Is GenAI a Sustaining or Disruptive Innovation in Hollywood?
Progressive Syntheticization vs. Progressive Control
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There is a lot of debate and confusion in Hollywood about the likely impact of GenAI on the TV and film production process and cost structure. (For reference, I’ve written a lot about the topic, including Forget Peak TV, Here Comes Infinite TV, How Will the “Disruption” of Hollywood Play Out?, AI Use Cases in Hollywood and What is Scarce When Quality is Abundant.)
Some believe that the effects will be relatively marginal. They reason that it may increase efficiency and reduce costs, but as was the case for innovations like DSLRs or CGI, these savings will mostly end up as higher production values on screen. Others think it will be transformative. The AI-video corner of Twitter/X (AIvidtwit?) includes plenty of posts declaring that “Hollywood is dead” and the impact of AI on jobs was, of course, a central issue in the recent WGA and SAG-AFTRA strikes.
Another way of framing this split is that the former camp is viewing GenAI as a sustaining innovation and the latter as a disruptive innovation. So, which is it? The answer is that it can be both, depending on how it is used.
The application of GenAI to TV and film production is fundamentally about “syntheticization,” replacing physical and labor-intensive elements of the production process — sets, locations, vehicles, lighting, cameras, costumes, make-up and people, both in front and behind the camera — with synthetic elements, made by a computer. This is much more efficient, but it requires a tradeoff with quality control. Each pixel created by a computer delegates some human oversight and judgment to AI.
Opinions in Hollywood about GenAI are polarized partly because syntheticization is happening from two different directions, reflecting opposing approaches to the tradeoff between efficiency and quality control. One approach is what we can call “progressive syntheticization:” systematically incorporating GenAI into existing production processes. The other is what we can call “progressive control:” starting out entirely synthetic and systematically increasing creator control. The former is a sustaining innovation, the latter is disruptive. Like in Rashomon, different perspectives yield different conclusions.
In this essay, I explore the distinctions between these approaches and the implications.
Tl;dr:
- GenAI can be either a sustaining or a disruptive innovation, depending on how it is used. Whether you think it is the former or the latter depends on who you are and where you look.
- Many traditional studios, both majors and independents, are pursuing “progressive syntheticization” and incrementally incorporating GenAI tools into existing workflows. Like most incumbents, they view technology as a tool to improve the cost and/or quality of existing products and processes, the definition of a sustaining innovation.
- At the same time, AI video generators, such as Runway, Pika and Stable Video Diffusion, have started off as entirely synthetic, with limited creator control and are providing more control over time (“progressive control”). Not surprisingly, creators outside the traditional Hollywood system are the most excited about these tools.
- The initial output of these tools was almost a joke — surreal, disturbing and generally unwatchable (in the language of disruption theory, clearly not “good enough”). But they are improving at a startling pace and creators are developing custom workflows using multiple tools to get even more control and better output.
- This is the definition of a disruptive innovation: something that starts out as an inferior product, gets a foothold, and then gets progressively better.
- When a technology can either a sustaining or disruptive innovations, the sustaining use cases usually go mainstream first. So, the first mainstream commercial applications of GenAI may not move the needle much.
- In parallel, the AI video generators will keep getting better until they cross the threshold of “good enough,” for a sufficient number of consumers, for certain content genres.
- GenAI may look like a sustaining innovation — until it suddenly doesn’t. It will be easy to be lulled into complacency, if you’re looking in the wrong place.
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