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By Andrea White
Communication Design Instructor

As educators, we are in a unique position to help provide our learners with a framework for deciding why and how to use a tool, if at all. And that’s just it; AI is a tool. But we are not in a position to bury our heads; college administrators are all but requiring that we teach our students how to understand this emerging technology lest we be left behind. There is little room for the ethical debate about the technology’s ability or origins (or scary futures).

In education there seems to be a growing chasm between embracing the technology (either out of obligation or admiration) and avoiding the technology altogether (either out of disciplinary fear or student cheating potential). In a discipline like design, there certainly is disciplinary fear (among many) and also a growing potential for students to cheat their way through assignments. As for the disciplinary fear, it feels like—again, much like in education—the side of embracing is winning, and design educators must embrace it as well, like it or not. We are preparing professionals for a world where they will find employment after all. But in the classroom it is another story. We need to ensure the “rails” are on this technology and that we can adequately assess what students are learning, and that they are learning.

In the age before the internet, at least in my experience, designers (in school or otherwise) would submit final designs and no one really questioned how they got there (or if the work was their own?). How else would they get there but to make it, right? As content became widely available through Google searches, and then with social platforms like Pinterest (and following that hosted design portfolio sites like Behance and Dribbble), students and professionals increasingly found inspiration online. Of course, before there was online inspiration, there were Communication Arts and Print magazines. But perhaps something changed with online references; designers could more easily place an existing reference into their software and trace it (and this became even easier with built‑in software functions such as Image Trace). Every faculty person undoubtedly has had to confront a student about their work closely imitating existing work found online (if not exactly copying). It’s an age‑old tale at this point. But with generative AI, there is no single existing reference to point at. If they used the same tactic of placing a graphic into their software to copy, we cannot simply reverse image search on Google to find the original. This poses a conundrum. Or does it?

Read more of Andrea's insights over on her substack >> Thinking About AI in the Design Classroom - by Andrea White