Diffused Seeing
This article examines the transformation of the relationship between seeing and understanding in humans and machines by the technologies of machine learning known as ‘generative AI’. Taking Stable Diffusion as the main case study, while also looking at its competitors (DALL·E 2 and Midjourney), it...
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Format: | Article |
Language: | English |
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Simon Dawes, Centre d’histoire culturelle des sociétés contemporaines (CHCSC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)
2024-06-01
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Series: | Media Theory |
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Online Access: | https://journalcontent.mediatheoryjournal.org/index.php/mt/article/view/1075 |
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author | Joanna Zylinska |
author_facet | Joanna Zylinska |
author_sort | Joanna Zylinska |
collection | DOAJ |
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This article examines the transformation of the relationship between seeing and understanding in humans and machines by the technologies of machine learning known as ‘generative AI’. Taking Stable Diffusion as the main case study, while also looking at its competitors (DALL·E 2 and Midjourney), it starts by analysing the photographic infrastructure underpinning these generative models. The subsequent examination of ‘diffusion’ as a key concept that underpins the text-to-image generation process leads to some broader questions about the ongoing instability and dissolution of our current epistemological and political frameworks. Taking seriously the charge issued by some critics equating developments in generative AI with nihilism or even fascism, the article considers whether the current socio-technical moment can also offer some emancipatory possibilities. Images are used as part of the article not just by way of illustration but also to enact some of its argument.
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format | Article |
id | doaj-art-024dc5eb9b8b4ac6be09cd7d8aa484aa |
institution | Matheson Library |
issn | 2557-826X |
language | English |
publishDate | 2024-06-01 |
publisher | Simon Dawes, Centre d’histoire culturelle des sociétés contemporaines (CHCSC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ) |
record_format | Article |
series | Media Theory |
spelling | doaj-art-024dc5eb9b8b4ac6be09cd7d8aa484aa2025-07-18T21:00:09ZengSimon Dawes, Centre d’histoire culturelle des sociétés contemporaines (CHCSC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)Media Theory2557-826X2024-06-018110.70064/mt.v8i1.1075Diffused SeeingJoanna Zylinska This article examines the transformation of the relationship between seeing and understanding in humans and machines by the technologies of machine learning known as ‘generative AI’. Taking Stable Diffusion as the main case study, while also looking at its competitors (DALL·E 2 and Midjourney), it starts by analysing the photographic infrastructure underpinning these generative models. The subsequent examination of ‘diffusion’ as a key concept that underpins the text-to-image generation process leads to some broader questions about the ongoing instability and dissolution of our current epistemological and political frameworks. Taking seriously the charge issued by some critics equating developments in generative AI with nihilism or even fascism, the article considers whether the current socio-technical moment can also offer some emancipatory possibilities. Images are used as part of the article not just by way of illustration but also to enact some of its argument. https://journalcontent.mediatheoryjournal.org/index.php/mt/article/view/1075entropyFlussergenerative AIhumannonhumanperception |
spellingShingle | Joanna Zylinska Diffused Seeing Media Theory entropy Flusser generative AI human nonhuman perception |
title | Diffused Seeing |
title_full | Diffused Seeing |
title_fullStr | Diffused Seeing |
title_full_unstemmed | Diffused Seeing |
title_short | Diffused Seeing |
title_sort | diffused seeing |
topic | entropy Flusser generative AI human nonhuman perception |
url | https://journalcontent.mediatheoryjournal.org/index.php/mt/article/view/1075 |
work_keys_str_mv | AT joannazylinska diffusedseeing |