Uncommon courses are a random series from a conversation where we emphasize the unconventional teaching method.
Name, of course:
Art and generative ai
What prompted the course idea?
I see that many students who value artificial intelligence as human, simply because they can write essays, do complex mathematics, or answer questions. PG may mimic human behavior, but it lacks meaningful communication with the world. This disconnection inspired the course and was formed by the idea of the 20th century German philosopher Martin Heidegger. His work emphasizes how deeply we are related and present in the world. We find meaning in actions, care and relationships. Human creativity and craftsmanship stems from this intuitive connection with the world. Contemporary AI, on the contrary, mimics the intelligence by processing symbols and patterns without realizing or worrying.
In this course, we reject the illusion that machines completely master everything and first bring students’ expression. In doing so, we value uncertainty, mistakes and imperfection as the necessary creative process.
This vision expands outside the class. The 2025-26 school year will include a new cooperation between community learning with Atlantic art communities. Local artists will integrate artistic practice with me together.
The course is based on my 2018 class, menu and geometry, which I and local artists. The course explored Picasso’s cubism, which depicted reality as broken from many perspectives; It also looked at Einstein’s relativity, the idea that time and space is not absolute and unique, but part of the same fabric.
What does the course explore?
We start exploring the first mathematical neuron model, Perceptron. Then we explore the Hopfield network that mimics how our brains can remember the song, just listening to a few notes, filling the rest. We look at Hinton’s Boltzmann Machine, a generative model that can also imagine new, similar songs. Finally, we are exploring today’s deep nerve networks and transformers, AI models that imitate how the brain learns to recognize images, language or text. Transformers are particularly good for understanding sentences and conversations, and they feed on technologies such as Chatgpt.
In addition, we integrate artistic practice into coursework. This approach broadens the perspectives of student science and engineering through the artist’s lens. First course offer 2025 In the spring, he was with Mark Leiber, an artist and practice professor Georgia Tech. Its competence is art, ai and digital technology. He taught students the basics of various art media, including charcoal drawing and oil painting. Students used these principles to create art using AI ethically and creatively. They critically investigated the source of teaching data and ensured that their work respects authorship and originality.
Students also learn to record brain activity using electroencephalography – EEG – headphone. As part of AI models, they learn to turn nerve signals into music, images and narrative. This work encouraged the shows where the dancers improvised by responding to the music created by A.
Why is this course relevant now?
AI has entered our lives so quickly that many people do not fully understand how it works, why it works when it fails or what its mission is.
When creating this course, the goal is to give students the opportunity to fill that gap. Whether they are new AI or not, the goal is to make your own internal algorithms clear, accessible and honest. We focus on what these tools actually do and how they can go wrong.
First we set out students and their creativity. We reject the illusion of the perfect machine, but we provoke an Ai algorithm to confuse and hallucinate when it creates inaccurate or unconscious answers. To do this, we consciously use a small data set, reduce model size, or limit training. It is in these flawed states that students get involved in conscious creators. Students are the missing algorithm that takes over the management of the creative process. Their creation does not obey hes, but re -imagine it by man’s hand. A work of art is saved from automation.
What is a critical lesson from the course?
Students learn to recognize AI restrictions and use its inability to recover creative authorship. The work of art is not caused by AI, but it was rethought by students.
Students study Chatbot requests for environmental costs as large PG models consume a lot of power. When designing calls or using AI, they avoid unnecessary iterations. This helps to reduce carbon emissions.
What is the course to prepare students?
The course prepares students to think as artists. Due to abstraction and imagination, they gain confidence to overcome 21st century engineering challenges. These include environmental protection, development of cities and health improvement.
Students also understand that although AI has a huge engineering and scientific program, ethical implementation is very important. It is necessary to understand the type and quality of the training data used by AI. Without it, AI systems risk a biased or flawed forecast.
This article has been published from a conversation, non -profit, independent news organizations that provide you with facts and reliable analysis to help you give meaning to our complex world. It was written by: Francesco Fedel, Institute of Georgia Technology
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Francesco Fedel is not working, consulting, having any company or organization or receiving funds for which it would benefit from this article, and has not disclosed any important relationships except for their academic appointment.