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(un)real data : Unmasking AI's Pixel Puppetry.
Main entry:

Berger, Neja, author.

Title & Author:

(un)real data : Unmasking AI's Pixel Puppetry.

Publication:

[Place of publication not identified] : Aksioma Institute for Contemporary Art, 2024.

Description:

1 online resource.

Series:

Tactics&Practice [podcast] ; 16

Notes:
Archived and cataloged by Library Stack.
Summary:

"What exactly is in the images generated by AI? Is it possible to decode training datasets and detect biases that fusion models, such as Dall-E or Midjourney, reproduce? Eryk Salvaggio, researcher and new media artist interested in the social and cultural impacts of artificial intelligence, suggests a method that enables anyone to peel off the layers behind the datasets. Exploiting the ghost human labour needed to create images and label them, the full automation of AI dehumanizes the representation of the real, reducing it to clusters of pixels rearranged by statistical mathematical models. However, human agency and creativity are nested between the dots of the pixels, and they still give us the power to scratch at the surfaces that algorithms are constantly trying to reproduce."-- provided by distributor.

Subject:

Algorithms.
Artificial intelligence.
Automation.
Data mining.
Algorithmes.
Intelligence artificielle.
Automatisation.
Exploration de données (Informatique)
algorithms.
artificial intelligence.
automation.

Form/genre:

Interviews.
Podcasts.

Added entries:

Okretič, Marcela, producer.
Salvaggio, Eryk, contributor.
Torkar, Gašper, contributor.
Library Stack, distributor.
Library Stack.

Actions:
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