> ## Content Index > Fetch the complete content index at: https://www.forwardnation.com/llms.txt > Use this file to discover other available public pages before exploring further. # What is Culture When Anyone Can Make Anything? - URL: https://www.forwardnation.com/what-is-culture-when-anyone-can-make-anything/ - Published: 2026-09-03T15:33:03.000Z - Updated: 2026-09-03T16:47:35.000Z - Author: Noelle Weaver Here’s a question that has been swirling around in my mind lately. What does culture become when anyone can make anything? As AI begins to take over the production of culture, is the very definition of culture morphing into something new? What is emerging isn’t the death of culture (much like the death of TV or the death of rock n’ roll, which, despite headlines, never materialized), but perhaps a meaning that is simply narrowing. What’s starting to change? Where its meaning gets made? Who is trusted to make it? What does ‘popular actually mean in a world of infinite content? Who is exposed to ‘culture’ in a world of infinite attention, when that culture is created for the audience that AI wants it to reach? ### What is culture in the age of AI? For most of the last century, culture had a fairly settled definition: the accumulated, human-made record of a group's values, expressed through art, ritual, language, and shared reference points. For much of the last century, we tended to think about culture as the accumulated record of a group's values, expressed through art, ritual, language, and shared reference points. Implicit in that definition was an assumption that culture is something a community produces, which then reflects that community back to itself. The artifact and the meaning were bundled together. But that bundle is starting to come apart. Whether it is considered high quality or slop, the reality is that AI is now producing songs, images, video game worlds, and social media memes without any of it originating from lived experience or memory. Emerging thinking in this space suggests the old definition of culture, “the things people make,” is losing its explanatory power, because the things are increasingly ambient and machine-assisted. What remains as the distinguishing feature of culture is valuing. Not what was made, but what a group of humans collectively decides to care about, argue over, or ritualize. And consumer behavior is already validating this theory. AI-generated content in brand marketing is increasingly penalized by consumers. A March 2026 study of nearly 8,000 consumers by the CRM platform Klaviyo and the research studio Datalily found that 32% said that visible AI-generated content makes them trust a brand less, compared with just 7% who said it makes them trust a brand more. In another study, Sprout Social's Q1 2026 Pulse Survey found 56% of consumers now say they see “AI slop” often or very often in their feeds, and 88% report declining trust in social content as a result. Consumers aren't fully rejecting AI outright, but they're rejecting brands that use it as a shortcut around judgment, and they're getting sharper at spotting the difference. As we look to the future, one scenario is that the definition of culture will keep narrowing toward this idea: **culture is the filter, not the archive.** It's the mechanism a group uses to decide what synthetic or human output is actually worth paying attention to, in a world where content itself is no longer scarce. If culture is becoming less about the artifact and more about the judgment applied to it, then the brands built to “chase culture” to spot a trend early and jump on it are chasing the wrong half of the equation. **Trend-chasing was always a bet that speed plus relevance equals revenue or, at the very least, continued cultural survival.** AI breaks that equation because the thing trend-chasing teams have been built to do by identifying, imitating, and scaling what is already gaining attention is increasingly the thing AI can do fastest. AI can now spot and replicate a trend faster than any human trend-chasing team ever could. Pattern-matching to what's already popular is precisely the task AI is built for. What can't be automated is a point of view. Academics and culture writers researching algorithmic curation have been converging on this for several years, well before generative AI accelerated the conversation. Journalist Kyle Chayka, author of Filterworld: How Algorithms Flattened Culture, has argued that outsourcing cultural choices to recommendation engines has made audiences more passive and that reclaiming that agency matters. As Chayka put it in an NPR interview: *“The act of choosing a piece of culture to consume is a really powerful one.”* That single idea- that choosing is the powerful, human act vs. producing- is a useful lens for brands. A brand's job in the next decade isn't to generate more content into an infinite feed; it's to be trusted enough that its choices, curation, and point of view carry weight. ### Given all of this, will consumers look at culture differently in the future? My thinking is yes, because they're being forced to become editors themselves. When anyone, or anything, can generate a passable ad, a passable song, a passable opinion, the average stops impressing anyone. Provenance becomes a question audiences increasingly ask before investing meaning in something, rather than an assumption they make automatically. Transparency researchers are already picking up on this shift in consumer expectation: RWS's global research across 14 markets found that 62% of consumers say they would trust a brand more if it were transparent about its use of AI. Over 80% believe AI-generated material should be clearly labeled. Brands that treat disclosure as a compliance footnote rather than a trust signal are likely to fall further behind as this expectation hardens. Ten years out, the brands still standing in culture won't be the loudest participants in every trend cycle. They'll be the ones people trust to have taste, which is becoming an increasingly scarce resource in a world of increasingly cheap and rushed content. ### Will people care less about popular culture in the future? This is the harder question, because it depends on separating two things that are usually treated as one: caring about culture and sharing culture with a mass audience. The evidence suggests the second is declining while the first may not be declining at all. The idea of a cultural “monoculture” a piece of culture experienced by nearly everyone at once is widely regarded by critics as already gone, and given its pattern recognition from only what currently exists, generative AI is more likely to be accelerating an existing trend than ever starting a new one. Cultural critics started declaring the end of the American monoculture as early as the late 2010s, tying it to the rise of streaming and on-demand media. Kyle Chayka's Filterworld thesis extends that argument into the algorithmic era: as platforms increasingly generate feeds tailored to individual behavior rather than shared broadcast schedules, the communal consistency that once gave culture its impact breaks down. As AI-generated and AI-curated feeds become individualized to a single person vs filtered for them... the logic intensifies. Perhaps this isn’t a story of decline so much as it is one of relocation. Rather than culture crumbling into meaningless “slop,” some critics are framing the growing fragmentation as a legitimate new aesthetic mode closer to how niche, experimental, and subcultural scenes have always operated. They are just now accessible at a scale and speed never possible before. So what’s actually changing? People aren’t caring less about culture; they have stopped expecting it to be shared with hundreds of millions of strangers and started caring more intensely about the smaller, self-selected communities it appears in. **The most likely future might be that** **total cultural attention doesn't shrink, but it does stop being legible as a single mass phenomenon.** Instead of one Super Bowl-sized cultural moment, expect thousands of smaller, more intense ones; a niche fandom, a hyper-specific format, a subculture with its own internal references. What is declining is mass-visible caring, the kind a brand or media company used to point to and say “everyone is talking about this.” In short, the “popular” in popular culture is the thing that is most under pressure (not culture itself). ### What does this mean for brands? · **Build internal capacity to curate, not just create.** Over the next 3-5 years, the scarce skill inside a brand won't be content production; it'll be editorial judgment: knowing what to leave out, what to amplify, and what's worth the brand's name attached to it. Brands should be hiring and training for taste the way they once hired for output volume. · **Design for provenance from the start.** As "is this real/human/authorized" becomes a default question consumers ask before engaging, brands should build traceable creative processes now, documentation of who made what and how, so they can answer that question credibly instead of scrambling to prove authenticity after trust is already in question. · I**nvest in the humans and communities that can't be synthesized.** If AI compresses the cost of producing "passable" content to zero, the enduring value shifts to relationships, and creators, communities, and collaborators whose credibility comes from lived experience. Brands should treat long-term partnerships with these voices as a hedge against a content landscape trending toward sameness. · **Treat AI transparency as a trust asset.** With a majority of consumers saying disclosure would increase their trust and visible, unlabeled AI content already proven to cost trust at a 4-to-1 ratio, labeling and honesty about AI use is becoming a competitive differentiator, not just a compliance requirement. Sources & Further Reading: - Sprout Social press release, March 25, 2026 [https://sproutsocial.com/insights/press/social-media-is-now-the-top-source-for-breaking-news-new-sprout-social-research-finds](https://sproutsocial.com/insights/press/social-media-is-now-the-top-source-for-breaking-news-new-sprout-social-research-finds?ref=forwardnation.com) - NPR Here & Now, Kyle Chayka, January 17, 2024 [https://www.npr.org/2024/01/17/1224955473/social-media-algorithm-filterworld](https://www.npr.org/2024/01/17/1224955473/social-media-algorithm-filterworld?ref=forwardnation.com) - RWS, March 2025 "Unlocked 2025: Riding the AI Shockwave" [https://www.rws.com/about/news/2025/unlocked-2025-riding-the-ai-shockwave/](https://www.rws.com/about/news/2025/unlocked-2025-riding-the-ai-shockwave/?ref=forwardnation.com) - Digital Journal, Jan 21, 2026, Paul Wallis "Opinion: AI vs. Culture, or the World vs. AI Monoculture" [www.digitaljournal.com/article/opinion-ai-vs-culture-or-the-world-vs-ai-monoculture/](http://www.digitaljournal.com/article/opinion-ai-vs-culture-or-the-world-vs-ai-monoculture/?ref=forwardnation.com) - Klaviyo, 2026 "What Do Consumers Really Think About AI in 2026?" [https://www.klaviyo.com/marketing-resources/ai-consumer-trends](http://www.digitaljournal.com/article/opinion-ai-vs-culture-or-the-world-vs-ai-monoculture/?ref=forwardnation.com) - The New Yorker, Aug 25, 2026, Joshua Rothman "A.I. is Coming for Culture" [ ](http://www.digitaljournal.com/article/opinion-ai-vs-culture-or-the-world-vs-ai-monoculture/?ref=forwardnation.com)[https://www.newyorker.com/magazine/2025/09/01/ai-is-coming-for-culture](https://www.newyorker.com/magazine/2025/09/01/ai-is-coming-for-culture?ref=forwardnation.com)