Three years after the 2023 strikes raised alarms about artificial intelligence replacing entertainment workers, some of those same workers are now training the technology that worries them. As film and television jobs grow harder to find, writers, editors, and executives across Hollywood are quietly taking gig work just to pay the bills. The practice is called Reinforcement Learning from Human Feedback (RLHF), and it involves fine-tuning AI models by providing human judgments on outputs.

For many, it is a reluctant pivot. The strikes of 2023 were partly about protecting human creativity from automation, yet now the very people who marched on picket lines find themselves feeding the machine. The paradox is not lost on them, but economic necessity has a way of quieting ideals.

Hollywood workers explain why they’re training AI models

According to The Hollywood Reporter, editor Gabe Sena turned to AI training after a stretch of unemployment, saying he wanted to understand the technology rather than simply fear it. He found work on a platform called Mercor, which pairs domain experts with AI companies needing human feedback. Sena’s reasoning was pragmatic: if AI is going to reshape his industry, he might as well learn how it operates from the inside.

Former HBO development executive Steven Woolworth had a similar motivation. He described the gigs as a way to stay informed rather than bury his head in the sand. After more than a year of fruitless job hunting, Woolworth realized that traditional Hollywood roles were no longer coming back in the numbers they once had. He now spends his days rating AI-generated dialogue and checking for narrative consistency.

Both men are part of a growing workforce that the entertainment industry never anticipated: human trainers for the very systems that could eventually replace entry-level and mid-level creative jobs. The platforms that connect these workers to AI labs have become a quiet safety net for a profession in crisis.

What the work actually looks like once you’re in it

Screenwriter Ruth Fowler described a far rougher experience in her own essay for Wired. She detailed eight months and twenty contracts across five different platforms. The pay ranges from $16 an hour for entry-level annotation work to $150 an hour for highly specialized writing tasks. But the inconsistency is brutal. Projects get canceled abruptly. Pay rates shift without notice. Young, inexperienced managers with little understanding of narrative craft oversee workers decades into their careers.

Fowler wrote about the emotional whiplash of being asked to evaluate a plot point’s believability one day and being ghosted by the same client the next. The lack of job security, health benefits, or any sense of professional respect makes the work feel like a step backward for people who once built entire seasons of television.

Yet the demand for RLHF workers keeps growing. AI models need constant human feedback to improve their reasoning, creativity, and adherence to context. The more sophisticated the system becomes, the more nuanced the human evaluation required. Hollywood veterans bring exactly that kind of nuance: years of experience reading scripts, understanding character arcs, and judging what makes a scene work.

That expertise, however, is being commoditized into piecework. The platforms treat workers as independent contractors, meaning no overtime, no sick leave, no unemployment insurance. Many workers report working multiple contracts simultaneously just to string together a living wage, only to have one of them vanish overnight.

A growing AI industry built on real legal and ethical tension

RLHF work has expanded rapidly regardless. AI-related job postings within the arts nearly doubled between 2025 and 2026. Major studios are also investing directly: Amazon, for instance, has its own dedicated AI studio aimed at cutting film and TV production costs by using machine learning to streamline script analysis, casting, and even set design.

Even Martin Scorsese has officially joined the AI camp, a sign of how far the acceptance of these tools has spread across the industry. Scorsese, a filmmaker known for his meticulous human touch, has spoken about using AI to restore old films and de-age actors, though he has also expressed caution about its broader applications.

The legal landscape is tangled. Lawsuits pile up alleging worker misclassification and unstable scheduling across the AI training industry. Some plaintiffs argue that the constant project cancellations and pay cuts violate basic labor protections. Others claim that the platforms are deliberately structuring work to avoid providing benefits, a practice that mirrors the gig economy problems seen in ride-sharing and food delivery.

Meanwhile, unions are watching closely. The Writers Guild of America and SAG-AFTRA have both issued statements about the need to regulate AI training work, but so far no formal contracts cover these gigs. The contracts that do exist often contain nondisclosure agreements, preventing workers from discussing pay rates or project details with one another.

Critics of generative AI in Hollywood, like Breaking Bad creator Vince Gilligan, say they understand why struggling workers take these gigs despite the contradictions involved. Gilligan has been vocal about the dangers of AI replacing human storytellers, but he also acknowledges that in an industry where traditional jobs have evaporated, people do what they must to survive.

For many in Hollywood right now, training the machine has become less about curiosity and more about simply making rent. The technology they once feared is now their paycheck. Whether that leads to a permanent shift in how entertainment labor is valued, or just a temporary stopgap until the industry recovers, remains an open question.

The RLHF trend also highlights a deeper structural change. Hollywood has always relied on a pyramid of talent, with a small number of high-profile stars at the top and a broad base of writers, editors, and production assistants below. That base is shrinking. Studios are producing fewer projects, budgets are tighter, and streaming platforms are demanding more content for less money. The humans who once filled those lower rungs are being replaced either by software or by gig workers willing to do the same work for less.

Training AI models may feel like a betrayal of the creative spirit, but it is also a rational adaptation. The people doing this work are not naive about the long-term consequences. They know they are helping build the technology that could eventually eliminate their own jobs entirely. But they also know that rent is due next week, and the AI platforms pay on time.

As the industry continues to evolve, the line between human and machine labor will blur further. The writers, editors, and executives who now sit at computer terminals rating chatbot responses are still artists. They just happen to be artists whose canvas is a dataset.

Source: Digital Trends News