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AI and Computational Thinking in Digital Art History
Course Content

This spring semester of 2024, we are teaching a course at the University of Zurich entitled “AI and Computational Thinking in Digital Art History”


Course Content

The first segment of this course introduces the basic concepts behind Artificial Intelligence. It explores examples of computational projects, allowing students to enter the realm of Digital Art History (DAH). Students explore the endless interaction between art and science over the past two decades, focusing on the rise of Artificial Intelligence (AI) and computational methods for image analysis of art. In the second segment of the course, students engage with the topic through hands-on case studies. The case studies are tailored to showcase the application of computer methods in resolving specific art historical inquiries, with a keen focus on visual analysis of paintings. This immersive learning experience allows students to navigate through every step within an AI framework, such as introducing data and databases, understanding the different families of AI models, deciphering machine perception, and conducting exploratory data analysis. This course requires no prior knowledge of computer programming or mathematics and it is intended for students who want to understand, and possibly demystify, the AI hype and reflect on the potential challenges and promises of this groundbreaking technology.

Learning Outcome

After attending this lecture, participating in the exercise sessions, and working on the group projects, students will be able to design and carry out a Digital Art History project in a basic coding environment. They will understand the fundamentals of Artificial Intelligence and be able to incorporate computational thinking into Art Historical research practice