by Unusual courses is an occasional series from the conversation that highlighted our unconventional approaches to teaching.
Title of course:
Art and generative AI
What was the reason for the idea for the course?
I see many students considering artificial intelligence as human, simply because it can write essays, do complex maths or answer questions. AI can simulate human behavior, but lacks meaningful involvement in the world. This decoupling inspired the course and was formed by the ideas of the 20th-century German philosopher Martin Heidegger. His work emphasizes how we are deeply connected and present in the world. We find meaning through action, care and relationships. Human creativity and control come from this intuitive bond with the world. Modern AI, on the other hand, simulates intelligence by processing symbols and patterns without understanding or taking care of it.
In this course we reject the illusion that machines fully control everything and make the expression of students first. In addition, we appreciate uncertainty, errors and imperfection as essential for the creative process.
This vision expands beyond the classroom. In the Academy Year 2025-26, the course will include a new community-based reading cooperation with Atlanta’s art communities. Local artists will find out together with me to integrate artistic practice and AI.
The course builds on my 2018 class, art and geometry, which I learned together with local artists. The course investigated Picasso’s cubism, which defeated reality as broken from multiple perspectives; It also looked at the relativity of Einstein, the idea that time and space are not absolute and different, but part of the same substance.
What does the course explore?
We start by exploring the first mathematical model of a neuron, the perceptron. Then we study the Hopfield network, which simulates how our brain can remember a song from listening to a few notes by filling in the rest. Then we look at Hinton’s Boltzmann machine, a generative model that can also imagine and make new, similar songs. Finally, we study the deep neural networks and transformers of today, AI models that simulate how the brain learns to recognize images, speech or text. Transformers are especially suitable for understanding sentences and conversations, and they power technologies such as chatgpt.
In addition to AI, we integrate artistic practice into the courses. This approach broadens the perspectives of students on science and engineering by the lens of an artist. The first offer of the course in the spring of 2025 was taught together with Mark Leibert, an artist and professor in practice at Georgia Tech. His expertise is in art, AI and digital technologies. He learned students Fundamentals from various artistic media, including charcoal drawing and oil painting. Students used these principles to create art using AI ethical and creative. They critically investigated the source of training data and ensured that their work respects authorship and originality.
Students also learn to record brain activity with the help of Elektro -Enencefalography – EEG – Headsets. Through AI models they then learn to convert neural signals into music, images and stories. This work inspired performances in which dancers improvised in response to music generated by AI.
Why is this course now relevant?
AI was introduced so quickly that many people do not fully understand how it works, why it works, when it fails or what his mission is.
When creating this course, the goal is to enable students to fill that gap. Whether they are new to AI or not, the goal is to make his inner algorithms clear, approachable and honest. We focus on what these tools actually do and how they can go wrong.
We first place students and their creativity. We reject the illusion of a perfect machine, but we lure the AI algorithm to confuse and hallucinate when it generates inaccurate or nonsensical reactions. To do this, we deliberately use a small data set, we reduce the model size or we limit training. It is in these poor situations of AI that students intervene as conscious co-creators. The students are the missing algorithm that takes back control over the creative process. Ai do not obey their creations but think of it by the human hand. The artwork is saved from automation.
What is a critical lesson from the course?
Students learn to recognize the limitations of AI and to use their failure to reclaim creative authorship. The artwork is not generated by AI, but it is re -devised by students.
Students Learning Chatbotqueries have an environmental costs because large AI models use a lot of power. They avoid unnecessary iterations when designing instructions or the use of AI. This helps reduce carbon emissions.
What will the students prepare?
The course prepares students to think as artists. Through abstraction and imagination, they get the confidence to tackle the technical challenges of the 21st century. These include protecting the environment, building resilient cities and improving health.
Students also realize that although AI has enormous technical and scientific applications, ethical implementation is crucial. Insight into the type and quality of training data that AI uses is essential. Without this, AI systems risks producing biased or inadequate predictions.
This article is re -published of the conversation, a non -profit, independent news organization that gives you facts and reliable analysis to help you understand our complex world. It is written by: Francesco Fedele, Georgia Institute of Technology
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Francesco Fedele does not work for, consults, owns shares or receives financing from a company or organization that would benefit from this article and has not announced relevant ties with their academic appointment.
