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Beyond magic

Prompting for style as affordance actualization in visual generative media

Bibliographic Data

ID7477112
AuthorsNataliia Laba (0000-0003-0724-1467, University of Groningen, corresponding author)
Year2024
Volume28
Issue1
Pages148-168
Publication date2024-10-29
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueNew Media & Society (JOURNAL)
Journal identifiersISSN: 1461-4448 • E-ISSN: 1461-7315
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/14614448241286144
OpenAlexW4403871971
LanguageEN
Citations received6
References cited30

As a sociotechnical practice at the nexus of humans, machines, and visual culture, text-to-image generation relies on verbal prompts as the primary technique to guide generative models. To align desired aesthetic outcomes with computer vision, human prompters engage in extensive experimentation, leveraging the model’s affordances through prompting for style . Focusing on the interplay between machine originality and repetition, this study addresses the dynamics of human-model interaction on Midjourney, a popular generative model (version 6) hosted on Discord. It examines style modifiers that users of visual generative media add to their prompts and addresses the aesthetic quality of AI images as a multilayered construct resulting from affordance actualization . I argue that while visual generative media holds promise for expanding the boundaries of creative expression, prompting for style is implicated in the practice of generating a visual aesthetic that mimics paradigms of existing cultural phenomena, which are never fully reduced to the optimized target output

Aesthetics · Affordance · Art · Cognitive psychology · Cognitive science · Generative grammar · MAGIC (telescope · Multimedia · Physics · Style (visual arts · Visual arts · Visual media · Communication · Computer Science · Creativity in Education and Neuroscience · Design Education and Practice · Digital Games and Media · Psychology · Artificial Intelligence

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  • Prompt Culture

    Open Access•Norma Musih•Theory Culture & Society•2026

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    John C Hayvon•Community Development•2026

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    Open Access•Emilia Edwards, Dhiraj Murthy•New Media & Society•2026

  • Computer-mediated representations

    Open Access•Tony Thomson•Visual Communication•2025

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    Tarleton Gillespie•Media Technologies•2014

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    Open Access•Eva Cetinić, James She•ACM Transactions on Multimedia…•2022

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    Open Access•Jennifer O’meara, Cáit Murphy•Convergence The International…•2023

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    Open Access•P Atkinson, Richie Barker•Convergence The International…•2023

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    Open Access•Shane Denson•Journal of Visual Culture•2023

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    Open Access•Alexander Campolo, K Crawford•Engaging Science Technology and…•2020

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    Open Access•Mike Ananny, K Crawford•New Media & Society•2016

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    Open Access•Nataliia Laba•Media Culture & Society•2024

  • Sociotechnical challenges to the technological accuracy of computer vision

    Open Access•Eun-Sook Kim, Yoehan Oh et al.•Technology in Society•2023

  • Mind ascribed to AI and the appreciation of AI-generated art

    Open Access•Tanja Messingschlager, M Appel•New Media & Society•2023

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    Open Access•Sarah Burkhardt, Bernhard Rieder•Big Data & Society•2024

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    Open Access•Benjamin N Jacobsen•Big Data & Society•2023

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    Open Access•Peter Nagy, Gina Neff•Social Media + Society•2015

  • Doubt and the Algorithm

    Open Access•Louise Amoore•Theory Culture & Society•2019

  • Thinking Colours and/or Machines

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Unique citing works6
Citations per year6
Citation span2025 - 2026 (2)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 5

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