This is data and scripts for a paper exploring how robot and human characters interact with machine vision technologies in art, games and narratives, based on data collected in the database Machine Vision in Art, Games and Narratives as part of the ERC-funded project Machine Vision in Everyday Life: Playful Interactions with Visual Technologies in Digital Art, Games, Narratives and Social Media. See the Machine Vision Datavis repository for the raw exports, and the Database of Machine Vision in Art, Games and Narratives for a human-friendly version of the data.
The full dataset captures cultural attitudes towards machine vision technologies as they are expressed in art, games and narratives. It includes records of 500 creative works (including 77 digital games, 191 digital artworks and 236 movies, novels and other narratives) that use or represent machine vision technologies like facial recognition, deepfakes, and augmented reality.
This part of the study examines what robot and human characters do with machine vision technologies, and uses R scripts to analyse and visualise data about characters and their actions related to machine vision in the works, using variables like gender, race and sexuality to explore possible biases in their representation.
This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771800).