This Week with EdSurge podcast

Assignments, Invoices, and the AI Fix

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This week, two guests trace the true cost of AI, one in the classroom and one behind the scenes. Michael Hernandez explains how he taught himself to code so he could build a free tool that flags weak assignments before students ever think about cheating. Mi Aniefuna follows the electricity powering that same technology, tracing the invoice that lands on a district's desk long after the contract is signed. Together, their stories ask what schools are really paying for when they bring AI into the building.

WHAT YOU'LL LEARN

  • Michael Hernandez used vibe coding, describing an idea in plain language and letting AI write the code, to build the Cheat Vulnerability Index, a free tool that scans an assignment and flags where it is exposed to cheating.
  • Michael identifies three traits, originality, personal connection, and purpose, that he believes make an assignment resistant to cheating.
  • Mi Aniefuna reports that United States data centers used about 176 terawatt hours of electricity in 2023, roughly 4.4% of the countrys total electricity consumption.
  • Mi points to a Stanford review of more than 800 studies on AI in K-12 education, only 20 of which met the bar for rigorous, causal-impact research, even as adoption keeps outpacing the evidence.

STORIES MENTIONED IN THIS EPISODE

Story 1 I Used AI to Build AI-Resistant Assignments by Michael Hernandez

Story 2 Can Schools Afford an AI-First Future? by Mi Aniefuna

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HOST AND CONTRIBUTORS

Host: Ira Apfel

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