The specter of artificial intelligence haunts contemporary culture, infiltrating every corner of creative expression with promises of efficiency and optimization. From literature to visual arts, entire industries grapple with AI’s remaking of traditional practices. In cinema, this transformation has already begun to manifest in unsettling ways: the Academy-winning film ‘The Brutalist’ utilizing AI to refine actors’ vocal performances, the controversial re-release of ‘Raanjhanaa’ with an AI-altered ending that subverts the original tragic climax, and the emergence of entire AI film festivals showcasing works generated predominantly through algorithmic processes. These incidents are not isolated anomalies but harbingers of a broader cultural shift that threatens to fundamentally alter the nature of filmmaking itself.

This piece seeks to understand why film, and particularly the practice of filmmaking, must be defended from AI’s increasing encroachment. The argument here moves beyond economic or professional to become ontological, i.e., the methods internal to the production and feeling of film fundamentally reject what AI represents. To understand this rejection, we must see how cinema operates as a form of embodied knowledge production, a practice that depends entirely on the irreplaceable presence of human consciousness engaged in the slow, uncertain work of storytelling.

The Threat of Cinematic Alienation

If a film fossilizes records of interpersonal interaction, then the work of filmmaking is inherently embodied. The relationship between the author and their work, its language, texture, and rhythm, becomes profoundly intimate, even mystical in its particularity. In their attempt to document reality, the filmmaker immerses themselves in the world, breathing it in fully, to channel that encounter into a visual grammar, thus marking the technique as stubbornly human.

The datasets that these systems feed on are built from millions of prior acts of artistic devotion, stolen without credit, commercialized without compensation, stripped of their original context and intention.

Yet, this intimate bond between creator and their creation now faces its gravest threat. AI represents the ultimate form of cinematic alienation since it doesn’t just alienate labor; it annihilates the laborer entirely. The datasets that these systems feed on are built from millions of prior acts of artistic devotion, stolen without credit, commercialized without compensation, stripped of their original context and intention. What emerges is content obscured of all memory, bearing no trace of the provenance behind the image it mimics. Therefore, the process becomes antiseptic, and the most personal of artistic acts becomes utterly impersonal.

A Marxist Critique of AI Obfuscation

This alienation from creation finds its clearest articulation in Marxist film theory, which offers a helpful lens for understanding what is at stake in AI’s capture of the medium. As film theorist Mike Wayne notes, “Marxism and Film share at least one thing in common: they are both interested in the masses.” For Walter Benjamin, the camera’s mechanical reproduction could strip away the “aura” of traditional art, potentially democratizing cultural production and making visible the power structures that shape our world. Bertolt Brecht’s theatrical innovations sought similar ends through defamiliarization- breaking the illusion to force audiences into critical awareness of their social conditions.

Rather than revealing the social relations embedded in cultural production, who owns the means of creation, whose labor builds the datasets, which perspectives get amplified or erased, AI generation actively conceals these power dynamics behind a veneer of neutral technological progress.

However, can technologies that thrive on invisibility and operate as black boxes engender such revelation? Here lies the fundamental contradiction: where Benjamin and Brecht championed transparency as a tool for liberation, AI systems deliberately obscure their operations and present their workings as efficient and closed to interpretation, even as we know their mechanisms are ultimately knowable. The algorithms that generate content remain proprietary secrets, their training data sources hidden, their decision-making pathways opaque to users. When this obscurity functions as a creator, it produces deeper obfuscation. Rather than revealing the social relations embedded in cultural production, who owns the means of creation, whose labor builds the datasets, which perspectives get amplified or erased, AI generation actively conceals these power dynamics behind a veneer of neutral technological progress. Following a materialist approach, we must examine AI-generated content not for its illusory unity but for its “material disparity”—the contradictions, tensions, and crises that reveal its historically determined limitations. Where Benjamin saw mechanical reproduction as potentially revolutionary, AI’s reproduction serves primarily to concentrate cultural power in the hands of tech corporations while mystifying the very labor and social relations that make such production possible. The materialist analysis rejects the notion of AI-generated works as complete, self-sufficient artifacts, instead exposing them as fundamentally incomplete simulations that conceal rather than reveal the social relations of their production.

Why AI Cannot Be a Creative Partner

Cinema, as Vivian Sobchack reminds us, is never an object of passive consumption but a sensing, sensual, sense-making subject that engages in a complex interplay with its viewer. This relationship emerges from what Sobchack describes as the film experience, depending fundamentally on two “viewers” viewing: the spectator and the movie itself, each existing simultaneously as both subject and object of vision. The camera becomes an extension of human perception, embodying one’s experience and intentionality. This exchange that we live daily as both “mine” and “another’s,” requires the irreplaceable presence of human consciousness behind the camera. When a filmmaker frames a shot, selects a moment, or constructs a narrative, they bring their embodied understanding of what it means to see, to feel, to exist in the world.

AI-generated content, however sophisticated, fails to fulfill this indispensable role of the “other” in this fundamental exchange. It cannot see, cannot sense, cannot make meaning in the experiential sense that filmmaking demands.

AI-generated content, however sophisticated, fails to fulfill this indispensable role of the “other” in this fundamental exchange. It cannot see, cannot sense, cannot make meaning in the experiential sense that filmmaking demands. AI consumes patterns and regurgitates outputs based on data, but lacks the phenomenological foundation that gives cinema its power to engage. Where cinema requires this relationship between maker and viewer, a conversation between two forms of consciousness, AI offers only simulation. As a result, we are left with a peculiar form of filmic solipsism: films that appear to address us while remaining fundamentally indifferent to our presence.

The Unautomatable Ethos of Care

Just as critically, AI dismantles what Erik Knudsen, a professor of media practice, identifies as the irreducible problem of methodology. He explains how the process of creation and reflection is rarely definable, nor necessarily logical. He points out how more often than not, he is overwhelmed by his creations, which take shape largely without his wilful conscious intervention, leading him to reflect, “Did I really create that?” This bewilderment and sense of being astonished by one’s own invention is a feature of the artistic method. The filmmaker’s relationship to their work is characterized by what feminist theorists would recognize as an ethic of care—a patient, attentive tending to the work as it unfolds, a willingness to be changed by the work itself. This care manifests in the countless hours spent nurturing an idea through its awkward adolescence, in the filmmaker’s capacity to preserve space for uncertainty without rushing toward resolution, in their commitment to remaining present with the work, even and especially when it resists their intentions. Such care cannot be automated or accelerated; it exists only in a person willing to be moved, challenged, and ultimately transformed by their own creative labor.

The filmmaker’s relationship to their work is characterized by what feminist theorists would recognize as an ethic of care—a patient, attentive tending to the work as it unfolds, a willingness to be changed by the work itself.

This vital, human struggle stands in direct opposition to the logic of AI. In fact, AI generation promises clarity where filmmaking demands thinking through polemical conflict; it champions speed where the medium requires slowness. This is captured in Robert Graves’ poem, ‘In Broken Images’. The poem presents two contrasting modes of thought that map directly onto our current dilemma: the algorithmic promise of immediacy and clarity versus the filmmaker’s necessary embrace of unhurriedness:

“He is quick, thinking in clear images;

I am slow, thinking in broken images.

He becomes dull, trusting to his clear images;

I become sharp, mistrusting my broken images.

He continues quick and dull in his clear images;

I continue slow and sharp in my broken images.

He in a new confusion of his understanding;

I in a new understanding of my confusion.”

The filmmaker, like Graves’ narrator, must remain “slow and sharp” in their broken images. This iterative wrestling with precariousness and patient cultivation of doubt is what allows patterns of concern, interest, and expression to emerge organically, sharpening both the work and the worker. AI’s promise of instantaneous “clear images” bypasses this essential struggle, delivering the dulled efficiency that Graves warns against and severing the filmmaker from the very confusion that makes them sharp.

Capital Prefers Machines Over Artists

The opposition between the “slow and sharp” and the “quick and dull” is not aesthetic; it is profoundly ideological. The drive to implement AI in movies must be recognized as coinciding with capital’s inherent tendency to prioritize marketable products that can be easily quantified, scaled, and sold. The slow, unprofitable, and meandering technique of the artist is an irrelevant inefficiency to a market that rewards only the measurable outcomes.  In this light, AI represents something deeper than technological progress: a perfect tool to feed capitalism’s disdain for process, offering to compress time-consuming work into instant deliverables.

Most critically, this shift transforms what Jean-Luc Godard recognized as cinema’s essential character—its function as a thinking medium that operates through the full spectrum of cognition, thinking not just with the mind but with eyes, ears, skin, the entire sensing apparatus of our being. When AI generates several script options or visual styles on command, our role subtly degrades from that of a creator grappling with the void to that of a curator browsing a pre-generated menu. The cardinal act of creative confrontation is replaced by the comfortable but ultimately hollow task of choosing among prefabricated results based on user prompts.

Filmmaking as Community Building

Meaningful filmmaking functions as a community-building, as vividly illustrated by the filmmakers of Malegaon. In this small town in Maharashtra, India, a group of friends developed their own practice of storytelling that speaks to their specific context and concerns. Their films emerge from extended ways of collaboration, where neighbors become actors, local spaces transform into sets, and the entire community participates in the act of exploration and articulation. Their cinema functions as what it has always been at its best: a communal practice where the labor of conception becomes inseparable from the work of building and maintaining community. In a nation where communal tensions increasingly fracture social cohesion, their approach offers a model of secular, collaborative cultural production that creates space for different voices and perspectives to coexist. When AI threatens to automate filmmaking, it jeopardizes individual imagination and, more critically, these vital processes through which we understand ourselves and each other. The social fabric that forms around the labor of collective storytelling—the conversations, negotiations, and discoveries that emerge from working together toward a shared vision—cannot be replicated by algorithmic operation.

The push for AI in cinema represents more than methodological convenience- it is the final enclosure of one of our last commons, the space where we gather to make meaning together. When we automate the labor of storytelling, we lose the capacity to surprise ourselves, to be changed by our own creations, to build communities around shared solidarities and shared dreams.

In conclusion, the choice before us is stark: do we want films that think, or films that are merely generated to make a profit? The push for AI in cinema represents more than methodological convenience- it is the final enclosure of one of our last commons, the space where we gather to make meaning together. When we automate the labor of storytelling, we lose the capacity to surprise ourselves, to be changed by our own creations, to build communities around shared solidarities and shared dreams. The Malegaon filmmakers remind us what we stand to forfeit: not perfection, but presence; not efficiency, but encounter; not content, but connection. This is why we must resist. The fight against AI-generated film isn’t a Luddite rejection of technology, but a defense of the human spirit. It is to move towards a right to work, to collaborate, to fail, and to ultimately create something that bears an undeniable fingerprint. It is a fight to ensure that our stories remain ours to tell.