Machine Vision

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Machine Vision in Everyday Life: Playful Interactions with Visual Technologies in Digital Art, Games, Narratives and Social Media is a five year, ERC-funded project that explores how new algorithmic images are affecting us as a society and as individuals. Professor Jill Walker Rettberg is the principal investigator of Machine Vision, which runs from 2018-2023. A five page project summary is available, and preliminary results

The Machine Vision in Art, Games and Narratives database gathers information about 500 video games, artworks and narratives (movies, novels, etc) that represent or simulate machine vision in various ways. The dataset is available on DataverseNO, and is documented in a data paper published in May 2022 in the journal Data in Brief.

Jill Walker Rettberg smiling in front of the BBC offices.

Jill Walker Rettberg talking about her new book on the BBC

Machine Vision on radio: About the history of humans expanding our vision with technology, on Start the Week.

Gabriele de Seta - vinner av Prisen for unge forskere 2021

Exploring how artificial intelligence affects our lives

Social scientist Gabriele de Seta is looking at how we interact with digital media in everyday life. Now he is awarded the Prize for Young Researchers for his outstanding work.

Graphical abstract for data paper on machine vision dataset

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 500 creative works, including 77 digital games, 190 digital artworks and 233 movies, novels and other narratives.
Personer sitter rundt et bord

Roleplaying AI and Technology

Jon Andreas Edland developed "Ettersynsing" as a practical master thesis in Digital Culture. Last week he ran it for AI scientists and developers at NORA's annual conference.

Screenshot of front page of database showing description and a list of works.

The Machine Vision Database

The Machine Vision Database collects information about games, art and narratives that use or represent machine vision technologies. Our aim is to trace connections, similarities and differences in the ways machine vision is invoked culturally and aesthetically.

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).