The AI Revolution’s Impact on Filmmaking and Film Schools

 

AI is transforming many industries and impacting corresponding job markets.  The disruption is just beginning and nowhere has its impact been more visible than in filmmaking.  The first AI created video commercial just aired in the NBA finals.  We will take a look at the impact AI has so far had on filmmaking as a profession and then delve into how this affects the way filmmaking is taught in film schools.  The philosophical question of whether this is a good thing or not we will leave to others–in the real world, the impact is underway and will only pick up steam in the months and years to come.

 

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TABLE OF CONTENTS 

• The AI Revolution in Filmmaking; Threat or Opportunity?
  • Where AI and Human Skills Meet in Filmmaking
  • The Rise of AI in Film
    • The Bridge: An AI Short Film Example
  • Jobs Most Vulnerable to AI Automation
    • Kalshi: An AI Commercial Example
  • Jobs That Will Demand Humans
  • The Future of Filmmaking: Collaboration, Not Replacement
  • Where Things Are Going Next
• The Impact of AI on Film School Curriculum and Teaching Methods
  • AI Integration in Filmmaking Education
  • Introduction
  • Navigating the Intersection of Tradition and AI in Film Education
  • AI Tools in Filmmaking: A Curriculum Overview
  • Changes in Teaching Methods
  • Challenges and Opportunities
  • Empowering Filmmakers for the AI Age
  • Adapting Film Schools for AI Integration
  • The Lag Time in Adopting AI into the Film Curriculum
• Film Connection’s Predictions and Solutions

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The AI Revolution in Filmmaking: Threat or Opportunity?

The Rise of AI in Film

AI is rapidly transforming various aspects of the film industry, from pre-production to post-production. Its capabilities range from script analysis and storyboarding to visual effects (VFX), editing, and even generating synthetic actors. This technological advancement raises concerns about job displacement but also offers the potential for increased efficiency, cost reduction, and new creative avenues.

 

 

 

The Bridge: An AI Short Film

by Marlon Torres

“And my take on AI now? It’s just a tool. Nothing more. The soul of the story—the choices in pacing, mood, framing, and emotion—that’s still 100% me. The prompts, the visual references, the hours of coaxing and tweaking until it felt right… that’s the artistry.  AI didn’t replace me. It simply gave me a new brush to paint with.”  Video Creator Marlon Torres

 

Jobs Most Vulnerable to AI Automation

Several roles within the film industry are particularly vulnerable to automation due to their repetitive or data-driven nature:

 

The Impact of AI on Film School Curriculum and Teaching Methods

AI is moving at warp speed when it comes to advances in film generation.  It seems as if every day there is a new AI tool or upgrade that produces better results, quicker.  There’s always been a lag between what is taught in schools and what is actually practiced in the real-world of commercial filmmaking.  Up until now, this didn’t matter much as generational shifts in equipment and techniques happened over years, if not decades.  Now it matters greatly as this lag can easily mean that by the time you graduate from a film school everything you learned will be obsolete.

 

Introduction

Artificial Intelligence (AI) is rapidly changing the landscape of numerous industries, and filmmaking is no exception. Film schools, traditionally focused on hands-on training and artistic development, are now grappling with the need to incorporate AI into their curricula. This integration presents both opportunities and challenges, requiring a re-evaluation of teaching methods and the skills deemed essential for future filmmakers.

AI Tools in Filmmaking: A Curriculum Overview

Several AI-powered tools are making their way into the filmmaking process, influencing how film schools approach their curriculum.  Given the current acceleration of these AI-powered tools, there influence is only going to grow:

• Scriptwriting and Story Development: AI tools can assist with brainstorming ideas, generating plot outlines, and even writing dialogue. Film schools are beginning to explore how these tools can be used to enhance creativity and efficiency in the scriptwriting process. Curricula are adapting to teach students how to effectively prompt AI models, evaluate generated content, and integrate it into their own creative vision.

• Pre-visualization and Storyboarding: AI can generate realistic pre-visualizations and storyboards based on script descriptions. This allows filmmakers to experiment with different shots and compositions before entering production. Film schools are incorporating these tools into their pre-production courses, enabling students to visualize their projects more effectively and communicate their ideas to crew members.

• Production and Cinematography: While AI-driven cameras are not yet commonplace, AI is being used to enhance camera control, automate certain tasks, and improve image quality. Film schools are introducing students to these technologies, focusing on how AI can assist with tasks such as focus pulling, color grading, and stabilization.

• Post-Production and Editing: AI is revolutionizing post-production with tools for automated editing, visual effects, sound design, and color correction. Film schools are integrating these tools into their editing and post-production courses, teaching students how to leverage AI to streamline their workflows and enhance the quality of their films.

• Distribution and Marketing: AI-powered analytics can help filmmakers understand their audience, optimize marketing campaigns, and distribute their films more effectively. Film schools are incorporating these concepts into their business and marketing courses, preparing students to navigate the evolving landscape of film distribution.

 

Changes in Teaching Methods

The integration of AI into film school curricula necessitates a shift in teaching methods:

• Hands-on Training with AI Tools: Film schools are moving beyond traditional filmmaking techniques to incorporate hands-on training with AI-powered tools. This includes workshops, tutorials, and project-based assignments that allow students to experiment with AI and integrate it into their filmmaking process.

• Emphasis on Critical Thinking and Creative Problem-Solving: As AI automates certain tasks, the emphasis shifts towards critical thinking, creative problem-solving, and artistic vision. Film schools are focusing on developing these skills, encouraging students to use AI as a tool to enhance their creativity rather than replace it.

• Collaboration between Technical and Artistic Disciplines: The integration of AI requires collaboration between students from different disciplines, such as filmmaking, computer science, and design. Film schools are fostering interdisciplinary collaboration to encourage students to learn from each other and develop innovative solutions.

• Ethical Considerations: Film schools are also addressing the ethical implications of AI in filmmaking, including issues such as bias, copyright, and the impact on human jobs. Students are encouraged to consider these ethical issues and develop responsible practices for using AI in their work.

“In this rapidly evolving landscape, Film Connection’s Mentor/Apprentice method of education is more relevant than ever as their students are exposed to the commercial applications of AI usage in filmmaking utilizing the latest technology and real-world experienced instructors.” Film Connection

 

Challenges and Opportunities

While AI offers numerous opportunities for film schools, it also presents several challenges:

• Keeping Up with Rapid Technological Advancements: AI technology is constantly evolving, requiring film schools to continuously update their curricula and teaching methods.  Film schools will always lag behind commercial film production companies in the latest AI technology: the film school must go through budgetary and planning bureaucratic steps; the commercial production company must adapt to the latest developments in order to stay competitive and survive.

• Balancing Traditional Filmmaking Skills with AI Integration: Film schools must strike a balance between teaching traditional filmmaking skills and integrating AI into the curriculum. It is important to ensure that students develop a strong foundation in filmmaking principles before learning how to use AI tools.

• Addressing Concerns about Job Displacement: Some filmmakers worry that AI will displace human jobs in the industry. Film schools need to address these concerns and prepare students for a future where AI and humans work together.

Despite these challenges, the integration of AI into film school curricula presents a significant opportunity to prepare students for the future of filmmaking. By embracing AI and adapting their teaching methods, film schools can empower students to become innovative and successful filmmakers in the age of artificial intelligence.

AI is poised to revolutionize the film industry, and film schools must adapt to prepare their students for this new reality. By integrating AI tools into the curriculum, shifting teaching methods, and addressing ethical considerations, film schools can empower students to become innovative and successful filmmakers in the age of artificial intelligence. The key is to view AI not as a replacement for human creativity, but as a powerful tool that can enhance and augment the filmmaking process.

The Lag Time in Adopting AI Into the Film Curriculum

The lag time between the adoption of cutting-edge technology by real-world professionals in the music and film businesses and its comprehensive integration into college film and audio curriculums can vary significantly, but generally ranges from 1 to 5+ years, with some areas experiencing even longer delays.

Here’s a breakdown of the factors contributing to this lag:

1. Rapid Pace of Technological Change:

• • Film: Technologies like virtual production (LED volumes), advanced AI tools for editing and visual effects, real-time rendering, 8K+ cameras, and specialized drones are constantly evolving.

 

• • Music: AI for music creation, mixing, and mastering, immersive audio (Dolby Atmos, Spatial Audio), blockchain for royalties, advanced cloud collaboration tools, and evolving digital audio workstations (DAWs) are at the forefront.

 

• • The speed at which these tools are developed and become industry standard often outpaces the slower, more deliberate process of academic curriculum development.

 

2. Curriculum Development and Accreditation Cycles:

• • Bureaucracy: Colleges and universities often have rigid curriculum structures and approval processes. Any significant change to a program typically requires multiple layers of review (departmental, college-level, university-wide, and sometimes external accreditation bodies). This can take months or even years.

 

• • Faculty Expertise: Professors need to be trained on new technologies themselves, which requires time, resources, and often a shift in their own research or teaching focus. Not all faculty members are constantly engaged in active industry production.

 

• • Resource Allocation: Implementing new technology means investing in expensive hardware, software licenses, and specialized lab facilities. Budgets for higher education are often tight, and securing funding for cutting-edge equipment can be a significant hurdle. Upgrading labs frequently is very costly.

 

3. “Proven” vs. “Emerging” Technologies:

• • Colleges often wait for a technology to become somewhat established and proven in the industry before fully integrating it into the core curriculum. This is to ensure they are teaching skills that will have longevity and real-world applicability for graduates, rather than chasing every fleeting trend.

 

• • However, this cautious approach can mean that graduates are entering the workforce familiar with tools that are already being superseded by newer, more efficient workflows.

 

4. Industry-Academia Collaboration (or Lack Thereof):

• • Schools with strong ties to the industry (e.g., located near major production hubs like Los Angeles, New York, or Nashville) tend to be more agile in updating their curricula. They may have adjunct professors who are current industry professionals, guest lecturers, and opportunities for internships that expose students to the latest tech.

 

• • For schools without these strong connections, the lag can be much more pronounced.

 

5. Focus on Foundational Skills:

• • Many programs argue that teaching core principles (e.g., storytelling, sound design theory, lighting principles, composition, recording techniques) is more important than specific software or hardware. While this has merit, it can lead to graduates who understand the concepts but lack hands-on experience with the tools currently used.

 

General Lag Time Estimates:

• 1-2 Years (for core software updates/workflow shifts): For widely adopted software updates (e.g., new versions of Pro Tools, Avid Media Composer, DaVinci Resolve, Adobe Creative Suite) or common camera models, colleges might update their teaching within a year or two as new versions are released or become dominant.

 

• 3-5 Years (for significant technological shifts): For more substantial shifts like the widespread adoption of virtual production stages, advanced AI tools, or widespread immersive audio production, the lag time for full curriculum integration tends to be longer, as it requires more significant investment and faculty retraining.

 

• 5+ Years (for truly revolutionary, yet still niche, technologies): Some highly experimental or extremely expensive technologies might take even longer to trickle down into common academic settings, if they ever do, unless the program is specifically research-focused.

 

Mitigation Efforts by Colleges:

Many film and audio programs are actively working to reduce this lag by:

• Employing adjunct faculty who are active industry professionals.

 

• Offering short courses, workshops, and certifications on new technologies.

 

• Encouraging internships and experiential learning.

 

• Building industry partnerships for equipment donations, beta testing, and guest speakers.

 

• Focusing on transferable skills and adaptability, preparing students to learn new technologies quickly.

 

In essence, while colleges strive to stay current, the inherent nature of academia (curriculum cycles, funding, faculty expertise) combined with the breakneck speed of technological innovation creates an unavoidable lag. Students often need to be proactive in seeking out cutting-edge knowledge through internships, online resources, and personal projects to fully bridge the gap.

 

“For 40 years the Film Connection has taught filmmaking using the mentor/apprentice (externship) model of education which results in job-ready graduates”

 

The Film Connection Educational Approach Advantages

 

• • It ensures the Film Connection student is always exposed to the most current technology.

• • Curriculum Development is achieved in weeks, not years and the faculty is always engaged in active industry production.

• • Industry-Academia Collaboration is always present as the faculty is working in the industry.

• • Foundational skills are taught alongside technology skills.

• • Lag Time is non-existent.

 

The mitigation efforts traditional film schools are striving for are already part of the Film Connection’s academic approach.  The faculty are active industry professionals.  Short courses, workshops and certifications are the core offerings.  Externships are standard.  Industry partnerships are extensive, built over 40 years of networking with the film industry.

 

 

Film Connection’s Predictions and Solutions:

• Much like the advent of digital filmmaking’s impact on analog filmmaking, the cost barrier to entry as a filmmaker will be lowered. This means even more competition for eyeballs.

• The AI filmmaker will truly be able to be a one-man band, BUT ONLY if they understand the basics of screenwriting, producing, directing, cinematography, lighting, etc. The AI filmmaker will essentially become a combination Screenwriter/AI prompt writer.

• Screenwriting and storyboarding will be essential as the clip length of any AI generated scene will likely remain quite short due to the computer costs of generating scenes. The old standby of “We’ll fix it in post” will be much less relevant–instead the filmmaker will need to know exactly what the finished film will look like before they start generating AI clips.

• Film schools that teach the fundamentals will still be of value. The same skill sets will still be necessary, but how these skills get applied to AI filmmaking will necessitate a change in how they are taught.

• Live or pseudo live TV will probably be the least affected: game shows, newscasts, sports events, reality shows and the like work because they are centered around real people and production costs are relatively low.

• The large film studios will undergo a fundamental shift much like what happened with the record labels when music went digital.

• There will be great challenges for the film artist to monetize their talents. Before digital music took over, the musicians made their money from record sales. Now they make their money from live concerts. It remains to be seen how the film artist will be rewarded financially.

• The film industry unions will have a lot to say as the potential disruption from AI to their members is enormous.

 

“The best way to future-proof film education is with short courses within a commercial film production company that make the latest AI technology available to the student and offer them the benefits of practical expertise and techniques that provide the student with a path towards monetizing their talents in a viable manner.”

“A good story will always be a good story no matter the means of production.”
Film Connection