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. 

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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.

New research

Situated Data Analysis

Jill Walker Rettberg proposes situated data analysis as a new method for analysing how personal data is always constructed and represented in specific contexts.

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.
Blurry blue image showing a crowd of people with green boxes superimposed on the image, suggesting some kind of machine vision.

The Machine Vision LARP

The ERC project MACHINE VISION has received funding from the Norwegian Research Council to develop a set of live action role-playing games exploring ethical decisionmaking and new technologies.

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Follow the Machine Vision project in Social Media

Machine Vision is growing and has a new Tumblr with weekly updates.

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).