Netflix's massive spending on films like the $320 million "The Electric State," which quickly fell from the streamer's top spot to obscurity, highlights a trend: the "algorithm movie." These films, often starring actors like Ryan Reynolds and Jennifer Aniston, prioritize broad appeal and easily digestible storylines, sometimes even incorporating notes to ensure viewers can follow along even with passive viewing. This strategy, while generating massive content volume, has raised concerns among independent producers like Ted Hope, who worry that it prioritizes audience acquisition over artistic merit. Netflix, with over 300 million subscribers, wields immense influence over cinema's future, yet the extent of its algorithm's impact on creative decisions remains debated. While the company denies algorithmic film commissioning, former employees describe a system incorporating thousands of "altgenres" to tailor recommendations and subtly influence creative choices.
The system, initially based on user ratings, transitioned to implicit recommendations using viewer behavior—what content was watched, how long, and on which devices. This massive dataset informs everything from greenlighting decisions to genre classifications, subtly nudging filmmakers toward more conventional storytelling and aesthetic choices. While Netflix claims data enhances, not replaces, creative processes, several filmmakers and executives describe a sense of pressure to conform to data-driven suggestions regarding narratives and pacing.
Netflix's recent shift toward a tighter budget and a renewed focus on quality, spearheaded by new executives, suggests a potential course correction. The company's success, however, indicates that its current model of "gourmet cheeseburgers"—familiar, high-quality mass-market content—effectively sustains subscriber numbers, even if it results in a homogenization of cinematic output and raises concerns about the future impact of AI's role in creative processes.
Impact Statement: Netflix's data-driven approach significantly impacts film production, potentially homogenizing content and challenging the traditional film industry business model. The increasing role of AI further intensifies these concerns.