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Abstract
This chapter seeks to identify a criticality for creative praxis that uses artificial intelligence within the production of a series of artworks. The article refers to the work of Karen Barad to provide a theoretical framework within which to understand how machine learning and deep learning support intra-actions between humans (artist, data scientist, audience), data sets, and algorithms in the production of artwork. By recovering the work of McQuillan who calls for Agential Realism to inspire a countercultural praxis for data science, and Joler and Pasquinelli who present the limitations of datasets as a resource for creative praxis, the authors identify the logical and political limitations of AI to predict or generate something statistically unlike the already existing or the already known. A case study is introduced to exemplify the implications upon creative praxis that involves working with data-driven technologies.
Original language | English |
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Title of host publication | Distributed Perception |
Subtitle of host publication | Resonances and Axiologies |
Editors | Natasha Lushetich, Iain Campbell |
Place of Publication | London |
Publisher | Routledge |
Chapter | 11 |
Number of pages | 15 |
Edition | 1 |
ISBN (Electronic) | 9781003157021 |
ISBN (Print) | 9780367743017 |
DOIs | |
Publication status | Published - 30 Dec 2021 |
Publication series
Name | Routledge Studies in Science, Technology and Society |
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Dive into the research topics of 'Intra-actions in data-driven systems: A case study in creative praxis'. Together they form a unique fingerprint.Projects
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Creative Informatics: Data Driven Innovation for the Creative Industries
Speed, C., Jones, C., Rovatsos, M., Schafer, B., Smyth, M., Terras, M., Elsden, C., Helgason, I., Lechelt, S., Morgan, E., Osborne, N., Paneels, I. & Thornton, P.
29/10/18 → 28/04/23
Project: Research