| id |
acadia23_v3_49 |
| authors |
A. Noel, Vernelle; Dortdivanlioglu, Hayri |
| year |
2023 |
| title |
Text-to-image generators: Semiotics, Semantics, Syntax, and Society |
| source |
ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 3: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-1-0]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 24-32. |
| summary |
Text-to-image generators, such as Midjourney, DALL-E, and Stable Diffusion, are becoming increasingly popular. These generators, whose models are trained on large datasets of text-image pairs, often scraped from the web, take text prompts as input, and use them to generate images—text-to-image prompting. In this visual essay, we raise questions about the entanglement of semiotics, semantics, syntax, and society in these text-to-image generator tools. We are intrigued by how these technologies are “intrawoven” with social and cultural contexts. How are their constructions and presentations reconfigurations? How do, or might they, inform pedagogy, theory, methods, and our publics? To explore these questions, we entered six prompts related to the built environment in six different languages, eight months apart in Midjourney (“Midjourney” n.d.). The generated images (Figure 1), require that we ask deep questions of each image, in comparison with each other, across each group of four, and across time (eight months apart). We argue that text-to-image generators call for a rigorous exploration of semiotics, semantics, syntax, and the society, with implications for pedagogy, theory-building, methodologies, and public enlightenment. Furthermore, we assert that these tools can facilitate pertinent questions about the relationships between technology and society. This is just the beginning. For now, we have questions. |
| series |
ACADIA |
| type |
field note |
| email |
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| full text |
 file.pdf (4,002,548 bytes) |
| references |
Content-type: text/plain
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| last changed |
2024/04/17 13:59 |
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