Participation by invitation. Contact: Lotte Philipsen, lottephilipsen@cc.au.dk

The focus of this seminar is the relationship between AI image practices, democratization principles and digital citizenship. The seminar emphasizes the importance of understanding the ideology of images in the field of AI studies, and it discusses how art and the humanities can contribute towards exploring the democratic potentials/challenges of AI images.  

We will discuss insights gained from four different workshops on AI images conducted by AIIM over the course of this year (see below). Importantly, the seminar seeks to identify our most significant insights and discuss how they may be developed into relevant output – academic as well as in formats that extend beyond traditional academia.

The programme is a progressive three-step format:

10:00 – 12.30 (incl. coffee/croissants and short breaks): Short presentations of insights from each of the four seminars + (critical) comments and input.

12.30 – 13: Lunch

13:00 – 14.30: Discussion aimed at synthesizing insights across the four workshops and identifying the most relevant questions/issues related to AI image practices’ democratic implications.

14.30-14.45: Coffee/tea, cake

14.30-17:00 (incl. short breaks): In continuation of step 2, this discussion is aimed at identifying what output it would be relevant to work on in the future (e.g.: publications, applications, technical guides, educational material, policy brief etc.) and how it strategically would make sense to work with generating such output.  

17 – 18 (with refreshment): Small talk and big, wild ideas about AI images practices and democracy.

18- : Dinner at restaurant nearby.

Background information: the seminar’s point of departure is four different workshops conducted earlier in collaboration with external partners:

• Workshop 1 with Art Hub Copenhagen
• Workshop 2 with DokkX
• Workshop 3 with Systime
• Workshop 4 with Ritzau/Scanpix. 

The seminar is arranged by AIIM, Centre for Aesthetics of AI Images, and is generously supported by SHAPE – Shaping Digital Citizenship and Aarhus University Research Foundation.