During my last year as a classroom teacher, I was tasked with grading 5,400 assignments. Here’s the math: 150 students x 4 quarters x 9 assignments (the number we were required to grade quarterly). Yes, some of those 5,400 were short quizzes or in-class presentations I could assess in real time. But because these were Honors and IB English language arts (ELA) classes, many other assignments were paragraphs or full-length essays. If I spent just ten minutes per essay per student, that added up to 25 hours of grading for a single assignment. By contrast, I had 7.5 hours of in-school prep time each week, and much of that time was absorbed by meetings, lesson planning, and family communication.

I loved teaching writing, but all those hours grading late at night and on the weekends snowballed into one of the largest forces that drove me out of teaching. “Set more boundaries!” I kept hearing. But nothing seemed skippable. Less planning time would’ve meant struggling through worse lessons, ignoring email would’ve meant missing updates from families and colleagues, and so on. I never figured out a way to streamline without losing something essential.

While my situation was perhaps extreme, it was hardly unique. Three-quarters of teachers who plan to leave identify “an unmanageable workload” as a key factor. Only 19 percent of teachers report working 40 or fewer hours per week during the school year (compared to 60 percent of otherwise similar working adults). And almost a third work 51 hours or more (compared to 9 percent of adult peers). Although it’s true that grading isn’t the only professional responsibility that teachers have outside regular hours, it’s high on the list for many.

With the advent of generative AI just months after I left teaching, the challenges of grading student writing ballooned, as students began submitting ChatGPT-authored work while schools scrambled to respond to the new technology. I was not sorry to have missed that shock to the system. But as I learned more, I became curious about how AI might ease teachers’ burden in other ways, especially by assisting with the time-consuming task of giving feedback on writing. Initially, I feared that AI would simply reward the most formulaic student writing or allow bias to pervade its judgments. Though I haven’t shed these concerns, I’m increasingly open to the possibility that, as long as there are humans who care about writing, we can teach AI to attend to the nuances of writing. 

Earlier this year, I spoke with a high school ELA teacher who’s doing exactly that. She explained how she “put her brain” into her school’s AI program by feeding it assignment prompts, grading rubrics, past student work, and her own past feedback on student work. As it churned out scores and comments to students, the teacher gave the AI feedback to fine-tune it in accordance with her voice and instructional priorities. Even after months of this work, she still personally reviewed all student submissions and AI-generated feedback. And, she assured me, she was fully transparent about the process with her students.

This teacher isn’t alone. Though many educators remain wary of using AI for writing feedback, the use of platforms like MagicSchool AI for this purpose is becoming more widespread.

Yet this method of grading doesn’t seem portable across contexts. For starters, only an experienced teacher could provide such sophisticated bot-training. And even though this teacher thoroughly reviews all student submissions and AI feedback, I’m skeptical that the same would be true for many others. I imagine that it would feel more efficient to treat the AI much like a human teaching assistant, by reading the feedback closely during the first few attempts and thereafter trusting the assistant to stay on course, maybe checking a couple random samples periodically. And if a teacher isn’t reading closely, they’ll save more time, but they’ll also risk losing opportunities to learn the nuances of students’ strengths and needs.  

Or, from an instructional perspective, is it enough for AI to synthesize student writing data and look for trends? Maybe it is. I honestly don’t know, and given the dearth of evidence to date, I don’t think anyone else does, either. There’s enough potential for it to be worth finding out, but with how many students, with which students, and for how long? It would be awfully nice to somehow track the use of AI-assisted writing feedback, and to formalize professional learning opportunities across schools to share both best practices and setbacks, so that teachers aren’t stuck reinventing the AI wheel via trial and error in isolated contexts.

There’s also the human element. To preserve trust, transparency with students about AI use is the bare minimum. Jessica Grose recently wrote for the New York Times about a group of students who felt “betrayed” by undisclosed teacher AI use. Teachers rightly don’t want students passing off AI writing as their own; it’s entirely reasonable for students to expect the same of teachers.

Even with complete transparency, though, I still wonder how students feel about being graded by AI. I’m doubtful that teens will buy that a teacher is really reading their work if some or all of the feedback is automated. And wouldn’t most of us, at any age, write differently for a robot audience than we would for a human audience? But maybe it’s not so terrible to have young people learning to write not just for fellow humans, but also for a robot audience. Dystopian though it may sound, that’s probably a workforce-ready skill now.

Most fundamentally, how might AI grading disrupt—or enhance—human connection? We know that student-teacher relationships are essential for teaching and learning. The act of providing feedback on student writing is inherently one that shows care: A teacher is taking the time to read, engage with, and respond to a student’s thoughts. Already something is lost when feedback is delivered through an online learning management system rather than by hand, just like a handwritten note still feels more personal than an email (source: I transitioned from accepting only hard-copy papers to requiring Canvas submissions from my undergrads circa 2014). By further depersonalizing the feedback process, relying on AI-generated feedback seems to sacrifice opportunities for authentic, one-on-one exchanges of ideas.

Yet, thinking back to that digital pile of 5,400 assignments, maybe AI grading can also support the most human elements of teaching. For example, it could give teachers more minutes in the day for relationship-building work, such as more carefully tailored lessons or family communications. Even if teachers don’t repurpose those minutes toward specific tasks, the shift to a lighter workload could help with relationships. As a teacher, I was slow in getting longer assignments turned around. If AI had helped me pick up the pace, then students might have been less annoyed with me, and they might have perceived more respect for their work. I certainly would have been less overwhelmed and better rested, which would have better enabled me to manage behavior and build rapport.

In a moment when many young people continue to feel lonely and disengaged from school, AI-assisted writing feedback has the potential to weaken the already-fragile threads holding together classroom communities and to create opportunity for strengthening those bonds. As with any instructional tool, an individual teacher’s skill in wielding it will factor into whether the benefits outweigh the risks. It also doesn’t have to be all or nothing: Teachers might rely on AI-assisted feedback for some writing tasks but not others, or they could provide both so that the student can compare the human and bot responses to their work. Personally, I remain wary of too much AI reliance—admittedly, a decade ago I was one of the last of my colleagues to switch from paper to digital submissions. But in my optimistic moments, I hope that forward-thinking teachers will uncover scalable strategies for deploying AI to make the crucial work of writing instruction more manageable and, above all, to build the relationships that matter so much for learning and for our humanity.