The Homework Machine Ep 3 "The Duplicitous Nature of Humanity"

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Aug 12, 2025

In this engaging discussion, Joe O'Hara, a high school chemistry teacher from Chicago, tackles the challenges of AI-assisted cheating in classrooms. He shares clever detection strategies, emphasizing the importance of evidence-gathering like screen monitoring. O'Hara explores the moral dilemmas teachers face between punishment and education, advocating for clear communication with parents to build trust. His innovative approach includes AI-proofing assignments, designing projects that promote ownership, and adapting to the evolving landscape of education.

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INSIGHT

AI Produces Convincingly Polished Work

Generative AI makes it unusually easy to produce polished, comprehensive student work that may not match their voice.
Teachers often detect AI use by mismatched vocabulary, syntax, or suddenly sophisticated punctuation.

ANECDOTE

Live Monitoring Caught Copy‑Paste Cheating

A teacher watched a student paste each question into Grammarly and copy back full answers via GoGuardian monitoring.
The teacher confronted the student in a chat: “I'm watching you cheat right now.”

INSIGHT

Discipline Dilemma And Equity Concerns

Teachers balance avoiding unfair discipline with preventing students from missing learning by cheating.
Historical disparities in discipline make teachers cautious about accusing students of AI misuse.

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Teachers have all sorts of opinions about AI. Some are optimistic, some are pessimistic. But the most common topic that came up in our interviews was cheating.

While students have always taken shortcuts to complete their work, ChatGPT and other generative AI have a historically unique power to quickly, convincingly and comprehensively do a students’ assignment. This is proving a powerful temptation to students.

So how do teachers help their students make good decisions? Teachers know that schools have historically struggled to manage discipline fairly but they also recognize that letting students get away with cheating isn’t doing them a favor. Teachers share how they’re navigating the Scylla and Charybdis of school discipline in the AI age.

Listen to a bleeped version of this episode (Coming soon!).

Transcript coming soon!

This episode was produced by Jesse Dukes with Yebu Ji.
Editing: Alexandra Salomon and Ruxandra Guidi
Reporting and research from Natasha Esteves, Andrew Meriwether, Holly McDede, Andrew Parsons, Marnette Federis, and Chris Bagg.
Sound design and music supervision by Steven Jackson.
Production assistance from Nathan Ray.
Data analysis from Manee Ngozi Nnamani and Manasa Kudumu.
Special thanks to Josh Sheldon, Camila Lee, Liz Hutner, and Eric Klopfer.
Administrative support from Jessica Rondon.

Thanks to the teachers who spoke to us including Joe O'Hara, Alec Jensen, Schuyler Hunt, Anna Rose Pandey, Ray Salazar, and Jessica Petit-Frere. And thanks to all the teachers and students who partipated in our research.

Thanks to Greer Murphy and Jessa Kirk, at UC Santa Cruz's Office of Academic Integrity. Check out Greer Murphy's co-authored survey of academic integrity policies.

The research and reporting you heard in this episode was supported by the Spencer Foundation, the Kapor Foundation, the Jameel World Education Lab, the Social and Ethical Responsibility of Computing initiative at MIT, and the RAISE initiative, Responsible AI for Social Empowerment and Education also at MIT.

We had support from Google’s Academic Research Awards program.

The Homework Machine is a program of the MIT Teaching Systems Lab, Justin Reich, director.