I have put a lot of thought into the additional workload I face as I try to give meaningful feedback on student writing (not only formal paper drafts but also routine interactions like discussion forum posts and e-mailed requests for help) that shows signs of AI involvement. I regularly ask AI to do things like fix HTML inconsistencies, or warn me when a new page of assignment instructions reads too much like lecture notes; but overall I feel AI has lost me far more time than it has gained. Students who rely more heavily on AI to generate their drafts are less invested in the revision process, so they get less out of my personalized feedback. (I still give it anyway.)
Of course it’s not all-or-nothing. I can still have the students annotate a printout and then talk to each other about their annotations; or I can have them talk to each other first and then write about their conversation. Students still gain a lot from an exercise where I have them trade papers and then read each other’s work out loud. AI doesn’t change any of that.
Still, I’m devoting more class time to hand-written assignments now, and even though I don’t assess every single document I collect, the logistics of handling bluebooks/copybooks, organizing make-up assignments and accessibility/accommodation requests, and the loss of time I could have spent on lectures/workshops/discussions does make my classroom quieter than I’d like.
This item from the Harvard Business Review is the first I’ve seen written from the perspective of a businessperson receiving AI-assisted work from co-workers. It’s nothing really surprising, except that as a professor I’m not directly responsible for the quality of a student’s work, at least not in the same way that a manager is responsible for the quality of the work produced by the team.
As AI tools become more accessible, workers are increasingly able to quickly produce polished output: well-formatted slides, long, structured reports, seemingly articulate summaries of academic papers by non-experts, and usable code. But while some employees are using this ability to polish good work, others use it to create content that is actually unhelpful, incomplete, or missing crucial context about the project at hand. The insidious effect of workslop is that it shifts the burden of the work downstream, requiring the receiver to interpret, correct, or redo the work. In other words, it transfers the effort from creator to receiver.
If you have ever experienced this, you might recall the feeling of confusion after opening such a document, followed by frustration—Wait, what is this exactly?—before you begin to wonder if the sender simply used AI to generate large blocks of text instead of thinking it through. If this sounds familiar, you have been workslopped. —Harvard Business Review
