by Unusual courses are an occasional series from the conversation in which we highlight unconventional teaching approaches.
Title, of course:
Art and generative AI
What did the idea have prompted the course?
I see many students who consider artificial intelligence to be human, simply because they write essays, make complex mathematics or answer questions. AI can imitate human behavior, but there is no sensible examination of the world. This separation inspired the course and was shaped by the ideas of the German philosopher of the 20th century Martin Heidegger. His work shows how we are deeply connected and present in the world. We find meaning through action, care and relationships. The human creativity and championship come from this intuitive connection with the world. The modern AI simulates intelligence by processing symbols and patterns without understanding or care.
In this course we reject the illusion that machines completely master everything and put the expression of the students in the first place. We appreciate uncertainty, mistakes and imperfections as essential for the creative process.
This vision extends beyond the classroom. In the academic year 2025-26, the course will include a new community learning cooperation with the artificial groups of Atlanta. Local artists will work with me to integrate artistic practice and AI.
The course builds on my class, art and geometry from 2018, which I work with local artists. The course examined Picasso’s cubism, which represented reality from several perspectives than broken. It also examined Einstein’s theory of relativity, the idea that time and space are not absolutely and clear, but part of the same fabric.
What does the course explore?
We start researching the first mathematical model of a neuron, the Perceptron. Then we study the Hopfield network, which imitates how our brain can remember a song if you only listen to a few notes by filling out the rest. Next we see the Boltzmann machine from Hinton, a generative model that can also imagine and create new, similar songs. Finally, we study today’s deep neural networks and transformers, AI models that imitate how the brain captures images, language or text. Transformers are particularly suitable for understanding sentences and conversations, and they power a technologies such as chatt.
In addition to AI, we integrate artistic practice into the courses. This approach extends the perspectives of the students to science and engineering through the lens of an artist. The first offer of the course in spring 2025 was worked with Mark Leibert, an artist and professor for the practice at Georgia Tech. His specialist knowledge is in art, AI and digital technologies. He taught students of the basics of various artistic media, including charcoal drawing and oil painting. The students used these principles to create art ethically and creatively with AI. They critically examined the source of training data and ensured that their work respected authorship and originality.
The students also learn to record brain activity with electroencephalography – EEG – headsets. Through AI models you will learn to transform neural signals into music, pictures and storytelling. This work inspired performances in which dancers improvised in response to A-generated music.
Why is this course relevant now?
AI entered our lives so quickly that many people do not fully understand how it works, why it works when it fails or what their mission is.
When creating this course, the goal is to strengthen the students by filling this gap. Whether you are new to the AI or not, the goal is to make your inner algorithms clearly, accessible and honest. We focus on what these tools actually do and how they can go wrong.
We place the students and their creativity first. We reject the illusion of a perfect machine, but we provoke the AI algorithm to confuse and hallucinate when it creates inaccurate or nonsensical reactions. To do this, we deliberately use a small data record, reduce the model size or limit the training. In these incorrect AI states, the students appear as conscious fellow artists. The students are the lack of algorithm that takes back control of the creative process. Your creations do not obey AI, but newly new. The artwork is saved from automation.
What is a critical lesson from the course?
The students learn to recognize the limits of the AI and use their failures to regain creative authorship. The work of art is not produced by AI, but it is reinterpreted by students.
Students learn that Chatbot queries have environmental costs because large AI models use a lot of electricity. You avoid unnecessary iterations when designing input requests or the use of AI. This helps to reduce carbon emissions.
What will the course prepare for the students?
The course prepares the students how artists think. Through abstraction and imagination, you gain trust to tackle the technical challenges of the 21st century. This includes the protection of the environment, the structure of resilient cities and the improvement of health.
The students also recognize that AI has transitional and scientific applications, but the ethical implementation is decisive. Understanding the type and quality of training data that AI uses is essential. Without them, AI systems risk having risked or incorrect predictions.
This article will be released from the conversation, a non -profit, independent news organization that brings you facts and trustworthy analyzes to help you understand our complex world. It was written by: Francesco Fedele, Georgia Institute of Technology
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Francesco Fedele does not work for a company or an organization that benefits from this article and have not published any relevant affiliations about their academic appointment.
