrow points out that the most significant predictors of academic success remain poverty, housing instability, and access to healthcare and early childhood education. A student who is hungry, lacks a quiet place to study, or has fallen behind in reading by third grade will not be rescued by a chatbot, no matter how sophisticated it is. The tech industry often frames AI as a great equalizer, but in practice, it tends to benefit schools with strong infrastructure, well-trained teachers, and students who already have reliable internet at home. Underfunded districts, which need the most help, often lack the devices, bandwidth, and technical support to implement these tools effectively.
Murrow argues that the focus on AI distracts from proven solutions like reducing class sizes, increasing teacher pay, and investing in school counselors. These are not flashy or profitable, but they address the human conditions that drive learning. The risk is that policymakers will see AI as a cheap substitute for real investment, allowing them to claim innovation while ignoring the systemic neglect that has widened the achievement gap for decades. Until the country confronts the root causes of inequality, AI will remain just another shiny tool that fails to fix what is broken.
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