Duration: since 2023
Event type: Lecture Course
Organizer: Kunstuniversität Linz
Venue: Linz, Austria

Department: Institut für Medien & Visuelle Kommunikation
Course leader: Art and image production in the context of Al

Expanded Course Description

The philosophical and artistic part of the course is a blend of visually rich lecture-seminars that delve into the intersection of intermedia art, philosophy of technology and speculative design research. The explored narratives are based on recent discourse within the field of philosophy of technology and acknowledgement of fundamental challenges that life on earth faces in the era of the so-called, fourth industrial revolution. We’re going to explore Ai as a technology of automation and algorithmic cognition, peer-to-peer computation systems, new networked infrastructures and mixed realities. We will address some topics in purely technical terms, while others through the lens of socio-humanitarian studies, derivative aesthetics, epistemic challenges posed by synthetic forms of knowledge production and, of course, design questions that these technological projections pose in both near and far futures. It is important to recognise the scale of impact of the current state of computational advancements not only on every aspect of how the world is built, but also on how it is studied. We will be exercising recognition and prediction of the trends and challenges to come, that will be central to artistic & design research. Students will be invited to look at AI, Web3 & MR both through the lenses of speculative design and practical knowledge in order to learn work with these technologies within their individual, group, commissioned or self-initiated practices.

Working with Ai artistically involves recognition of its agential capacity, suggesting dichotomy between synthetic and “natural” forms of intelligence; this should help to understand and navigate across the approaches of Ai as a tool vs Ai as a form of intelligence. Or between approaches of addressing Ai as a mere methodology of data-based statistical automation vs Ai as a new cognitive infrastructure based on a dynamic between intelligence and matter. Thus aiming to develop approaches of working coherently with Ai, via Ai, about Ai and maybe even for Ai in critically reflexive ways.