Enterprise AI Analysis
Underground AI? Critical Approaches to Generative Cinema through Amateur Filmmaking
Authors: Brett A. Halperin, Diana Flores Ruíz, Daniela K. Rosner
Amateurism has long helped human-computer interaction (HCI) scholars map alternatives to status quo technology developments, cultures, and practices. Following the 2023 Hollywood film worker strikes, many scholars, artists, and activists alike have called for alternative approaches to AI that reclaim the apparatus for co-creative and resistant means. Towards this end, we conduct an 11-week diary study with 20 amateur filmmakers of 15 AI-infused films, investigating the emerging space of generative cinema as a critical technical practice. Our close reading of the films and filmmakers' reflections on their processes reveal four critical approaches to negotiating AI use in filmmaking: minimization, maximization, compartmentalization, and revitalization. We discuss how these approaches suggest the potential for underground filmmaking cultures to form around AI with critical amateurs reclaiming social control over the creative possibilities.
Key Research Insights
Our study uncovered novel insights into generative AI adoption within creative practices. Here are the core metrics from our comprehensive analysis:
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Study Duration
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Amateur Filmmakers
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AI-Infused Films
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Critical Approaches Identified
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Minimization
Maximization
Compartmentalization
Revitalization
Minimization: Containing AI's Encroachment
This approach involves minimally using or even refusing AI tools in filmmaking, driven by philosophical objections, ethical concerns (e.g., bias, privacy), or practical limitations. Filmmakers found AI counter-productive for their creative visions or prone to generating stereotypical content.
Enterprise Application: Companies can learn from this approach to understand when AI integration may be detrimental to core creative or ethical standards. It highlights the importance of evaluating AI's true value beyond novelty, especially when it introduces bias or workflow complexities. This strategy is valuable for risk mitigation and maintaining brand integrity in sensitive creative outputs.
Maximization: Exposing AI's Pitfalls as Critique
Filmmakers adopting this approach hyper-used AI, often leaning into its technical limitations and flaws, to create satirical commentary or social critique. By pushing AI to its extremes, they exposed inherent biases, "empty" corporate rhetoric, or problematic narratives around AI's capabilities.
Enterprise Application: This highlights a strategy for ethical AI development and deployment. By proactively stress-testing AI systems and embracing their "flaws" for internal review or critical analysis, organizations can gain deeper insights into potential misuses, biases, or unintended outputs. It can serve as a powerful internal audit mechanism, transforming perceived weaknesses into opportunities for robust critique and improvement.
Compartmentalization: Strategic Siling of AI Functions
This approach involves intentionally restricting AI's role to specific functions or phases of production, such as visual effects, image generation, or script feedback, without allowing it to automate or interfere with core human-authored practices like storytelling or animation. AI augments rather than replaces key creative elements.
Enterprise Application: This model provides a blueprint for controlled, high-value AI integration. By identifying specific, well-defined tasks where AI can enhance efficiency (e.g., automated subtitles, visual effect rendering) without compromising human creativity or control in critical areas (e.g., scriptwriting, core narrative design), businesses can optimize workflows and leverage AI for augmentation rather than wholesale automation. It emphasizes a deliberate, bounded approach to AI adoption.
Revitalization: Imbuing AI with New Lifeworlds
Filmmakers revitalized AI by embracing its serendipitous outputs, working around its biases, and leveraging its capabilities to conjure imaginative lifeworlds that would be otherwise difficult to create. This involved artistic confrontation with AI's politics of representation and finding creative workarounds.
Enterprise Application: This approach underscores the potential for AI to unlock novel forms of innovation and address existing systemic biases through creative intervention. Organizations can foster internal "critical creative" teams who are empowered to experiment, challenge AI's normative outputs, and find unexpected, inclusive applications. It redefines AI's role from a mere tool to a co-creative partner that, with human ingenuity, can lead to more diverse and representative solutions.
Enterprise Process Flow: Study Methodology
11-Week Generative AI Filmmaking Group
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Weekly Reflections & Critiques
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Short Film Production (2-10 min)
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AI Tool Integration (Optional)
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Final Film Submission
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Public Screening & Discussion
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AI-Infused Films Created
| Approach | Core Goal | AI Engagement Strategy |
|---|---|---|
| Minimization | Contain AI's encroachment, avoid corruption of craft. |
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| Maximization | Expose AI's pitfalls and harms as social critique. |
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| Compartmentalization | Integrate AI for specific functions without widespread interference. |
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| Revitalization | Imbue AI with alternative lifeworlds, rework its politics, address bias. |
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Case Study: Revitalizing AI with "LOVE IN VR"
"LOVE IN VR" (2024) by Maza Hailu exemplifies the Revitalization approach. This afrofuturist-romance leveraged AI at every production phase, not for uncritical automation, but to confront and rework its politics of representation and inclusion. Hailu actively addressed algorithmic biases related to Black hairstyles and skin tones encountered in Runway's image generators. Instead of abandoning AI, she employed adroit camera control (over-the-shoulder shots, silhouettes) to work around these limitations, and even embraced the aesthetic of glitches and distortions as part of the film's visual narrative.
This case highlights how creative practitioners can transform AI's shortcomings into opportunities for creating liberatory lifeworlds, pushing back against normative representations, and demonstrating how human ingenuity can guide AI towards more diverse and equitable outcomes.
Calculate Your Potential AI Impact
Estimate the potential efficiency gains and cost savings your enterprise could realize by strategically integrating AI, inspired by the varied approaches in creative industries.
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Your AI Implementation Roadmap
A typical enterprise AI integration involves several phases, tailored to align with critical approaches and ensure successful, ethical deployment.
Phase: Strategic Assessment & Goal Setting
Define clear objectives, identify key pain points, and assess current infrastructure. Determine which critical approach (Minimization, Maximization, Compartmentalization, Revitalization) best aligns with organizational values and project scope.
Phase: Pilot & Experimentation
Conduct small-scale pilot projects, embracing an "amateur" mindset for exploration. Gather feedback on AI tool integration, technical limitations, and unexpected outputs. Document "frictions" and creative workarounds.
Phase: Ethical AI Development & Bias Mitigation
Integrate robust ethical AI frameworks. Actively identify and mitigate algorithmic biases, using strategies like "revitalization" to adapt and create more inclusive outputs. Prioritize data privacy and consent.
Phase: Targeted Deployment & Integration
Implement AI solutions for specific, high-impact functions, leveraging "compartmentalization." Ensure seamless integration with existing systems, focusing on augmentation rather than full automation where human oversight is critical.
Phase: Continuous Monitoring & Iteration
Establish ongoing monitoring for performance, ethical compliance, and user feedback. Iterate on AI models and integration strategies, remaining agile and open to adapting based on real-world impact, much like an evolving creative process.
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