The Enshittification Audit: Why Streaming Platforms Are Outsourcing Curation to AI-Driven Surveillance

The transition of streaming platforms from libraries of discovery into hyper-optimized surveillance engines represents a fundamental betrayal of the user experience, trading artistic serendipity for a sterilized, algorithmically-enforced feedback loop of engagement.

We are living through the "Enshittification" of our digital entertainment landscape. Coined by author and activist Cory Doctorow, the term describes a predictable pattern: platforms start by being good to their users, then shift to abusing those users to benefit shareholders, and finally, they degrade into a hollowed-out husk of their former selves^[4]. In the world of streaming platforms, this decline is no longer just about price hikes or ad-supported tiers; it is about the quiet death of human curation^[1].

For years, we marveled at the "Netflix effect"—the ability to find hidden gems and global cinema at the touch of a button. Today, that magic is being replaced by opaque, AI-driven architectures designed to maximize "stickiness" above all else^[1]. As the industry moves from a growth-at-all-costs model to a profitability-focused era, the primary goal of these platforms has shifted. They are no longer curating content; they are engineering behavioral compliance^[1].

The Surveillance Feedback Loop

The core of this shift lies in the integration of generative AI to manipulate our perception of content. Netflix, for instance, has long utilized AI to personalize thumbnails and promotional imagery^[2]. While this might seem like a benign optimization to help you find something to watch, it is, in reality, a form of digital surveillance. Every click, every hover, and every abandonment is fed into a machine that learns exactly how to manipulate your impulse to watch^[1].

I contend that this process creates a dangerous feedback loop. By prioritizing content that is "algorithmically safe"—media that the AI predicts will keep you scrolling rather than challenging your perspective—platforms are actively suppressing niche, high-quality, or experimental works. The evidence suggests that we aren't being shown what we *might* love; we are being shown what the machine knows will keep us trapped in the ad-inventory pipeline^[1].

As Statista reports, global streaming services are projected to spend over $200 billion on content in 2024, yet an increasing portion of those resources is being diverted away from production and toward data analytics and ad-tech infrastructure^[3]. When a platform spends more on the surveillance of its viewers than on the creative voices of its filmmakers, the artistic integrity of the entire industry is compromised^[1].

The Counter-Argument: Solving Choice Paralysis

Industry proponents often argue that algorithmic personalization is an essential tool for the modern viewer. With thousands of titles available, "choice paralysis" is a legitimate issue. In this view, AI serves as an indispensable librarian, sorting through the noise to provide relevant recommendations to diverse global audiences. Without these systems, they argue, the sheer volume of content would render these platforms unusable.

Furthermore, supporters contend that data-driven curation allows for more efficient content distribution. By understanding user preferences at a granular level, platforms can ensure that niche content actually finds its target audience, rather than being buried in a static, chronological library. From this perspective, the algorithm is not a tool of control, but a bridge connecting creators to their specific fans.

The Verdict: A Loss of Serendipity

While the "choice paralysis" argument is convenient for tech executives, it ignores the crucial distinction between discovery and addiction. Being shown a movie that fits your exact demographic profile is not "discovery"—it is a confirmation bias loop. True curation requires the human element: the risk-taking editor, the taste-making critic, and the serendipity of stumbling upon something that defies your data profile.

As Cory Doctorow famously stated, "Platforms are no longer trying to be good at their jobs; they are trying to be good at extracting value from the people who use them."^[4] When we outsource our taste to an AI designed to keep us watching ads, we lose the very thing that made streaming revolutionary. We are trading the infinite variety of human culture for the narrow, predictable output of a profit-seeking machine^[1].

It is time for an audit of our streaming habits. We must demand transparency in algorithmic design and support platforms that prioritize human-led editorial discovery. If we don’t, we risk turning our digital libraries into nothing more than automated, ad-supported echo chambers. Choose your content, don't let the algorithm choose for you.