Linn Heidi Stokkedal

Linn Heidi Stokkedal
University of Bergen | UiB · Centre for the Study of the Sciences and the Humanities

Photographer and Master Student

About

7
Publications
8,517
Reads
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13
Citations
Citations since 2017
6 Research Items
13 Citations
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201720182019202020212022202302468
201720182019202020212022202302468
201720182019202020212022202302468
Introduction
I am currently writing my masters due in May 2016, where I focus on prehistoric art in a neuroscientific light.
Additional affiliations
January 2015 - February 2015
University of Bergen
Position
  • Lecturer
Description
  • Had guest lectures related to my master dissertation
September 2014 - present
University of Bergen
Position
  • Scientific Assistent
Education
August 2011 - June 2014
University of Bergen
Field of study
  • Art history/neuroaesthetics

Publications

Publications (7)
Article
Full-text available
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 technologi...
Preprint
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 technologi...
Data
This dataset 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, 191 digital artworks and 236 movies, novels and other narratives) that use or represent machine vision technologies like facial recognition,...
Article
Full-text available
Cave Art in the Upper Paleolithic presents a boost of creativity and visual thinking. What can explain these savant-like paintings? The normal brain function in modern man rarely supports the creation of highly detailed paintings, particularly the convincing representation of animal movement, without extensive training and access to modern technolo...
Conference Paper
Full-text available
Machine vision technologies are increasingly ubiquitous in society and have become part of everyday life. However, the rapid adoption has led to ethical concerns relating to privacy, agency, bias and accuracy. This paper presents the methodology and preliminary results from a digital humanities project that maps and categorises references to and us...
Preprint
Full-text available
Machine vision technologies are increasingly ubiquitous in society and have become part of everyday life. However, the rapid adoption has led to ethical concerns relating to privacy, bias and accuracy. This paper presents the methodology and some preliminary results from a digital humanities project that is mapping and categorising references to an...
Thesis
Full-text available
The aim with this master thesis is to prove that prehistoric art is worth the Westerners attention, not the least the attention of art historians. I am interested in placing prehistoric art/cave art in the spotlight, by reminding readers about the stunning craftsmanship and timeless beauty these paintings convey. I will do this by participating in...

Network

Cited By

Projects

Project (1)
Project
This five year, ERC-funded project (2018-2023), led by Professor Jill Walker Rettberg, explores how new algorithmic images are affecting us as a society and as individuals. The Machine Vision team will study theories and histories of visual technologies and current machine vision, analyse digital art, computer games and narrative fictions that use machine vision as theme or interface, and examine the experiences of users and developers of consumer-grade machine vision apps. Three main research questions are woven through all the approaches, addressing 1) new kinds of agency and subjectivity; 2) visual data as malleable; 3) values and biases. 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).