The Allure of Artificial Worlds

Fig. 1: ‘Vapourwave Hall’, generated by the author using Leonardo.Ai, 2024. Introduction With generative AI (genAI) and its outputs, visual and aural cultures are grappling with new practices in storytelling, artistic expression, and meme-farming. Some artists and commentators sit firmly on the critical side of the discourse, citing valid concerns around utility, longevity, and ethics. But more spurious judgements abound, particularly when it comes to quality and artistic value. This article presents and explores AI-generated audiovisual media and AI-driven simulative systems as worlds: virtual technocultural composites, assemblages of material and meaning. In doing so, this piece seeks to consider how new genAI expressions and applications challenge traditional notions of narrative, immersion, and reality. What ‘worlds’ do these synthetic media hint at or create? And by what processes of visualisation, mediation, and aisthesis do they operate on the viewer? I suggest here that these AI worlds offer a glimpse of a future aesthetic, where the lines between authentic and artificial are blurred, and the human and the machinic are irrevocably enmeshed across society and culture. Where the uncanny is not the exception, but the rule. Analytic Survey The term ‘composite’ is co-opted here from Lisa Purse, whose writings have become perhaps inadvertent champions of digital augmentation and visual effects in film. The critical and academic response to AI media is not dissimilar from that to the advent of high-concept, visual effects-laden, digitally-encoded cinema. An “overdetermined nexus of loss”, Purse dubs the digital screen, “of material presence, of an indexical relation to the world and lived experience” (Purse 149). James Verdon says that there is an incontrovertible “indexical severance when pro- or a-filmic reality is recorded or manipulated digitally” (Verdon 197), and photography and cinema seemingly continue to struggle with this severance. In terms of AI media, though, there is no harsh ‘severance’ with which to grapple; the dilemma is much more existential, in that the ‘real’ of these objects never existed. Despite their often realistic outputs, AI media still possess an eerie, uncanny quality. Some scholars suggest that the result is a kind of ‘haunted’ media: the main thing haunting these new AI images is actually the camera itself, rendered a ghost now by its total absence from the new medium, a seemingly unnecessary anachronism, but one that nevertheless exerts a strong spectral influence on everything that is generated. (Schofield 17) Andreas Ervik also observes this spectral influence in how generation models structure their outputs with a clear predisposition towards older forms of media. Ervik calls these images without ‘real’ referents “views of nowhere”, offering the example of “an ahistorical emulation of the general vibe of classical portrait painting” (Ervik 83-4). This uncanniness persists in abstract or glitched AI outputs as well as in those that are more realistically rendered. There is always some trace of something recognisable or tangible, be that a human feature, a graphical element, or an assortment of colours. AI media, tools, and applications are lingering, surviving, and in the process are changing visual culture, particularly in terms of aesthetics. Shane Denson notes that AI tools and generators are “dissolving the industrial-era wedge between art and tech” (Denson 147), leading to a profound shift in aisthesis: these ... technologies are transforming the domain of sensation itself, opening up new objects of perceptual and cognitive experience, and changing the scope and parameters of embodied relation to the environment. (Denson 147) Denson’s general argument is that, love them or loathe them, the power of AI media lies in their visceral impact, rather than the technical accomplishment of their generation or any immanent artistic value or quality. The outputs of these AI models are received and filtered through the body and mind; they are thus triggers for ‘felt’ experience, where the viewer is immersed, if only momentarily, in a hallucinated reality. What kinds of felt experiences can AI media conjure, and through what mechanisms do these conjurings occur? How might these experiences change our understanding of reality and representation when we return to everyday life? Eryk Salvaggio writes that “when we look at AI images ... we are looking at infographics about these datasets, including their categories, biases, and stereotypes” (Salvaggio, "How to Read" 87). Salvaggio’s process-driven analysis is based on his experience with Stable Diffusion, where concepts or forms that are highly represented in the model’s training data emerge more clearly in outputs than less-represented concepts. This notion remains true for most media generators, particularly in the realm of image and video. In Salvaggio’s creative work, too, he finds that more provocative results come in pushing at the less-represented, at the gaps between the model’s defined ‘vision’ or ‘understanding’ of the world: AI models, when used as intended, don’t move us away from the bias of human vision, it constrains us to that bias. This bias is infused into training data, a bias that merges images into the categories of their descriptions, reconstructing links between words and what they represent. (Salvaggio, "Moth") Despite the constraints of a bias towards the human, many models have hallucination purposely built in. In these cases, hallucination is a feature rather than a bug. It is hallucination—the introduction of some chaos and randomness into the maths underpinning the mechanisms of generation—that may give that uncanny feeling of human connection when conversing with ChatGPT, but that also causes glitches and unexpected mutations in outputs from media generators. But these glitches, too, are what artists and creatives often gravitate towards in working with generative AI. As Nataliia Laba notes, in engaging with the machinic, one positions oneself as an agent with multiplicities: as a promptor, I assume the role of a social actor engaging in the co-creation of visual outputs alongside Midjourney’s bot on Discord. As a researcher, I operate on the premise that AI-generated images are not straightforward extrapolations from existing generative AI technology, but are to be understood as the contingent outcome of a series of social, political, and organizational factors. (Laba 10) Echoing earlier work around algorithmic agency, AI generators and their human users sit at the nexus of technology, mythology, and representation (boyd and Crawford 663). The results of this enmeshment are AI-generated media. The moment of generation, thus, “fixes a unity from scattered data elements, at that same moment fabulating new connections and traits, forging attributes that will attach to other beings in the future” (Amoore 102-3). AI media are not just fixed unities or instances, the results of algorithmic and mathematical operations, but also complex, networked assemblages enacting particular effects. They are, essentially, worlds unto themselves. This is why AI media are so rapidly provoking and affecting visual culture and the media landscape more broadly. Thus, more nuanced analysis is required of their origin and creation, their forms and qualities, and their potential or actual effects. This article looks directly at AI media, and how they are being reconstituted into media artefacts—specifically short films—for consumption, enjoyment, and provocation. Beyond this, I engage with ‘simulative AI’, or rather, AI-driven simulations, and where and how these might attract and engage users. With both films and simulative experiences, I observe how these media have innate agency and power to influence us viscerally and psychologically. They seduce us with their aesthetic and material qualities: that these qualities are synthetic is also, paradoxically, a part of their charm. Two Video Works AI systems like RunwayML and Pika generate moving images by adding a “video-aware temporal backbone” to the process (Blattman et al., 3). These systems are becoming increasingly adept at producing videos of some length, though their outputs remain susceptible to hallucinations and glitching. For many creators, this is precisely where the ‘point’ of AI media lies. Fig. 2: Screen capture from “You Are, Unfortunately, an A.I. Artist” (Mind Wank, 2024). “You Are, Unfortunately, an A.I. Artist” (Mind Wank, 2024) interrogates the legitimacy and artistic value of AI media. Its main character, a small, fluffy, bug-eyed creature in spectacles, toils at their computer, generating endless outputs to edit into small clips to sell via the blockchain. The editing is judicious, avoiding the worst of the morphing or glitching, though some remains, lending an unnatural taint to the creature’s movements and its environment. We observe the pitiful protagonist as though through rippling water or oil, a shifting and dynamic carnival mirror visual filter. The robotic narration does little to allay this feeling of unease, addressing the viewer directly per the work’s title: “You are trying to create something new, something meaningful.” The critical moment of the piece is when the Wi-Fi connection cuts out: “Without Internet, are you really an AI artist? Or are you just some guy? Obviously you have no technical skills, or you would’ve done something else.” The central creature retains its general form, as a fluffy figure, though as it ‘grows’ through the film, it changes somewhat, with different body structures, and occasionally featuring human-like hands. This is likely a result of the AI model filling in some visual information with its best guess. The effect of this, though, works for the narrative; the creature is unstable as a character, but also as perceived by the viewer. Visuals, narration, music—all entirely AI-generated—here combine in