Creative Assistants with Style: Making Sense of Generative AI as “Style Engines”

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dc.contributor.author Peter, Sandra
dc.contributor.author Riemer, Kai
dc.date.accessioned 2023-12-26T18:42:38Z
dc.date.available 2023-12-26T18:42:38Z
dc.date.issued 2024-01-03
dc.identifier.isbn 978-0-9981331-7-1
dc.identifier.other 7a22cedd-46e9-4372-87dd-9ea52b1a9501
dc.identifier.uri https://hdl.handle.net/10125/106866
dc.language.iso eng
dc.relation.ispartof Proceedings of the 57th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Artificial Intelligence-based Assistants and Platforms
dc.subject ai
dc.subject alien intelligence
dc.subject creative assistants
dc.subject generative ai
dc.subject styles
dc.title Creative Assistants with Style: Making Sense of Generative AI as “Style Engines”
dc.type Conference Paper
dc.type.dcmi Text
dcterms.abstract Generative AI technologies have been heralded for their ability to become powerful assistants, creating plausible text and realistic images. Yet they have also frequently been criticized for their lack of precision, accuracy or veracity. We argue that focusing on such traits misses what is most novel and defining about generative AI. As probabilistic technologies, generative AIs do not store, in any traditional sense, any data or content. Rather, essential features of training data become encoded in deep neural networks as patterns, or what we refer to, as styles. We discuss what happens when the distinction between objects, their properties, and appearance dissolves and all aspects of images and text become understood as styles, accessible for exploration and creative combination. We suggest that the ability to explore the world with styles is a defining feature of generative AI, with significant implications for how we assess its usefulness as creative assistants.
dcterms.extent 10 pages
prism.startingpage 3980
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