Is the Content Treadmill Killing Culture?

What if the more content we consume, the less culture we actually absorb?

It sounds counterintuitive. We have access to more music, film, writing, and art than any generation in human history. Streaming libraries run into the tens of millions of tracks and titles. Social platforms serve up an endless scroll of creative work every second. And yet, something feels off. Conversations keep circling back to the same IP franchises. Algorithms keep recommending what we already like. And the feeling that we're genuinely discovering something—something that changes how we see the world—seems increasingly rare.

The Financial Times recently put a name to this unease: the hunger for "content" may be keeping us culturally stuck.

The Content Machine and What It Optimizes For

The distinction between "content" and "culture" isn't just semantic snobbery. Content is optimized for consumption—for clicks, watch time, shares, and engagement metrics. Culture, historically, is what survives that process. It's the work that challenges, disorients, and ultimately reshapes the people who encounter it.

The problem is that the platforms distributing creative work today are not neutral pipes. Netflix, Spotify, YouTube, and TikTok are recommendation engines at their core, and recommendation engines optimize for retention, not revelation. A song that makes you uncomfortable is less likely to be served to you again. A film that demands patience rarely gets surfaced to new audiences. The algorithm, by design, tends to feed you more of what you already are—not what you might become.

The numbers tell part of the story. Spotify hosts over 100 million tracks, yet studies consistently show that the top 1% of artists account for the overwhelming majority of streams. Netflix spent roughly $17 billion on content in 2024, yet subscriber conversations—and cultural discourse—remain dominated by a handful of tentpole titles. Volume has scaled. Cultural diversity of attention has not.

Why Now? The Acceleration Problem

This tension isn't entirely new—mass media has always involved trade-offs between reach and depth. But the current moment has a distinct character. The pace of content production has outrun any individual's capacity to be selective. Generative AI is now capable of producing publishable text, releasable music, and distributable video at a scale and speed that human creators cannot match. Estimates suggest AI-assisted content output will add hundreds of millions of new pieces of media to the internet annually within the next few years.

When supply becomes effectively infinite, scarcity—which historically gave cultural works their weight and meaning—disappears. If everything is available, nothing is urgent. If there's always something new queuing up, there's less reason to sit with something difficult long enough for it to matter.

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There's also a social dimension. Cultural experience has always been partly communal—the shared reference points that let strangers feel like they belong to the same world. But hyper-personalized feeds mean that two people sitting in the same room may be consuming entirely different cultural universes. The common cultural vocabulary that once emerged from shared scarcity (everyone watched the same three channels; everyone read the same bestsellers) is fragmenting into billions of individual playlists.

Who Wins, Who Loses—and Who Decides?

The stakeholders here have very different interests, and it's worth being clear about that.

Platforms benefit from the content treadmill. Engagement metrics go up when users are always chasing the next thing. The longer the queue of unfinished shows and unread articles, the more indispensable the subscription feels. There's a perverse incentive to keep users in a state of perpetual, low-grade consumption rather than deep, satisfied engagement.

Established creators and cultural institutions—legacy publishers, film studios, major labels—have mixed feelings. They've largely learned to play the algorithmic game, investing in franchises and sequels that perform reliably. But many privately acknowledge that the pipeline for genuinely new cultural voices has narrowed. The economics of attention now favor the familiar.

Independent and emerging artists face the sharpest paradox: they have unprecedented distribution access, but the signal-to-noise ratio has never been worse. Being technically reachable by a global audience is very different from being actually heard.

Readers and audiences are simultaneously the beneficiaries and the victims of this system. More choice, in theory. But choice architecture shaped entirely by engagement optimization may not be the same thing as genuine creative freedom.

From a non-Western cultural perspective, the stakes look different again. Algorithmic systems trained predominantly on English-language, Western content tend to surface and amplify work that fits those aesthetic norms. The content treadmill may be accelerating a kind of soft cultural homogenization—not through censorship, but through the quieter mechanics of recommendation and reward.

The Counterargument Worth Taking Seriously

It would be easy to romanticize a past that wasn't actually better. The pre-streaming era had its own gatekeepers—record labels, film studios, publishing houses—that were hardly paragons of cultural diversity. Plenty of challenging, marginal, and non-commercial work never found audiences simply because distribution was controlled by a small number of powerful intermediaries.

The internet did genuinely democratize access and discovery in meaningful ways. Niche communities of taste that couldn't sustain a local record shop can now sustain global fan bases. Genres and traditions that major labels would never have signed are thriving in the long tail of streaming platforms.

The question isn't whether the old system was better. It's whether the current system's particular failure modes—homogenization by algorithm, acceleration beyond absorption, the collapse of shared cultural reference—are ones we're actively choosing, or ones we've simply inherited by default.