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Tech titans claim the genre inspired them. But all they’ve done is graft their politics onto stories of a better future
- by Ali Rıza Taşkale
Clipart Studio lets you cut up magazines sourced from the Internet Archive, images from Wikimedia Commons, & files you’ve uploaded, and create art collages from them. This is great — be sure to check out the gallery.
Watering your lawn in the summer can be both pragmatic and fun with so-called "silly sprinklers," designed to create amusing loops and spirals of water jets. And there's some fascinating physics at work to boot. Researchers at New York University's Courant Institute conducted a series of experiments with different silly sprinkler designs to find the answer to a longstanding problem in fluid dynamics, according to a new paper published in the Proceedings of the National Academy of Sciences.
As previously reported, the reverse sprinkler problem is associated with physicist Richard Feynman because he popularized the concept, but it actually dates back to a chapter in Ernst Mach’s 1883 textbook The Science of Mechanics (Die Mechanik in Ihrer Entwicklung Historisch-Kritisch Dargerstellt). Mach’s thought experiment languished in relative obscurity until a group of Princeton University physicists began debating the issue in the 1940s.
Feynman was a graduate student there at the time and threw himself into the debate with gusto, even devising an experiment in the cyclotron laboratory to test his hypothesis. One might intuit that a reverse sprinkler would work just like a regular sprinkler, merely played backward, so to speak. But the physics turns out to be more complicated. “The answer is perfectly clear at first sight,” Feynman wrote in Surely You’re Joking, Mr. Feynman (1985). “The trouble was, some guy would think it was perfectly clear [that the rotation would be] one way, and another guy would think it was perfectly clear the other way.”
Is all the beekeeping, baking and leatherwork just escapist fantasy or the start of a radically human approach to work?
- by Joshua Habgood-Coote
A visual proof that the sum of all positive odd numbers up to 2n – 1 is a perfect square.
Artificial intelligence is often promoted as a way to make teachers more effective by helping them write lesson plans, generate classroom materials and provide feedback to students in seconds. But one of the first randomized trials testing AI in real classrooms found that it can also undermine learning. Students whose teachers were given access to an AI teaching assistant felt less motivated to learn.
The damage was especially pronounced among students whose teachers were already weaker instructors, as measured by their performance before the experiment began. Their students also scored lower on standardized final exams, the researchers found.
“Teachers, just like students or coders, might be using AI as a crutch,” said Alp Sungu, lead author of the study and an assistant professor at the Wharton School at the University of Pennsylvania. “Instead of doing the actual work, they’re using AI to delegate the task, and that lowers the quality of their teaching.”
A draft of the study, “Generative AI Can Harm Teaching,” was released online in June and has not yet been published in a peer-reviewed journal. It echoes Sungu’s widely discussed 2024 research on how students’ use of AI is harming learning.
“Students use AI as an answer machine, not as a tool for learning, and therefore it harms learning,” said Sungu. “Here, I think teachers are potentially using AI as a material generating machine for homework, lecture notes, lesson plans, syllabus. Instead of improving their own output, they’re using AI as a replacement with very minimal interaction, and therefore the quality of output is not good enough.”
Related: Faster solutions, lower test scores: How AI is eroding math skills
Sungu’s experiment, conducted with fellow University of Pennsylvania researchers, including educational psychologist Angela Duckworth, followed 193 teachers and more than 2,800 middle and high school students in a private school chain in Turkey during the spring of 2025.
Teachers were randomly assigned either to receive access to a ChatGPT-based teaching assistant customized to Turkey’s national curriculum or to continue teaching as usual. Over 10 weeks, teachers primarily used the tool to generate lecture notes, assignments and exams.
Students whose teachers had access to the AI tool rated their classes as less enjoyable, less interesting and less important than students in the control group. The decline in intrinsic motivation was modest, but larger among students of those teachers who had already been heavier AI users before the experiment began.
Average academic achievement did not change overall. But among teachers whose students had lower marks before the experiment — a proxy for lower-performing teachers — student achievement and confidence both declined. Academic achievement was measured through externally administered standardized exams, ruling out the possibility that these teachers had different grading standards.
The study cannot explain exactly why teaching quality deteriorated. Researchers did not observe classrooms or analyze the AI-generated materials teachers used. But Sungu suspects that teachers may have been giving up one of their most effective tools.
“When you start using AI-generated material, you’re losing your personal voice,” said Sungu. “It might be technically good enough, but it doesn’t really carry your own style. If everything is very uniform, it just becomes a bit more boring.”
One possible explanation for the weaker academic performance among students of low-performing teachers, Sungu said, is that stronger teachers treat AI output as a first draft, revising and adapting it to their classrooms. Weaker teachers, he suspects, may be more likely to use AI-generated material as is.
Related: AI gives more praise, less criticism to Black students
This study is not a clean comparison between teaching with and without AI. Teachers in the control group were free to use other AI tools, making this a comparison between access to a customized AI assistant and whatever teachers chose to do on their own. If anything, Sungu said, these findings might be understating the risks of teachers relying heavily on AI-generated materials.
Still, Sungu cautions that it would be a mistake to conclude that “AI is terrible and will ruin education.” He sees a different lesson: Access to AI technology alone does not improve teaching.
The challenge is to help teachers use AI in ways that preserve human judgment and creativity. That will require teacher training programs, guardrails and better interfaces.
“As of right now, how teachers are using it organically, there is something to be worried about,” he said.
Sungu says he personally uses AI in his university teaching to create interactive games and polls that would otherwise take too long to build. “When I first get the output, it just looks great,” he said. “And then, if I don’t immerse myself in it, the examples, the numbers don’t make sense. I end up spending an equal amount of time to improve the output or calibrate it to my class.”
“It’s not a time saver,” he said.
Contact staff writer Jill Barshay at 212-678-3595, jillbarshay.35 on Signal, or barshay@hechingerreport.org.
This story about AI in teaching was produced by The Hechinger Report, a nonprofit, independent news organization that covers education. Sign up for Proof Points and other Hechinger newsletters.
The post Teachers save time with AI. Their students may pay the price appeared first on The Hechinger Report.
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