Representations of machine vision technologies in artworks, games and narratives: A dataset.

This data paper documents a dataset that captures cultural attitudes towards machine vision technologies as they are expressed in art, games and narratives. The dataset includes records of 500 creative works (including 77 digital games, 190 digital artworks and 233 movies, novels and other narratives) that use or represent machine vision technologies like facial recognition, deepfakes, and augmented reality. The dataset is divided into three main tables, relating to the works, to specific situations in each work involving machine vision technologies, and to the characters that interact with the technologies. Data about each work include title, author, year and country of publication; types of machine vision technologies featured; topics the work addresses, and sentiments shown towards machine vision in the work. In the various works we identified 874 specific situations where machine vision is central. The dataset includes detailed data about each of these situations that describes the actions of human and non-human agents, including machine vision technologies. The dataset is the product of a digital humanities project and can be also viewed as a database at http://machine-vision.no. Data was collected by a team of topic experts who followed an analytical model developed to explore relationships between humans and technologies, inspired by posthumanist and feminist new materialist theories. The dataset is particularly useful for humanities and social science scholars interested in the relationship between technology and culture, and by designers, artists, and scientists developing machine vision technologies.

Pattern Recognition: Using Rocks, Wind, Water, Anxiety, and Doom Scrolling in a Slow Apocalypse (to Learn More About Methods for Changing the World).

In 5 months of COVID isolation, living out of a suitcase in temporary housing, countless fractal patterns emerged. I can't say if I created these patterns by looking for them, or that I know the whole world by looking at a grain of sand. The truth of the matter is that it feels like the key for massive scale change is just in front of us, but slipping from our grasp. As we move through these days, weeks, and months, we have very little time before the difference recedes again. I address this matter of concern as a matter of method in performative grounded theory piece.

Experimenting With Algorithms and Memory-Making: Lived Experience and Future-Oriented Ethics in Critical Data Science.

In this paper, we focus on one specific participatory installation developed for an exhibition in Aarhus (Denmark) by the Museum of Random Memory, a series of arts-based, public-facing workshops and interventions. The multichannel video installation experimented with how one memory (Trine's) can be represented in three very different ways, through algorithmic processes. We describe how this experiment troubles the everyday (mistaken) assumptions that digital archiving naturally includes the necessary codecs for future decoding of digital artifacts. We discuss what's at stake in critical (theory) discussions of data practices. Through this case, we offer an argument that from an ethical as well as epistemological perspective critical data studies can't be separated from an understanding of data as lived experience.