DOI: 10.18848/2470-9247/cgp/a149 ISSN: 2470-9247

Orchestrating Meaning

Tamilarasan P, Caleb Theodar
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<p>Adaptation screenwriting faces a structural challenge in the era of generative artificial intelligence (generative AI): while tools such as GPT-4-based assistants and specialized script generators proliferate, no theoretically grounded framework has yet established principled guidelines for human–AI collaboration in this domain. This study addresses that gap by synthesizing adaptation theory, classical narratology, and recent computational research in neuro-symbolic story generation to construct a human-led, ethically governed co-creation model for adaptation practice. The methodology combines conceptual synthesis with close textual analysis of two landmark AI-generated short films, <em>Sunspring</em> and <em>Zone Out</em> and critical engagement with guild policy documents and industry scholarship. Analysis reveals that AI systems excel at generating stylistic variation and ideational speed but consistently fail to sustain causal coherence, character interiority, and thematic intentionality. Hybrid neuro-symbolic workflows combining human-defined symbolic constraints with neural language generation produce measurably more reliable narrative logic than unguided neural approaches. Ethically, AI deployment risks narrative homogenization and the amplification of representational bias encoded in training data. This study contributes a theoretically coherent framework with actionable implications for screenwriting practice, pedagogy, and guild policy: bounded AI deployment for ideation and stylistic exploration, human authority over interpretive intent and voice, and embedded representational sensitivity throughout production.</p>

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