Generative media: Sign, metaphor, and experience
DOI:
https://doi.org/10.33919/dasc.24.7.4Keywords:
generative media, generative AI, user interface, material semiotics, digital semioticsAbstract
This article explores the vivid field of generative media, focusing on the production and semiotic analysis of texts. It uses the broad definition of “text,” which encompasses written, visual, and interactive forms, and examines how generative media redefines the roles of content creators and tools. Utilizing Roman Jakobson’s communication model, the article highlights the dynamic decision-making process in text production, whether by human or AI. The paper offers a historical review which traces generative media from early computer art in the 1960s, through the advent of digital design tools in the 1980s and 1990s, to contemporary AI techniques like GANs and diffusion models. It identifies the key properties of generative media: synthetic, dynamic, digital, combinatorial, and agentic. The discussion also addresses the shift from unnoticed AI assistance in early tools to the inadvertently AI-generated content in today’s media landscape. The last part of the paper categorizes generative media interfaces into three types: conversational, web UI, and visual programming interfaces, analyzing their semiotic implications. It suggests that understanding these tools requires recognizing their layered technical components and the evolving user experience from magic-like simplicity to complex customization. In conclusion, the articles advocates for a multidisciplinary, process-oriented approach to fully grasp the cultural and communicative transformations driven by generative media, emphasizing the importance of transparency and user agency in AI interactions.
References
Boden, M., E. Edmonds. 2009. “What Is Generative Art?”. Digital Creativity, Vol. 20, No. 1–2, 21–46. Available at: https://doi:10.1080/14626260902867915.
Bøgh Andersen, P. 1997. A Theory of Computer Semiotics. Cambridge University Press.
Bommasani, Rishi, et al. 2021. “On the Opportunities and Risks of Foundation Models.” Report. Center for Research on Foundation Models (CRFM), Stanford Institute for Human-Centered Artificial Intelligence. arXiv preprint arXiv:2108.07258. Available at: https://doi.org/10.48550/ arXiv.2108.07258.
Burbano, A., E. G. Bravo. 2016. “Konrad Zuse: Enabler of Computational Arts?.” In Archiving and Questioning Immateriality, Proceedings of the 5th Computer Art Congress. Paris: Europia, 190–203.
Franco, F. 2022. The Algorithmic Dimension: Five Artists in Conversation. Cham: Springer.
Galanter, P. 2016. Generative Art Theory. In Paul, C. (ed.). A Companion to Digital Art. Hoboken: Wiley. 146–180.
Hall, E. 2018. Conversational Design. A Book Apart.
Huang, J. 2023. NVIDIA Keynote at SIGGRAPH 2023. [Video] Available at: https://www.youtube.com/watch?v=Z2VBKerS63A.
Jiang, P. 2023. “Positional Control in Node-Based Programming.” In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, 1–7.
Kneusel, R. 2023. How AI Works: From Sorcery to Science. London: No Starch Press.
Manovich, L. 2013. Software Takes Command. New York-London: Bloomsbury.
Myers, B. 1990. “Taxonomies of Visual Programming and Program Visualization.” Journal of Visual Languages & Computing, Vol. 1, No. 1, 97–123.
Peirce Edition Project. 1998. The Essential Peirce: Selected Philosophical Writings Volume 2 (1893–1913). Indiana University Press.
Perlin, K. 1985. An Image Synthesizer. In Proceedings of the 12th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH ‘85). New York: ACM, 287–296. Available at: https://doi. org/10.1145/325334. 325247.
Reyes, E. 2017. The Image-interface: Graphical Supports for Visual Information. Hoboken: Wiley.
Reyes, E., S. Labelle. 2018. Seeing Through the Web: Tools, Practices, Transformations. In Proceedings of the 2nd International Conference on Web Studies, 1–4.
Reyes, E. 2021. Face Value: Analyzing and Visualizing Facial Data. In Lexia. Rivista di semiotica, 37–38, 467–483.
Shanken, E. 2009. Art and Electronic Media. London: Phaidon Press.
Short, T. 2007. Peirce’s Theory of Signs. Cambridge University Press.
Valyaeva, A. 2023. “AI Has Already Created As Many Images As Photographers Have Taken in 150 Years. Statistics for 2023”. Everypixel Journal. Available at: https://journal.everypixel.com/ai-image-statistics (accessed 31 May 2024).
Van den Boomen, M. 2014. Transcoding the Digital: How Metaphors Matter in New Media. Amsterdam: Institute of Network Cultures.
Zylinska, J. 2023. The Perception Machine. Cambridge: MIT Press.
