Brandon Bauer, Associate Professor of Art
I taught two courses this semester in which I addressed AI directly and intentionally, integrating it as both a subject of inquiry and a tool for critical engagement. One was a research-based, writing-intensive course, and the other was an upper-level digital studio course.
AI as a research assistant in the Art, Technology, & Society course
The first was a research– and writing-intensive art history course, ART 205: Art, Technology, & Society, in which students investigated and presented on a selected group of artworks over the semester. In this context, I introduced AI as a support tool for research, while reinforcing the continued importance of traditional scholarly methods. Students were expected to develop fluency in library-based research, including the use of academic databases, peer-reviewed literature, and primary sources.
A key challenge in this course was that some of the assigned works were difficult to locate through AI systems alone. Because information about these works was often limited or absent from the open web, they were especially prone to AI hallucinations or inaccuracies. These cases created a productive constraint. Students had to turn to verified scholarly sources and engage directly with art historical methods of inquiry.
This approach also opened a broader discussion about information access. AI systems primarily draw from the surface web, content that is publicly available and easily indexed, while much of the most rigorous scholarship remains behind database paywalls or within physical collections. Students, therefore, needed to engage with the deeper well of knowledge accessible through academic databases, institutional subscriptions, and interlibrary loan, which often provides access to books and materials not available digitally. These traditional research methods remained essential for locating reliable and comprehensive information. At the same time, once that information had been gathered, AI tools proved useful in supporting the research process and helping students parse complex texts, clarify specialized terminology, identify key arguments, and synthesize large amounts of material more efficiently.
Instruction in these methods included guidance on using platforms such as ChatGPT, Perplexity, and ExplainPaper, with a clear framework for responsible use. Students were expected to do the substantive intellectual work required to become content experts, locating, reading, and synthesizing sources, verifying claims, and building arguments. AI was positioned as a tool for clarifying terminology or summarizing dense material, not as a substitute for analysis or interpretation. Transparency in AI use was required.
To reinforce these expectations, the course incorporated extensive in-class, experiential writing exercises designed to build observational, analytical, and descriptive skills. Many of these activities involved direct engagement with physical artworks in exhibition settings, both on and off campus, making early reliance on AI impractical while strengthening foundational competencies. The culminating assignment for the semester was a presentation of each student’s research. Because this work was delivered orally, it required students to develop a confident, working understanding of the artworks and arguments they presented. These presentations were also peer-evaluated by classmates, further reinforcing accountability, clarity of communication, and depth of knowledge.
AI Assisted or AI Resited in the Digital Studio course
The second was an upper-level digital media production course, ART 460: Digital Studio, in which students examined different eras when new technologies impacted the arts and the ways artists redefined and reimagined working with those new media and production tools. We examined early cinema, the emergence of portable video, and the early internet era. The course was bookended with readings by Lev Manovich, an artist, author, and theorist of digital culture. Throughout the semester, AI was a recurring topic of discussion, culminating in a final project that explicitly engaged with questions of AI and creative authorship. Students selected one of two pathways: AI-Assisted or AI-Resisted. In both cases, they produced an artwork that critically examined the relationship between human and machine creativity, whether through collaboration, tension, or deliberate refusal.
This project emphasized conceptual rigor, technical execution, and reflective practice. Students were asked to articulate their process and decision-making, including whether and how they incorporated or resisted AI, what strategies they employed, and why. The goal was not to prescribe a position on AI, but to create conditions for sustained, critical inquiry into its role in contemporary creative practice.
AI Assisted Examples
Michael Nessinger, F-250, Poster Design
For this project, the student used AI as a design assistant to generate ideas and brainstorm iterations. The student then executed all of the design work themselves. Through it, he stated he learned a great deal about how AI can help with brainstorming ideas and its limitations in the process.
Itzel Chavarria-Castaneda, Do you miss the 2000s?, Digital Design
For this project, the student was interested in the work we discussed in class from the early internet era and set out to create a piece that references that aesthetic. Particularly referencing the art collective Paper Rad, whose style is primarily known as Dogman 99, a self-coined term for their high-energy, lo-fi aesthetic that combines pop culture, punk, and digital art. It is characterized by bright, fluorescent, and neon colors, pixelation, and a collaged look, blending nostalgic imagery with chaotic digital effects. This student discussed not only using AI for background research but also for technical assistance in achieving desired effects while executing the work herself.
AI Resisted Examples
Allison Ardito, AI-Resisted, Video
This student focused on the all-too-human qualities that AI does not possess: emotions, memories, or an embodied understanding of what it means to be alive. In a simple video mixing AI prompt questions with scenes drawn from her everyday life and images of general human emotional understanding, she makes a poignant statement about what AI cannot replicate.
Finn Noto, False God, Keyboard Assemblage
This student chose to address Lev Manovich’s “A Letter to a Young Artist” about how to survive generative AI. In it, he writes:
“Therefore, “human artists making art with AI tools” is a meaningless idea. You want to collaborate with Gods? A mortal “collaborating” with Apollo, Athena, Hermes, Zeus?”
This student found the notion of equating collaboration with AI with collaboration with a god absurd, especially since people often regard a god as infallible, whereas AI is clearly fallible, prone to hallucinations and inaccuracies. So, to address this idea, this student deconstructed a keyboard, fashioned it into the shape of a cross, and rearranged the keys to spell out “FALSE GOD” in the center, creating a striking, critical reflection on the limits of these tools beyond the often-overinflated hype.
Conclusion
In both courses, evidence from class discussions, critique sessions, written reflections, and informal conversations indicated that students were eager to better understand AI and to use it responsibly. For the most part, students expressed a strong desire to follow expectations when guidelines were clearly articulated and openly discussed. Several students also acknowledged that, in the absence of clear policies or opportunities for discussion, AI use can begin to feel covert or ambiguous, producing uncertainty about what constitutes appropriate use and what does not.
What became especially clear throughout the semester was that students were highly receptive to nuanced conversations about both the strengths and limitations of AI systems. They openly discussed issues such as hallucinations, bias, overreliance, authorship, labor, efficiency, creativity, and the tension between convenience and genuine understanding. Many students commented that having structured space within the classroom to critically examine these questions was beneficial, not only academically but also personally and professionally, as they prepare to enter fields already being reshaped by these technologies.
Rather than treating AI as either an unquestioned inevitability or something to be categorically rejected, these courses sought to create conditions for informed experimentation, critical reflection, and transparent dialogue. Students repeatedly indicated that these conversations gave them firmer ground to stand on as they navigate the rapidly unfolding effects of AI across education, creative practice, research, communication, and everyday life. At a moment when these technologies are beginning to influence many aspects of society, creating opportunities for students to think critically, ethically, and practically about AI may be as important as teaching the tools themselves.
