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Machine Vision SIGNED

Machine Vision in Everyday Life: Playful Interactions with Visual Technologies in Digital Art, Games, Narratives and Social Media

Total Cost €

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EC-Contrib. €

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Partnership

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Project "Machine Vision" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITETET I BERGEN 

Organization address
address: MUSEPLASSEN 1
city: BERGEN
postcode: 5020
website: www.uib.no

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Norway [NO]
 Total cost 1˙999˙547 €
 EC max contribution 1˙999˙547 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2017-COG
 Funding Scheme ERC-COG
 Starting year 2018
 Duration (year-month-day) from 2018-08-01   to  2023-07-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITETET I BERGEN NO (BERGEN) coordinator 1˙999˙547.00

Map

 Project objective

In the last decade, machine vision has become part of the everyday life of ordinary people. Smartphones have advanced image manipulation capabilities, social media use image recognition algorithms to sort and filter visual content, and games, narratives and art increasingly represent and use machine vision techniques such as facial recognition algorithms, eye-tracking and virtual reality.

The ubiquity of machine vision in ordinary peoples’ lives marks a qualitative shift where once theoretical questions are now immediately relevant to the lived experience of ordinary people.

MACHINE VISION will develop a theory of how everyday machine vision affects the way ordinary people understand themselves and their world through 1) analyses of digital art, games and narratives that use machine vision as theme or interface, and 2) ethnographic studies of users of consumer-grade machine vision apps in social media and personal communication. Three main research questions address 1) new kinds of agency and subjectivity; 2) visual data as malleable; 3) values and biases.

MACHINE VISION fills a research gap on the cultural, aesthetic and ethical effects of machine vision. Current research on machine vision is skewed, with extensive computer science research and rapid development and adaptation of new technologies. Cultural research primarily focuses on systemic issues (e.g. surveillance) and professional use (e.g. scientific imaging). Aesthetic theories (e.g. in cinema theory) are valuable but mostly address 20th century technologies. Analyses of current technologies are fragmented and lack a cohesive theory or model.

MACHINE VISION challenges existing research and develops new empirical analyses and a cohesive theory of everyday machine vision. This project is a needed leap in visual aesthetic research. MACHINE VISION will also impact technical R&D on machine vision, enabling the design of technologies that are ethical, just and democratic.

 Publications

year authors and title journal last update
List of publications.
2019 Linda Kronman
The deception of an infinite view – exploring machine vision in digital art
published pages: , ISSN: , DOI: 10.14236/ewic/pom19.11
Electronic Workshops in Computing 2020-03-11
2019 Jill Walker Rettberg
Et algoritmisk blikk
published pages: 1-20, ISSN: 0805-9535, DOI: 10.18261/issn.0805-9535-2019-01-03
Norsk medietidsskrift 26/01 2019-09-09

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The information about "MACHINE VISION" are provided by the European Opendata Portal: CORDIS opendata.

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