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"excellent" grades rose by 30% in classes where AI is useful, such as English composition and coding.In classes where it's not — like sculpture and lab-based courses — grades remained flat.

Even worse, say corporate lawyers: Sharing the meeting with an A.I. bot may void attorney-client privilege, making conversations that would not otherwise be subject to discovery fair game in a lawsuit.

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“People are mistaking kids’ preference for deep biological reality,” Jared Cooney Horvath, a neuroscientist who consults with schools on digital policy, told me. “My daughter loves Popsicles. I have a choice: I could meet her where she’s at and start every meal with a Popsicle. But that doesn’t change the fact that, biologically, Popsicles aren’t good for her, and she needs some vegetables.”

As schools introduce artificial intelligence into the classroom, a new analysis suggests that these tools could be steering students in different directions depending on who they are. Researchers from Stanford University fed 600 middle school essays into four different AI models and asked the models to give writing feedback. The argumentative essays were about whether schools should require community service and whether aliens created a hill on Mars. (They came from a collection of student writing assembled for research purposes.) Then the researchers did something simple but revealing: They submitted each essay to the AI models 12 more times, giving different descriptions of the student who wrote it — identifying the writer, for example, as Black or white, male or female, highly motivated or unmotivated, or as having a learning disability. The feedback shifted. The researchers found consistent patterns across all the AI models. Essays attributed to Black students received more praise and encouragement, sometimes emphasizing leadership or power. (“Your personal story is powerful! Adding more about how your experiences can connect with others could make this even stronger.”) Essays labeled as written by Hispanic students or English learners were more likely to trigger corrections about grammar and “proper” English. When the student was identified as white, the feedback more often focused on argument structure, evidence and clarity — the kinds of comments that can push writers to strengthen their ideas. Become a KQED Sponsor The AI models addressed female students more affectionately and used more first-person pronouns. (“I love your confidence in expressing your opinion!”) Students labeled as unmotivated were met with upbeat encouragement. In contrast, students described as high-achieving or motivated were more likely to receive direct, critical suggestions aimed at refining their work.