AI-Generated Images and Influences on Scenographic Design

Authors

  • Iulia Gherghescu Tulane University, USA CINETic – International Center for Research and Education in Innovative and Creative Technologies; UNATC, Bucharest, Romania Author

DOI:

https://doi.org/10.37130/kjg4pr54

Keywords:

co-creation, prompt poetics, augmented human creativity, Generative Artificial Intelligence, human agency, creativity, scenography, style transfer

Abstract

The advent of generative AI represents a significant transformation in image creation. It is essential to explore the implications of incorporating this technology into scenography and to begin dialogues about the fundamental challenges and opportunities arising from this developing relationship. Recent AI tools have demonstrated the ability to produce outputs traditionally considered creative. Systems such as text-to-image generative AI (e.g., Midjourney, Stable Diffusion, DALL-E) automate human artistic execution to generate digital artworks. This paper explores rapid visualisations of set design concepts, aiming to provoke critical introspection regarding the interplay between artificial and human creativity in shaping images for performance design, the impact on the creative process and workflow of designers. Does generative AI introduce a novel aesthetic dimension to scenography? Can it truly amalgamate diverse historical and contemporary styles to create visuals that are both 
evocative and unprecedented?

Author Biography

  • Iulia Gherghescu, Tulane University, USA CINETic – International Center for Research and Education in Innovative and Creative Technologies; UNATC, Bucharest, Romania

    Iulia Gherghescu is a scenographer, lecturer and researcher in scenography at the I.L. Caragiale National University of Theatre and Film, Bucharest, Romania. She holds a MFA degree in Design and Technical Production from Tulane University, as well as a Doctorate in Scenography with a thesis focusing on emerging creative influences and developments in contemporary stage and costume design. Her professional trajectory encompasses a diverse range of experiences, primarily within the realms of film and theatre. However, she remains receptive to opportunities across various fields and is fervently committed to collaborating with talented, multidisciplinary teams. She is particularly interested in exploring the transformative potential of new media and artificial intelligence in reshaping the landscape of scenography, and how these factors can influence evolving trends and aesthetics.

References

Anantrasirichai, N., & Bull, D. (2020) ”Artificial intelligence in the creative industries: a review”, Artificial Intelligence Review, 55, pp. 589-656.

Boden, M.A. (2004) The Creative Mind: Myths and Mechanisms, Routledge.

Cheng, M. (2022) ”The Creativity of Artificial Intelligence in Art”, Proceedings.; 81(1), p. 110. https://doi.org/10.3390/proceedings2022081110.

Earnshaw, R. and Liggett, S. (2023) ”Artificial Intelligence and Creativity”. In Earnshaw, R., Liggett, S., and Townsley, J. (eds) Creativity in Art, Design and Technology. Springer Briefs on Cultural Computing, pp. 65-71.

Lee, H.-K. (2022) ”Rethinking creativity: creative industries, AI and everyday creativity”, Media, Culture & Society, 44(3), pp. 601-612.

Manovich, L. (2017) Cultural Analytics. Cambridge, MA: The MIT Press.

Manovich, L. (2018) AI Aesthetics. Strelka Press.

O’Toole, K. and Horvat, E.-A. (2024) ”Extending human creativity with AI”. Journal of Creativity. doi: https://doi.org/10.1016/j.yjoc.2024.100080.

Rajcic, N., Llano, M. T., and McCormack, J. (2024) ”Towards A Diffractive Analysis of Prompt-Based Generative AI”, in Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (CHI ’24), May 11–16, 2024, Hawaii, USA. ACM, New York, NY, USA.

Sawyer, R. K. (2014) Explaining Creativity: The Science of Human Innovation. New York, NY: Oxford University Press.

Vinchon, F., et al. (2023) ”Artificial Intelligence & Creativity: A Manifesto for Collaboration”, The Journal of Creative Behavior, 57(4), pp. 472–484. https://doi.org/10.1002/jocb.597.

Walewska, J. (2023) ”Relationship of art and technology: Edward Ihnatowicz’s philosophical investigation on the problem of perception”. In S. Cubitt & P. Thomas (Eds.), Relive media art histories, The MIT Press, pp. 172–177.

Campitiello, J. (2023) ”vs. Artist: The Future of Creativity”. Cornell Tech News. Available at: https://tech.cornell.edu/news/ai-vs-artist-the-future-of-creativity/ (Accessed: 17 June 2024).

Fitzpatrick, R. (2018) ”Human creativity v machine creativity: When artificial intelligence gets creative”. Campaign Live, 5 March. Available at: https://www.campaignlive.co.uk/article/human-creativity-v-machine-creativity-when-artificial-intelligence-gets-creative/1485063 (Accessed: 17 June 2024).

Fridman, L. (2024) ”François Chollet: Keras, Deep Learning, and the Progress of AI”. Lex Fridman. Available at: https://lexfridman.com/francois-chollet/ (Accessed: 17 april 2024).

Pogrebin, R. (2012) ”Architecture and the Lost Art of Drawing”. The New York Times, 2 September. Available at: https://www.nytimes.com/2012/09/02/opinion/sunday/architecture-and-the-lost-art-of-drawing.html (Accessed: 17 march 2024).

Zhou, E. and Lee, D. (2024) ”Generative artificial intelligence, human creativity, and art”. PNAS Nexus, 3(3), pp. 1–8. Available at: https://academic.oup.com/pnasnexus/article/3/3/pgae052/7618478 (Accessed: 06 March 2024).

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Published

2024-12-18

Issue

Vol. 29 No. 2 (2024): Issues of Reception in Greek Theatre / AI and Interactive Technologies in Art Practices, Research, and Education / Film and Theatre Pedagogy

Section

Articles

How to Cite

Gherghescu, I. (2024). AI-Generated Images and Influences on Scenographic Design. CONCEPT, 29(2), 85-111. https://doi.org/10.37130/kjg4pr54