Lars Konzack’s paper “Generative AI, Simulacra, and the Transformation of Media Production” is a qualitative study of content from advertising, film, and television which was made with the heavy or exclusive use of generative AI tools. It analyzes the selected pieces of content through the framework of Baudrillard’s theory of hyperreality, and specifically as examples of simulacra – representations detached from their original referent which instead refer only to themselves. The Coca-Cola ad he analyzes is probably the most clear example of this. In November of 2024, Coca-Cola used AI to recreate their famous 1995 holiday ad. Konzack notes that the ad received a fair amount of backlash, and posits that a large amount of it stemmed from the commercial’s imagery being drawn not from any connection to real human experience but rather as a reference to the older, more fondly remembered ad (2025). The main goal of the article is to examine how the data-driven pattern recognition that characterizes AI could reshape the production process by enabling a mode of creation that is built on a foundation of repetition instead of innovation. This is reflected not just in generative AI tools creating content by reshaping old images pulled from their training data, but also by the algorithmic recommendation and personalization systems enabled by this tech reinforcing consumer behaviors to the point where they accept “synthetic content” at face value, a scenario where “consumers interact with and respond emotionally to content that lacks a direct human origin” (Konzack, 2026).
This paper provides a succinct and compelling argument for how generative AI tools in many ways epitomize Baudrillard’s theory of hyperreality. The cautionary argument Konzack lays out in the paper’s conclusion of the prospect of AI driven production leading to a creative environment that is “anticipatory rather than exploratory” is a tidy description of the setting I’m constructing for my project, where the content people enjoy on a regular basis is shaped more “by algorithmic logic than by human intent” (Konzack, 2026). This paper will probably be a key component of my explanation to the audience in the piece itself of the media environment that exists in 2057, and may even be integrated into the Department’s goals as the state of being that they’re attempting to manage and preserve. If anything, I’m surprised there aren’t more analyses out there in this vein, as generative AI’s ability to create content at an inhuman rate seems to neatly fit the description of endless image reproduction which is another key part of Baudrillard’s theory. Then again, AI is constantly improving and changing as the companies building it update and re-tool their models. The analysis and critique which human academics produce might simply be struggling to keep up with this inhuman rate of change.
This week I managed to make headway through a few of my training modules. I watched Cassie Phillipps’ talk from the 2016 Game Developer’s Conference on how to make efficiently branching narratives that offer choices to players which feel meaningful without having to construct sprawling, vastly different stories. I also saw Alex McDowell’s Linkedin Learning talk on worldbuilding and narrative, which was fascinating for offering a perspective on how worldbuilding and constructing a setting can be used in narrative and non-narrative works, as he described it as developing both context for a world and a system of interlocking, interrelated parts. While I selected this module with an eye first towards how I could apply it practically for my own worldbuilding efforts in the project, the talk also made me think about how worldbuilding could be applied as an in-universe concept, applying it specifically to the idea of the arcologies that people in my future setting live in and how a closed environment like that could be engineered. Finally, I watched the overview of how to create interactive videos with Adobe Captivate. It was a good intro to the program and to a few of the different interactivity options it offers, but I think I’ll need to start using the program to learn how to best apply it for my project. Captivate and interactive video in general is mostly discussed as a way to use content for training and e-learning. This weirdly fits with my project and prompted me to lean in during the script writing process to framing the video as a training module in form and function, with the understanding that the thing the user is interacting with is in fact an artifact from this imagined future. It also gave me the impression that Captivate will work at least for now and the proof-of-concept stage as a way of effectively and intuitively adding interactivity to my piece, and even a bit of looking around into other tools in the space leads me to believe that there’s a good chance that I’ll use the program for my final product.
Works Referenced:
GDC Festival of Gaming. (2019, Dec. 12). All choice no consequence: Efficiently branching narrative [Video]. YouTube. https://www.youtube.com/watch?v=TEa9aSDHawA
Konzack, L. (2025). Generative AI, simulacra, and the transformation of media production. Athens Journal of Mass Media and Communications, 11(3), 177–196. https://doi.org/10.30958/ajmmc.11-3-3
McDowell, A. (2015, October 9). Worldbuilding and narrative [LinkedIn Learning Video]. LinkedIn. https://www.linkedin.com/learning/alex-mcdowell-world-building-and-narrative/introduction
Your Learning Career. (2023, March 23). How to create interactive video with Adobe Captivate [Video]. YouTube. https://www.youtube.com/watch?v=b8eqmy3rfbs
