Cinema, as a multimodal creative process, traditionally divides production into various departments: screenwriting, research, directing, cinematography, editing, and sound design. Each department works in tandem to create a cohesive narrative and visual experience. With the advent of multimodal AI generation, these processes become more accessible to individuals and small teams, integrating different aspects of production seamlessly. However, this does not mean displacing professionals in these fields. The history of filmmaking shows how new tools have always been integrated, creating new roles and opportunities. While AI can enhance and streamline creative processes, traditional filmmaking still requires the human touch for real locations, performances, and collaborative creativity. AI in cinema offers innovative cinematic forms that were previously unattainable due to physical and financial constraints. This parallel development can significantly benefit the movie and TV entertainment industries.
The integration of multimodal AI in cinema leverages cutting-edge generative models to streamline and augment every stage of the video production pipeline. Key AI tools include:
ChatGPT - For developing storylines, writing scripts, storyboarding, and generating detailed shot descriptions to prompt other AI systems.
Midjourney/DALL-E - Creating concept art, set designs, character models, props, and visual world-building using text-to-image generation.
RunwayML - Generating short video clips and animations, applying stylized effects and filters, rendering 3D environments and characters.
ElevenLabs - Generating realistic voice performances for characters, narration, and audio dialogue.
Stability AI - Procedurally generating soundtracks, Foley effects, ambiance, and audio textures.
Pika Labs - A tool that generates videos from text descriptions, useful for creating quick concept videos or adding motion to static images.
Synthesia - A platform for generating AI-driven video content with virtual avatars, often used for corporate training, marketing, and personalized video messages.
Luma AI - A tool for generating realistic 3D models and environments from photos and videos, which can be used in video production and virtual reality.
This multimodal approach allows filmmakers to iterate fluidly across all production phases using AI as a complementary creative force. For example, a scriptwriter could prompt ChatGPT to generate a rough narrative premise, then feed that into Midjourney to visualize key characters and environments. Those visuals could drive prompts into RunwayML to render animation previsualization clips with ElevenLabs providing scratch character vocals to set the tone.
2. AI Scriptwriting
I've Been Figuring Out A.I. for Screenwriters
AI screenwriting tools transcend basic text generation by integrating with visual world-building and storytelling systems. A creator can have ChatGPT generate not just plot outlines but detailed shot list descriptions structured as multimedia prompts - feeding both text and visual references to other generative models. This facilitates a back-and-forth iteration between textual and visual ideation that evolves the narrative with each AI-to-AI handoff.
For example, prompting ChatGPT with a basic premise like "A boy finds a mysterious orb in the woods" could yield a few paragraphs breaking that down into potential shots and sequences. Those textual shot descriptions could populate visual prompts into Midjourney rendering concept imagery of the boy, woods, and orb designs. Reviewing those outputs, the creator could re-prompt ChatGPT with new narrative branches inspired by the visuals. The cyclic AI-facilitated process nurtures an expanding web of story and aesthetic interconnections.
3. AI Production
How to Create Worlds with Gen-1 | Runway Academy
On the production front, Midjourney and RunwayML become powerful tools for crafting virtually any cinematic element out of text prompts and uploaded references:
World-Building - Generating lavish concept art, matte paintings, and design plates for entire civilizations, geographies, and eras.
Characters - Designing characters of any species or genre with rich physical and cultural detailing, then rigging and animating them.
Props/Sets - Creating fully dressed environments, vehicles, machinery, and custom set pieces with specific materials and lighting.
Cinematography - Experimenting with unique lenses, film stocks, photographic techniques, and stylized color treatments.
VFX - Generating visual effect shorts like pyrotechnics, energy blasts, force fields, and more for easy compositing in post.
This AI-driven production workflow enables creators to rapidly prototype spectacular animated visuals with unparalleled creative freedom. What might take teams of artists months can be spun up by a single person collaborating with AI - radically accelerating the turnaround from first ideation to final renders.
4. AI Post-Production
TGenerative AI in Premiere Pro powered by Adobe Firefly | Adobe Video
AI ushers in similarly accelerated workflows for video editing, scoring, and post-production audio:
Video Editing - While human editors are still essential for high-level creative decisions, AI tools like RunwayML can automate tedious tasks like transcoding, assembling rough cut sequences, applying effects, and color grading using text prompts.
Voiceovers/Dialogue - Running scripts and storyboards through ElevenLabs generates rich character performances, narration, and lip-synced dialogue animation.
Sound Design - Tools like Stability AI procedurally generate layered Foley effects, ambiences, creatures, vocalizations, and even full scores based on text prompts and reference tracks. AI audio reactors can analyze and embody characteristics from sample sound libraries then remix and recombine those characteristics into new patterns based on text descriptions. A prompt like "ethereal underwater textures for mysterious deep sea sequences" could produce hours of usable underwater ambiences in seconds.
5. AI Effects
How to Remove Background from Video with Green Screen | Runway
While visual effects have relied on filming live plates or 3D graphics for decades, RunwayML and similar tools enable completely new AI-native VFX workflows:
Seamless Compositing - Integrating AI-generated elements into footage with automated rotoscoping/matting using machine learning.
Physical Simulations - Running complex simulations for natural phenomena like water, fire, smoke, and cloth just from text instructions.
Style Transfer - Applying stylized filters and treatments automatically to match any desired photographic aesthetic or painterly rendering.
Green Screen Effects - Automatically keying out backgrounds and replacing them with AI-generated environments or footage, enabling realistic scene integration without traditional green screen setups.
Object Removal - Using AI to seamlessly remove unwanted objects from video footage, filling in the gaps with contextually appropriate backgrounds.
Create Stylized Skins Over Video - Applying AI-generated textures, patterns, or artistic skins over live-action video, transforming the original footage into a completely different visual style.
Upscale Resolution - Enhancing video quality by using AI to upscale resolution, improving the sharpness and clarity of footage, especially older or lower-resolution videos.
True Slow Motion - Generating smooth slow-motion effects by predicting and creating intermediate frames between existing ones, resulting in realistic slow-motion playback even from standard footage.
These AI VFX capabilities open new frontiers for directors to realize their boldest visions unconstrained by live action requirements. Entire movies could theoretically be authored as text streams generating shots, characters, and environments in perfect unison.
6. Unit Exercise
In this exercise, you will create a 30 second video piece dramatizing a key narrative moment or short vignette from your AI-generated world. Leveraging the multimodal AI toolkit (ChatGPT, Midjourney, RunwayML, ElevenLabs, etc.), you will:
Write a brief script or outline for the scene using ChatGPT to generate descriptive shot lists.
Use those shot descriptions as prompts into Midjourney and RunwayML to create concept art, animated character models, environment designs, and rendered video clips for the scene.
Put the elements together into a rough video edit and use tools like ElevenLabs and Stability AI to generate voiceovers, sound effects, score, and other audio elements.
Refine the edit with text-prompted effects, color grading, and titles in RunwayML to establish a cohesive cinematic look.
Export the final video and write a brief reflection analyzing how the AI toolset enabled (or constrained) your creative vision for this world's narrative.
7. Discussion Questions
How does AI-generated cinema represent the next step in the evolution of cinema technology? In what ways does AI create new kinds of visual and narrative experiences that differ from traditional techniques?
How can knowledge of historical cinematic techniques be used to improve AI-driven outputs in storytelling, cinematography, and editing?
What rights do creators have over AI-generated content? How should copyright be managed when both humans and AI contribute to a project?
AHow might roles like director, editor, and producer change in a world where AI is an active collaborator? Could we see the emergence of new roles, such as an "AI Producer" or "AI Story Architect," dedicated to overseeing the human-AI collaborative process?
While AI excels at generating assets, human tasks such as story editing, thematic development, and high-level creative decisions are crucial. What strategies can be developed to better integrate these human contributions with AI-generated content to enhance the overall creative process?
What new methods or practices can be employed to ensure unity in projects that heavily rely on AI? How can AI be trained or guided to maintain a consistent style and tone throughout a film?
How can filmmakers and AI developers work together to cultivate more inclusive "lenses" in AI-generated cinema? What steps can be taken to ensure diverse and equitable representation in AI-driven storytelling?
8. Bibliography
Bordwell, David, and Kristin Thompson. Film Art: An Introduction. 11th ed., McGraw-Hill Education, 2016.
Brown, Blain. Cinematography: Theory and Practice: Image Making for Cinematographers and Directors. 3rd ed., Routledge, 2016.
Field, Syd. Screenplay: The Foundations of Screenwriting. Revised ed., Bantam Dell, 2005.
Murch, Walter. In the Blink of an Eye: A Perspective on Film Editing. 2nd ed., Silman-James Press, 2001.
Rabiger, Michael. Directing: Film Techniques and Aesthetics. 5th ed., Focal Press, 2013.
Thompson, Kristin, and David Bordwell. Film History: An Introduction. 3rd ed., McGraw-Hill Education, 2009.
Truffaut, François. Hitchcock/Truffaut. Revised ed., Simon & Schuster, 1985.
