This course explores artificial intelligence as an artistic medium and a process of translation. Rather than treating AI as a black-box technology for generating finished outputs, students investigate how computational systems abstract, translate, and transform information—and how these translations can become part of their own artistic methodologies.

Through hands-on experimentation, we will unpack the structures behind AI systems: how data is collected and abstracted, how datasets construct particular representations of the world, how models learn from these representations, and how computational outputs can be translated again through different media.

Students will move beyond off-the-shelf tools and generic AI aesthetics by creating datasets, experimenting with code and neural networks, and developing computational processes situated within their own practices. The computational output is understood not as the final artwork, but as an intermediate representation that can undergo further acts of translation. An image might become material, sound might become spatial, environmental data might become interaction, or an AI system might become part of a performance.

A particular focus lies on artistic agency within these chains of translation. Every abstraction includes certain qualities while excluding others; every dataset and model therefore embodies choices. Students will critically examine these decisions, including questions of bias, authorship, automation, and the cultural and ecological implications of AI technologies.

The course asks: What happens when AI becomes a medium rather than an answer machine? Where does artistic agency lie when creation is distributed between data, algorithms, humans, materials, and environments? And how can translation between these domains itself become an artistic act?

Participants will develop an individual AI-based project embedded within their own medium—architecture, video, sound, drawing, performance, material practice, or hybrid forms. The aim is not simply technical fluency, but the ability to critically appropriate emerging technologies and transform them through one's own artistic language.

Examination Modalities

The examination takes the form of a final presentation of the developed project and its process, demonstrating both the artistic outcome and a critical understanding of the computational abstractions, translations, and decisions that shaped it.