Three years after the 2023 strikes raised alarms about artificial intelligence replacing entertainment workers, some of those same workers are now training the very 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. This phenomenon is known as Reinforcement Learning from Human Feedback (RLHF), and it involves fine-tuning AI models by providing human preferences and evaluations.

Hollywood workers explain why they are training AI models

According to a report from 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. Former HBO development executive Steven Woolworth had a similar motivation, calling the work a way to stay informed rather than bury his head in the sand while job hunting proved fruitless for over a year.

Both found gigs through a recruiting platform called Mercor, which pairs domain experts with AI companies needing human feedback. This trend lines up with a broader industry pattern, with Amazon also turning to AI to cut film and TV production costs through its own dedicated studio. The gig economy for AI training has expanded rapidly, with platforms like Appen, Scale AI, and Toloka also offering similar roles to creative professionals.

The motivation for these workers varies. Some see it as a temporary lifeline while they wait for traditional Hollywood jobs to return. Others view it as a way to stay relevant in an industry that is rapidly adopting generative AI tools. A few, like Sena, believe that understanding AI from the inside could give them a competitive edge when they eventually return to their core professions.

The ethical dilemma is stark. Many of these workers participated in the 2023 strikes, which demanded protections against AI replacing human creativity. Now, they are directly contributing to the improvement of the same models that studios are using to generate scripts, edit footage, and even create visual effects. The irony is not lost on them. As one anonymous writer told The Hollywood Reporter, "Every time I click a button to tell the model that this plot point is better than that one, I am helping the machine get better at my job."

What the work actually looks like once you are in it

Screenwriter Ruth Fowler described a far rougher experience in her own essay for Wired, detailing eight months and twenty contracts across five different platforms. The pay ranges from $16 per hour for entry-level annotation work up to $150 per hour for specialized writing tasks. She described abrupt project cancellations, shifting pay rates, and young, inexperienced managers overseeing workers decades into their careers.

Fowler noted that the work is often isolating. Workers are typically assigned to tasks like ranking AI-generated story summaries, correcting grammar in dialogue, or identifying which character arcs feel most realistic. The work requires a high level of domain expertise, but the platforms treat these workers as independent contractors, offering no benefits, job security, or upward mobility.

Another key challenge is the instability of the gigs. Projects can disappear overnight when an AI company changes its training data requirements or runs out of funding. Workers must constantly monitor multiple platforms to maintain a steady income. The unpredictability mirrors the very freelance nature that has long defined Hollywood, but with even less transparency about pay and expectations.

Despite the difficulties, demand for RLHF workers continues to grow. AI companies need large volumes of high-quality human feedback to train models capable of generating compelling narratives, realistic dialogue, and culturally sensitive content. Hollywood workers, with their deep understanding of story structure, character development, and audience expectations, are ideal for this work.

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, even as lawsuits pile up alleging worker misclassification and unstable scheduling across the industry. The legal landscape is murky. Some workers have filed class-action suits against platforms, arguing that they should be classified as employees with benefits and protections. Others have raised concerns about copyright and intellectual property, noting that the AI models are essentially learning from their creative labor without compensation beyond the hourly wage.

Even Martin Scorsese has officially joined the AI camp, a sign of how far acceptance of these tools has spread across the industry. The legendary director recently partnered with an AI company to explore how machine learning could assist in restoring classic films and generating archival materials. While Scorsese's involvement is pragmatic, it underscores how even the most respected figures in cinema are now engaging with AI technologies.

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. For many in Hollywood right now, training the machine has become less about curiosity and more about simply making rent. Gilligan remarked in a recent interview, "I can't blame anyone for trying to survive. But we need to be honest about what we are building. We are handing over the keys to the kingdom one feedback loop at a time."

The broader context is that Hollywood has been shedding jobs for years. The 2023 strikes were a symptom of a larger structural shift, with streaming services cutting costs, traditional studios merging, and production moving to cheaper locations. AI is accelerating these changes. Studios now use generative AI to produce rough cuts, write synopses, and even compose music. While these tools are still far from replacing human creativity, they reduce the need for entry- and mid-level talent.

For workers who are training these models, the future remains uncertain. Some hope that by participating, they can shape the technology to be more ethical and less destructive. Others fear they are simply delaying the inevitable. One thing is clear: the gig economy for AI training is becoming a permanent fixture in the entertainment industry, and the line between human and machine creativity is blurring faster than anyone anticipated.

Source:Digital Trends News