Guest Blogger: Steven Brower
Steven Brower: The rabid increase and advancement of Artificial Intelligence (AI) has affected the world at large, and the visual / applied arts in specific. To that end I assembled a group of esteemed faculty to address the issue of how to respond to and teach AI in the classroom, for the new generation of designers and illustrators. Participants are Robin Landa, Distinguished Professor at the Michael Graves College, Architecture and Design / Robert Busch School of Design at Kean University, and author of myriad books on branding, advertising, communication and design; Craig Welsh of the award winning studio GoWelsh Studio and Associate Professor of Communications and Humanities, School of Humanities at Penn State; renown illustrator and Illustration Professor at Middle Tennessee State University Tony Rodriquez; From the School of Visual Arts: Peter Ahlberg, Principal of AHL&CO and Design Professor; James Daher, Emerging Media Coordinator; and Eric Corriel, Digital Strategy Director Visual Arts Press.
Special thanks to Gail Anderson, Chair of BFA Design and BFA Advertising and Creative Director Visual Arts Press at SVA.
Q: How has AI affected our field?
Landa: AI has transformed design in profound ways. Tasks that once required hours—mockups, color variations, layout experiments, storyboards, video demos—now happen in seconds. This forces us to reconsider what and how we teach, and what distinct value human designers contribute.
Welsh: Adobe has begun releasing BETA software updates in which AI tools are being integrated. Clients have begun using AI ahead of or in tandem of working with graphic designers. The results provided by AI for graphic design (logo projects) lack awareness of the technical production aspects of graphic design (resolution, file type, etc.). Younger designers have begun using AI as a kind of ‘crutch’ for thinking/making.
Ahlberg: I feel like AI has made clients assume design is easier than they already thought. Otherwise, the jury is still out.
Rodriguez: I think AI has created a kind of bully mentality among various illustration institutions and colleges—and understandably so. The Society of Illustrators, or rather some of its members, have expressed tremendous distaste for AI or AI-assisted imagery. Unlike the English department at my college, the Department of Art and Design seems to police AI-generated imagery quite heavily. Students even poke fun at one another if their hand-drawn work remotely resembles current AI aesthetics. I can’t imagine any of my illustration students being caught dead using AI to create their work. Right now, the culture suggests that doing so would be embarrassing rather than advantageous—whereas a student in a literature class might not feel the same sense of shame for using AI to assist their writing.
Career-wise, I haven’t felt many direct effects when it comes to the actual practice of creating illustration. Some people might immediately tie this question to monetary gains or losses, but I also see it as a workflow question. I can say it’s become easier to find reference materials more quickly through ChatGPT—I can locate color palettes and high-resolution references faster and with more intention than by browsing the web aimlessly. In that sense, I’m saving time. Some might argue that Pinterest already did that pre-AI, but to me, ChatGPT feels quicker, more effective, and more purposeful—it’s like having access to limitless “Pinterests,” if you will.
AI features within Photoshop have also made it easier to select and manipulate specific elements in my pieces or reference imagery. I can now isolate aspects of my compositions more intentionally, instead of painstakingly tracing with the lasso tool. I imagine there are similar AI tools speeding up workflows in other programs as well, such as Procreate.
My editorial illustration career has slowed since COVID, but it’s hard to say whether that’s due to AI or my own waning interest in that part of the industry—perhaps both. I know some publications have no qualms about cutting costs by using AI-generated imagery to accompany their articles. I’d be curious to know how a new, emerging illustrator might answer this question today.
Then there’s the data-scraping issue. I imagine this is one of the biggest challenges artists face right now, since their styles are being used—without permission—to train AI models. That feels like both an ethical concern and a kind of property theft. I know several illustrators who’ve taken companies like Midjourney and Stability AI to court over this. That said, companies like Meta and Google have likely been scraping data for decades, so the “data-scraping train” might already be too big to stop—I’m not sure.
Daher: Entry level design and production roles are changing, and young designers entering the field need to have a different set of skills, and a higher level of skill today in order to be competitive. They will also need to know how best to integrate AI into their workflow.
Ahlberg: I feel like AI has made clients assume design is easier than they already thought. Otherwise, the jury is still out.
Daher: Entry level design and production roles are changing, and young designers entering the field need to have a different set of skills, and a higher level of skill today in order to be competitive. They will also need to know how best to integrate AI into their workflow.
Corriel: I don’t think AI has dramatically affected the field of design yet. The tools are still not fully production-ready, though they are improving quickly. The most exciting vista opened up by AI is that it gives designers a much wider range of creative expression across tools and mediums that they are not specialized in. That said, like any tool, AI has clear predispositions and limitations. The principle of “quality in, quality out” still applies—low-effort prompts tend to produce low-effort, generic results that aren’t meaningfully differentiating.
Q: What advice do you have for your students?
Landa: My advice to students: Cultivate the human capacities machines can’t yet replicate—creative thinking, discerning cultural understanding (though AI is pretty decent at this), audience insight, and nuanced judgment. Learn AI tools deeply, but treat them as collaborators, not substitutes, for your creative mind.
Welsh: Start learning about the various AI image engines (Veo, Higgsfield, Nano Banana, etc.) and how each offers points of differentiation from the others. My instinct is that the manner in which we currently use software applications will change dramatically in the next 3-5 years. Work on becoming more verbally fluent and expand your vocabulary. AI will be driven by language skills, as referenced in the Large Language Models (LLMs) term for AI engines.
Rodriguez: My advice to students is the same I’d give to anyone learning to draw the figure from observation: think of AI as a tool, like your own pair of eyes. If your vision is poor, there’s nothing wrong with putting on glasses to see better—but it would be strange and pointless to let another conscious entity do the seeing for you. Balance is key.
I don’t think we should completely villainize AI any more than we should villainize any major shift that pushes humanity forward. To shun it entirely would put you at a disadvantage. It’s here to stay. Everything I mentioned about how AI has affected my workflow might seem minor individually, but together, they’ve likely made me more efficient—and will continue to do so over time.
I also encourage students to ask themselves: Where do you draw the line? It’s important to develop a moral compass around this issue. What makes art enjoyable to you? At what point does using AI make it feel less so? What feels reasonable—and what doesn’t?
For example, I love chopping garlic with a knife. My mother-in-law bought me a gadget that would make it faster, but I’ll never use it. I enjoy cutting garlic with my knife. That’s my line. I’m someone who takes joy in making things. If I ever reach a point where I’ve outsourced too much of my creative process, I’ll feel I’ve lost control—and then I’d have to ask myself: What’s the point?
Ahlberg: Develop a really strong sense of design, have a process that works for you, have good ideas, hone your eye, stay fresh, and be adaptable.
Daher: Experiment. Mix and match tools. Think of AI as another tool in your toolbox. You have to learn what it can and cannot do, and then you decide where and when it fits into your workflow. Is it part of your research, prototyping or production?
Corriel: Simply put, keep up with the technology. AI is evolving very quickly, and students would be doing themselves a disservice if they weren’t at least experimenting with it as it develops. It’s still unclear exactly where this technology will lead, but all signs point to a future in which it plays a meaningful role in design practice. Staying informed and curious about emerging tools and workflows is essential.
Q: Is there a way to use AI constructively?
Landa: AI can be a productive partner in education and practice. It accelerates prototyping, generates images for comps, handles repetitive production tasks, and serves as a writing companion. Students can use it to visualize concepts, explore imagery, and fill gaps in knowledge. AI should enhance the design process, not replace it.
Welsh: Yes. However, I believe ‘constructively’ assumes that one using AI has already developed a solid skill set in critical thinking, which is likely NOT the case. The immediacy of how the AI tools work will probably result in less thought from the one using AI.
Ahlberg: Probably. It’s still such a new technology and design is so complex and multi-disciplinary that I’m not sure its impact can be fully understood.
Daher: Is there a way to use AI constructively? Now I’m curious how to use it destructively. I like to use AI to build code for complex web projects that would traditionally require a developer.
Corriel: Absolutely. One of the most constructive uses of AI right now is to support creative work in areas outside your primary specialization. For example, a graphic designer can use AI prompt a professional photoshoot or a 3D product design into existence without needing to organize a full shoot or develop deep expertise in Maya. This is incredibly exciting in my opinion.
Q: Are you concerned about plagiarism?
Landa: Plagiarism concerns, while valid, miss the deeper issue: are students learning to think like designers, or outsourcing that thinking to machines? The greater risk isn’t cheating but the erosion of design judgment. That’s why we must teach AI.
Welsh: Yes. I have a difficult time trying to wrap my thoughts around how the plagiarism stuff isn’t an inherent inevitability with nearly all AI, unless the source material provided to the AI engine is all original.
Rodriguez: I’m not particularly concerned about plagiarism or art theft among humans. Given how interconnected we all are, it’s relatively easy to spot theft, call someone out, and have content removed. That said, most artists can’t realistically register every single piece they make with the U.S. Copyright Office. I tell my students to use their intuition: if there’s an image they think might be problematic—or has the potential to gain popularity—they might consider registering that one.
For example, I did a portrait of poet Terrance Hayes for The New Yorker. Most people don’t know who Terrance Hayes is, so I likely won’t register that piece. Art theft will never disappear entirely; every now and then, I still get kind messages from customers alerting me that someone has reprinted my work on apparel or other products. Sometimes it feels like that train is too big to stop, especially with older unregistered works.
As for my students, plagiarism is rare. When it does occur, peers usually call it out immediately. I don’t think anyone can sustain a creative career built on theft—it’s not habit-forming for most and is usually nipped in the bud early.
Regarding AI, I do think there should be legislation to monitor art theft, lifting, style replication, and model training. However, I’m not entirely convinced that illustrators should be compensated every time their work is used to train models—that might be a stretch. After all, we don’t currently pay search engines for the reference images we use in our own work. That’s debatable, of course, but it’s how I see it at the moment.
Landa: Plagiarism concerns, while valid, miss the deeper issue: are students learning to think like designers, or outsourcing that thinking to machines? The greater risk isn’t cheating but the erosion of design judgment. That’s why we must teach AI.
Ahlberg: Yes but no more than usual. There was and still is no shortage “creatives” who make careers off of copying the work of other people and never giving credit. AI just does it faster.
Daher: I can usually tell when something has been created by AI. My students don’t hide when they use it, we talk about it and understand that it’s important to know what its limitations are and I’m okay with them experimenting with AI, as long as they are upfront about it.
Corriel: Not any more than I have been historically. In some ways, AI has actually made plagiarism easier to detect. Low-effort prompts tend to be used by low-effort students, and the resulting outputs often cluster in recognizable ways, making patterns of cheating more visible. Time will tell whether this continues, but so far, I’ve found it easier to identify plagiarism than under previous paradigms, where students might outsource work to individuals who would produce unique—though still academically dishonest—work.
Q: Should it be taught and discussed in the classroom, and if so, how?
Landa: Ignoring it would be anachronistic. Students should engage hands-on with AI tools, critique their outputs, and identify what the technology fails to grasp.
Welsh: Yes. At this stage, my feeling is that a wide range of AI tools should be demonstrated with key points of differentiation highlighted. There are some pretty technical aspects to some of the AI graphic/motion engines and such intense skills should be reviewed. Additionally, I believe the classroom will always lag the industry with AI tools — almost need to have AI training provided by industry experts (via video/streaming) while in a classroom with an instructor who can help facilitate Q&A, act as moderator, and be available to assist students beyond the video interactions.
Welsh: Yes. At this stage, my feeling is that a wide range of AI tools should be demonstrated with key points of differentiation highlighted.
Rodriguez: I absolutely think AI should be discussed in the classroom. Students need to understand what they’re dealing with and what to expect as technology evolves. I believe these discussions should be reciprocal—teachers should not only share their perspectives but also learn from students about how they’re using AI in their creative practices. For example, I’ve learned a great deal from my students who use Procreate. The journey should be collaborative.
My university offers both optional and mandatory training sessions about AI use, including its ethical and moral implications. I think students should be required to engage in some of these trainings so that we can collectively cultivate a shared understanding of how to navigate AI responsibly as a creative community.
Faculty, too, should stay current within their disciplines. In the Adobe ecosystem, for instance, professors should keep up with AI-related updates so they can help students problem-solve more efficiently. I’ve been considering adding a more intentional AI component to each of my illustration projects—highlighting specific tools as AI features rather than just glossing over them as software updates.
I’ve also thought about using Midjourney or Stable Diffusion in class to show students how AI can serve as a creative reference tool rather than a shortcut. I want to lean into these technologies—especially emerging video-based models—to better understand how to use them productively. Pretending AI isn’t there or villainizing it doesn’t help anyone. I’d rather “run into the AI storm” than run away from it.
Rodriguez: I absolutely think AI should be discussed in the classroom. Students need to understand what they’re dealing with and what to expect as technology evolves.Faculty, too, should stay current within their disciplines. In the Adobe ecosystem, for instance, professors should keep up with AI-related updates so they can help students problem-solve more efficiently.
Rodriguez: I absolutely think AI should be discussed in the classroom. Students need to understand what they’re dealing with and what to expect as technology evolves.Faculty, too, should stay current within their disciplines. In the Adobe ecosystem, for instance, professors should keep up with AI-related updates so they can help students problem-solve more efficiently.
Ahlberg: Yes, you can’t not address it. But the “it” is always changing so it’s impossible to say how.
Daher: Absolutely! I think it should be discussed critically and I like to teach how it can be used for rapid prototyping. For example: there are certain things Figma can’t do, and with AI it’s really easy to build a website using CSS, Javascript and html markup language. Not just to build a simple website, but to experiment with fun, playful and hopefully innovate approaches to interaction.
Corriel: In general, yes. As with any emerging technology, AI should be taught and discussed, though the specifics will naturally depend on the course. If we believe AI is likely to play a role in the future of creative practice, then there’s little reason not to address it in the classroom so students can understand its capabilities, limitations, and implications.
Q: What about the ethical issues of using AI for commercial work?
Landa: Ethical questions remain urgent. Many AI systems were trained on artists’ work without consent, raising concerns about authorship, ownership, and compensation. (In fact, Anthropic pirated five of my own books!) Designers must navigate these gray areas with transparency and respect for creative labor.
Welsh: Total mess. Unless using unique, original source materials from which the resulting output is based. AI will also likely expand the socio-economic disparity between the ‘haves’ and ‘have nots’. Some AI engines are free to use at the moment but that will most likely change as the tools/companies move beyond the start-up phase, at which point some users will not be able to afford AI.
Rodriguez: If you’re typing “Abraham Lincoln drinking a Diet Coke” into an image generator and submitting the low-resolution result to an art director as your own work—that’s clearly wrong. However, if you’re using that generated image as reference for a pose or composition that you then reinterpret through your own artistic process, I think that’s perfectly acceptable. It makes you more efficient without compromising integrity.+
I believe most artists, regardless of generation or discipline, understand that distinction instinctively.
Landa: Ethical questions remain urgent. Many AI systems were trained on artists’ work without consent, raising concerns about authorship, ownership, and compensation. (In fact, Anthropic pirated five of my own books!) Designers must navigate these gray areas with transparency and respect for creative labor.
Ahlberg: “Using” has to be defined a bit better since if there are ethical concerns it might depend a little on where along the way someone or a team is making use of the technology. But I’m also not sure ethics play a big role in commercial design work.
Daher: I’m concerned about the environmental strain, and the “circular investment loop” between Navidia, Oracle and Open Ai, for example. When will the bubble burst?
Corriel: The legal and ethical frameworks around AI and commercial use are still evolving and, in many cases, actively being litigated. That said, some platforms—such as Adobe Firefly—have made efforts to ensure clean licensing of training data and generated outputs, making them more viable for commercial use. Beyond that, it’s essential for designers to do their due diligence and clearly understand what is and isn’t permitted when using AI in professional contexts.
Q: Does the rise of AI-generated art diminish the value of traditional artistic skills in favor of verbal prompts?
Landa: AI redefines traditional skills and their value. Manual execution matters less, while conceptual and creative thinking, taste, and curation matter more. You can’t prompt effectively without understanding composition, typography, and visual hierarchy. The designer’s eye remains irreplaceable.
Welsh: I hope it does the opposite. I hope that traditional skills increase in value as more of the world becomes visually synthetic. It’s the difference between someone taking time to make a meal from scratch vs. microwaving a frozen, packaged meal.
Ahlberg: This assumes a lot about “art” and people’s relationship to it along with ideas around craft, ownership, representation, authenticity, experience, etc. If art is simply about executing realistic drawings or pretty paintings or well-lit portrait photography in different tools/styles/colors then sure, AI risks diminishing artistic skills. But also, the “value of traditional artistic skills” has probably been on the decline for many, many decades.
Daher: I do not think it diminishes the value of traditional artistic skills; it may make them more valuable.
Corriel: No, I don’t think it does. AI-generated art, like computer-generated art before it, will exist alongside other forms of artistic practice. As with any medium, the resonance and value of the work will depend on the skill, intention, and emotional impact behind it—not on the tools used to produce it.
Q: Should design professors teach AI, or will it make design jobs obsolete?
Landa: Absolutely. Some roles have disappeared, but others will emerge for those who can direct, refine, and ethically apply AI. Our responsibility as educators is to prepare students for this hybrid discipline.
Welsh: Design professors will most likely have to concede to AI tools. If professors don’t quickly figure out how to co-exist with AI, I believe the role of design professor will be replaced by DIY, YouTube, How-To videos. That will likely take us down a path of widely homogenized work yet designers and clients will be enthralled by the ‘Wow!’ factor of what the AI engines produce.
Corriel: I strongly believe AI will not make design jobs obsolete, though it will make certain design tasks obsolete—and that’s likely a good thing.
Ahlberg: They should teach what they know technically and strategically, they should teach how to see and how to think, they should convey their experiences to students so that students can learn from them. AI will play a role and probably eliminate chunks of all professions but also probably create new opportunities.
Daher: I think it depends on the course. Not every design professor needs to teach AI. However, it should be integrated into classes that are teaching technical skills. Some design and production jobs will become obsolete, but students learning AI will help keep them competitive and ready for new roles and opportunities.
Corriel: I strongly believe AI will not make design jobs obsolete, though it will make certain design tasks obsolete—and that’s likely a good thing. There’s no particular reason humans should continue doing highly technical, repetitive work like rotoscoping when designers could instead focus on higher-level creative and strategic decisions. Organizations and individuals will always need ways to differentiate themselves, and designers will continue to play that role—just with an ever-expanding toolkit. That evolution should ultimately be an exciting one for the design community at large.
Question for students: How do you feel about AI? Is there anything else that should be addressed? Have you experimented with it? Do you feel it is being handled correctly in the classroom? As we enter this brave new world, your input here would be invaluable. Leave a Reply in the Comments below near the bottom of the page.
Contributors
Robin Landa, Kean University
https://www.robinlanda.com/
Craig Welsh, Penn State University
https://www.gowelsh.com/
Tony Rodriquez, Middle Tennessee State University
https://www.tonyrodriguezillustration.com/
Peter Ahlberg, School of Visual Arts
https://www.ahlandco.com/
James Daher, School of Visual Arts
https://jamesdaher.com/
Eric Corriel, Visual Arts Press
https://ericcorrielstudios.com/
Gail Anderson, School of Visual Arts
https://www.gailycurl.com/
Steven Brower, Marywood University
https://www.stevenbrowerdesign.com/
All images featured in this article were generated by the blog’s Editor-in-Chief