An AI script editor could help decide what films get made in Hollywood

by · MIT Technology Review

Every day across Hollywood, scores of film school graduates and production assistants work as script readers. Their job is to find the diamonds in the rough from the 50,000 or so screenplays pitched each year and flag any worth pursuing further. Each script runs anywhere from 100 to 150 pages, and it can take half a day to read one and write up a “coverage,” or summary of the strengths and weaknesses. With only about 50 of these scripts selling in a given year, readers are trained to be ruthless. 

Now the film-focused tech company Cinelytic, which works with major studios like Warner Bros. and Sony Pictures to analyze film budgets and box office potential, aims to offer script feedback with generative AI. 

Today it launched a new tool called Callaia, which amateur writers and professional script readers alike can use to analyze scripts at $79 each. Using AI, it takes Callaia less than a minute to write its own coverage, which includes a synopsis, a list of comparable films, grades for areas like dialogue and originality, and actor recommendations. It also makes a recommendation on whether or not the film should be financed, giving it a rating of “pass,” “consider,” “recommend,” or “strongly recommend.” Though the foundation of the tool is built with ChatGPT’s API, the team had to coach the model on script-specific tasks like evaluating genres and writing a movie’s logline, which summarize the story in a sentence. 

“It helps people understand the script very quickly,” says Tobias Queisser, Cinelytic’s cofounder and CEO, who also had a career as a film producer. “You can look at more stories and more scripts, and not eliminate them based on factors that are detrimental to the business of finding great content.”

The idea is that Callaia will give studios a more analytical way to predict how a script may perform on the screen before spending on marketing or production. But, the company says, it’s also meant to ease the bottleneck that script readers create in the filmmaking process. With such a deluge to sort through, many scripts can make it to decision-makers only if they have a recognizable name attached. An AI-driven tool would democratize the script selection process and allow better scripts and writers to be discovered, Queisser says.

The tool’s introduction may further fuel the ongoing Hollywood debate about whether AI will help or harm its creatives. Since the public launch of ChatGPT in late 2022, the technology has drawn concern everywhere from writers’ rooms to special effects departments, where people worry that it will cheapen, augment, or replace human talent.  

In this case, Callaia’s success will depend on whether it can provide critical feedback as well as a human script reader can. 

That’s a challenge because of what GPT and other AI models are built to do, according to Tuhin Chakrabarty, a researcher who studied how well AI can analyze creative works during his PhD in computer science at Columbia University. In one of his studies, Chakrabarty and his coauthors had various AI models and a group of human experts—including professors of creative writing and a screenwriter—analyze the quality of 48 stories, 12 that appeared in the New Yorker and the rest of which were AI-generated. His team found that the two groups virtually never agreed on the quality of the works. 

“Whenever you ask an AI model about the creativity of your work, it is never going to say bad things,” Chakrabarty says. “It is always going to say good things, because it’s trained to be a helpful, polite assistant.”

Cinelytic CTO Dev Sen says this trait did present a hurdle in the design of Callaia, and that the initial output of the model was overly positive. That improved with time and tweaking. “We don’t necessarily want to be overly critical, but aim for a more balanced analysis that points out both strengths and weaknesses in the script,” he says. 

Vir Srinivas, an independent filmmaker whose film Orders from Above won Best Historical Film at Cannes in 2021, agreed to look at an example of Callaia’s output to see how well the AI model can analyze a script. I showed him what the model made of a 100-page script about a jazz trumpeter on a journey of self-discovery in San Francisco, which Cinelytic provided. Srinivas says that the coverage generated by the model didn’t go deep enough to present genuinely helpful feedback to a screenwriter.

“It’s approaching the script in too literal a sense and not a metaphorical one—something which human audiences do intuitively and unconsciously,” he says. “It’s as if it’s being forced to be diplomatic and not make any waves.”

There were other flaws, too. For example, Callaia predicted that the film would need a budget of just $5 to $10 million but also suggested that expensive A-listers like Paul Rudd would have been well suited for the lead role.

Cinelytic says it’s currently at work improving the actor recommendation component, and though the company did not provide data on how well its model analyzes a given script, Sen says feedback from 100 script readers who beta-tested the model was overwhelmingly positive. “Most of them were pretty much blown away, because they said that the coverages were on the order of, if not better than, the coverages they’re used to,” he says. 

Overall, Cinelytic is pitching Callaia as a tool meant to quickly provide feedback on lots of scripts, not to replace human script readers, who will still read and adjust the tool’s findings. Queisser, who is cognizant that whether AI can effectively write or edit creatively is hotly contested in Hollywood, is hopeful the tool will allow script readers to more quickly identify standout scripts while also providing an efficient source of feedback for writers.

“Writers that embrace our tool will have something that can help them refine their scripts and find more opportunities,” he says. “It’s positive for both sides.”