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Preprint . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
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The Moral Problem of Infinite Film Generation: Ontological, Ethical, and Aesthetic Implications of Large Language Models in Cinematic Reproduction

Authors: Usai, Luigi;

The Moral Problem of Infinite Film Generation: Ontological, Ethical, and Aesthetic Implications of Large Language Models in Cinematic Reproduction

Abstract

The Moral Problem of Infinite Film Generation: Ontological, Ethical, and Aesthetic Implications of Large Language Models in Cinematic Reproduction AbstractThe advent of generative artificial intelligence, specifically large language and multimodal models, is poised to disrupt the ontology of cinema. This paper investigates the moral, legal, and aesthetic ramifications of infinite film generation: the capacity of AI systems to ingest a canonical work (e.g., The Matrix, 1999), then algorithmically regenerate it by substituting objects, voices, music, and even narrative structures, producing an indefinite proliferation of derivative yet ontologically distinct films. We analyze this phenomenon through the lenses of film studies, philosophy of art, intellectual property law, computational creativity, and moral philosophy. We argue that the infinite reconfiguration of cinematic works challenges traditional boundaries of authorship, originality, and cultural memory, raising urgent ethical questions concerning authenticity, saturation, and the potential trivialization of artistic experience. 1. Introduction Cinema has historically been a medium of scarcity: each film is a discrete cultural artifact, fixed in celluloid, digital master, or streaming format, carrying the aura of a bounded artistic whole (Benjamin, 1936; Deleuze, 1985). The emergence of generative artificial intelligence radically alters this ecology. Through techniques of scene graph manipulation (Johnson et al., 2015), voice synthesis (Zen et al., 2019), generative soundtrack composition (Briot, Hadjeres, & Pachet, 2020), and narrative recombination (Elsner, 2023), an AI can now produce countless "shadow-films": works that resemble an original film yet differ in every visual, auditory, and semantic layer. What happens when The Matrix can be algorithmically transmuted into 3,000 horror variants, 3,000 romantic comedies, and 3,000 speculative political thrillers, all sharing a spectral relation to the Wachowskis’ original? This paper addresses the moral problem of such infinite film generation. 2. Ontology of Infinite Variants 2.1 From Adaptation to Ontological Divergence Traditional cinematic adaptations (remakes, parodies, reboots) are bounded by human authorship. AI-driven recomposition erases this boundary: a single "ur-text" becomes the seed of infinite divergence. The ontological status of these films is ambiguous: are they derivatives, originals, or simulacra (Baudrillard, 1981)? 2.2 Scene Graph Surrogation Modern multimodal LLMs can re-describe a film at the level of a scene graph (nodes: objects; edges: relations). Substituting every object with an analogous surrogate (a cup with a chalice, a pistol with a laser emitter) generates a new ontological stratum of film. This transforms cinema into a dynamic lattice of possible worlds (Lewis, 1973; Ryan, 1991), where the distinction between “film” and “simulation of film” collapses. 3. Ethical Dimensions 3.1 Authorship and Responsibility Infinite generation challenges the moral weight of authorship. If billions of films are generated automatically, who is the "author"? The machine? The original creators? The user who pressed "generate"? Following Barthes’ Death of the Author (1967), authorship dissolves—but the ethical implications remain: who bears moral responsibility for offensive, harmful, or manipulative content emerging from infinite recombination? 3.2 Value Dilution and Cultural Saturation Art has cultural significance partly because of its scarcity and boundedness (Heidegger, 1950). The capacity to generate trillions of cinematic artifacts risks trivializing artistic experience. The signal-to-noise ratio of culture collapses: masterpieces may be drowned in algorithmic noise. 3.3 The Problem of Meaning Films serve as cultural memory, embedding historical contexts, struggles, and identities (Mulvey, 1975). Infinite AI recomposition risks decontextualization: the moral gravity of Schindler’s List or 12 Years a Slave could be flattened if endlessly reimagined as romantic comedies or action thrillers. This is not merely tasteless—it erodes the mnemonic and ethical function of cinema as witness. 4. Legal and Economic Ramifications 4.1 Intellectual Property Current copyright law cannot absorb the ontological shift posed by infinite recombination. If every pixel, line of dialogue, and musical motif is replaced, does the derivative film escape copyright claims (Lessig, 2004)? Or does the "structural DNA" of the narrative remain protected? 4.2 Collapse of the Film Industry Model Studios invest hundreds of millions into single productions. An AI capable of instantly producing 3,000 genre-shifted variants destabilizes this model. The economics of scarcity—ticket sales, streaming licenses, box office—are undermined. Cinema risks becoming a post-industrial folk art, where works are endlessly reconfigured rather than produced. 5. Aesthetics of Infinity 5.1 The Sublime of Exhaustion Philosophically, infinite film generation confronts us with a technological sublime (Lyotard, 1984). The very possibility of a billion alternative Casablancas evokes awe but also despair. If every possible version already exists, does artistic creation lose its urgency? 5.2 Curation as the New Aesthetics In a world of infinite films, curation replaces creation as the central aesthetic act. The critic, archivist, or algorithmic recommender system becomes the true "author," shaping significance by selection. 6. Case Study: The Matrix as an Infinite Seed Consider The Matrix (1999). Inputting the film into a generative LLM could yield: Sci-fi variants: Neo awakens not into a machine dystopia but an alien bio-dome. Romantic variants: Trinity and Neo’s love arc becomes the primary plotline, with the Matrix as metaphorical backdrop. Horror variants: Agents become vampiric entities; the Matrix a haunted necropolis. Each is ontologically distinct yet spectrally tied to the original. Thus, The Matrix becomes a narrative genome capable of endless recombination—a cinema without closure. 7. Toward a Moral Framework We propose three axes for ethical evaluation of infinite film generation: Ontological Integrity – Does the generated work respect the historical and cultural gravity of the original? Cultural Sustainability – Does infinite generation enrich or dilute the shared symbolic ecology? Responsibility of Mediation – Who curates, contextualizes, or restricts recombinations to prevent harm or trivialization? Without such a framework, the generative cinema revolution risks devolving into moral nihilism, where films lose their cultural weight as bearers of memory and meaning. 8. Conclusion The infinite generation of films by AI is not merely a technological novelty—it is a seismic shift in the ontology, ethics, and economics of cinema. It threatens to blur the line between original and derivative, artist and machine, memory and simulation. Yet, within this crisis lies potential: a redefinition of cinema as a living, proliferative organism, where human moral agency lies not in creation but in responsible curation of infinity. References Baudrillard, J. (1981). Simulacres et Simulation. Barthes, R. (1967). La mort de l’auteur. Benjamin, W. (1936). Das Kunstwerk im Zeitalter seiner technischen Reproduzierbarkeit. Briot, J.-P., Hadjeres, G., & Pachet, F. (2020). Deep Learning Techniques for Music Generation. Deleuze, G. (1985). Cinéma 2: L’image-temps. Heidegger, M. (1950). Der Ursprung des Kunstwerkes. Johnson, J. et al. (2015). Image Retrieval Using Scene Graphs. Lessig, L. (2004). Free Culture. Lewis, D. (1973). Counterfactuals. Lyotard, J.-F. (1984). Le Postmoderne expliqué aux enfants. Mulvey, L. (1975). Visual Pleasure and Narrative Cinema. Ryan, M.-L. (1991). Possible Worlds, Artificial Intelligence, and Narrative Theory. Zen, H. et al. (2019). Deep Generative Models for Speech Synthesis.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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