Have I been influenced, or is this actually me? Why personal taste feels hollow in the AI age

TL;DR: Recommendation algorithms and AI-generated content have flattened the messy, slow work of taste-making into fast, repeatable microtrends. That makes many people doubt whether their likes are authentic—and it forces brands to choose between chasing short-lived virality and investing in real cultural labor. A practical playbook can help leaders reclaim genuine cultural influence.

Why your likes don’t always feel like yours

You wake up humming a song you “discovered” in your feed and wonder: did I choose this, or did the feed choose me? That tug—where a preference feels less like personal history and more like handed-down content—isn’t just social anxiety. It’s the visible symptom of algorithmic personalization at scale.

Recommendation engines on social platforms, streaming services, and e-commerce sites are built to reduce friction and keep you engaged. They optimize for watchtime, streams, clicks and conversions—metrics that reward content which is instantly recognizable, broadly palatable, and easy to consume. Slow, complex, or context-dependent work gets deprioritized because it breaks the scroll.

“If you dismiss taste as trivial, you’re dismissing a core part of being human.”

How algorithms and marketing manufacture taste

Algorithms are not neutral curators. They are machines optimizing specific business goals. That creates two predictable outcomes: the ecology of culture flattens toward the easily digestible, and savvy marketers learn to game the mechanics.

Marketing firms run coordinated posting strategies and trend-simulation campaigns designed to trick recommendation systems into amplifying content. Journalists have documented tactics like “clipping”—covert ad campaigns disguised as organic posts—that seed feeds and create the appearance of grassroots momentum. Bands, shows, and influencers can be catapulted into the mainstream not by natural word-of-mouth, but by orchestrated amplification.

Kyle Chayka sums it up plainly: algorithms favor content that’s easy to consume and non‑disruptive, which pushes subtler or more challenging work below the surface. Ione Gamble has argued that people are increasingly being told what to like rather than discovering it for themselves; the conditions for independent taste—time, slow discovery, local communities—have narrowed.

When AI multiplies sameness

Generative AI accelerates both scale and sameness. Industry estimates suggest a large share of images circulating online are now AI-generated; some reporting places that figure high in the tens of percentage points. Platforms have struggled to police the result: Spotify, for example, reported removing roughly 75 million suspected AI or spam tracks in a recent year.

Cheap, rapid content production makes novelty burn out faster. Instead of a few voices experimenting slowly and influencing peers, millions of low-effort, formulaic assets flood feeds and create microtrends that bloom and wither in days. That churn dilutes the perceived authenticity of any given cultural moment, because much of the activity around it may be paid, coordinated, or machine-made.

At the same time, public engagement with social platforms has shown signs of friction. Time spent on social platforms peaked around 2022, and an Ofcom survey reported a double-digit drop in people posting year-over-year—evidence of what many call algorithm fatigue: less sharing, more passive consumption, rising skepticism about what’s genuine.

Where authenticity survives (and how businesses win)

Not all discovery is dead. Niches, curators, and offline networks still shape taste—and those channels are where long-term cultural value is built. Platforms and projects that foreground human curation, context, and editorial judgment are gaining traction: Letterboxd, specialist newsletters, small zines, and algorithm-free social sites show that people still seek meaningful recommendation systems that reward expertise, not just engagement spikes.

Curators monetize authenticity by selling time and trust. Newsletters like Blackbird Spyplane—run by founders who treat curation as editorial labor—are examples of how slow, trustworthy recommendation can become a business model. Small editorial projects and local scenes produce cultural capital that is hard to simulate with paid amplification.

Some tech leaders publicly argue taste will become a crucial human differentiator as AI agents automate routine work. That claim has merit—but it’s also performative. When companies buy their way into cultural events, drop merch to signal “cool,” or hire PR to manufacture trend affiliation, it rings hollow unless backed by sustained cultural labor.

“People are being told what to like rather than discovering it for themselves; there’s less space and time now to cultivate independent taste.”
— Ione Gamble

Two short case studies

Manufactured rise: A handful of coordinated accounts and paid placements can make an artist feel ubiquitous overnight. Reporting on several music campaigns has shown how labels and firms seed short clips across networks to trigger algorithmic picks and playlisting. The result looks like organic popularity but is often engineered.

Curator-led traction: A boutique newsletter or local venue that nurtures a scene builds slower but stickier engagement. Subscribers and attendees are more likely to return, buy tickets, and recommend to friends—metrics that matter for brand loyalty and lifetime value beyond one-off viral spikes.

Practical playbook for leaders

If you lead marketing, product or corporate strategy, treating taste as a resource requires operational changes. The following checklist is a starter playbook you can implement this quarter.

• Run a “taste audit.” Map where your cultural signals originate—paid amplification, algorithmic reach, curator partnerships, or offline activations. Measure depth (repeat engagement, sentiment) not just reach.
• Pay for editorial relationships, not one-off influencer blasts. Long-term partnerships with niche curators and newsletters convert authenticity into durable attention. Treat curation as labor worth compensating on retainer.
• Introduce creative constraints. Limit the palette, timing or format of campaigns (capsule drops, regional-only releases). Constraints force originality and reduce the temptation to optimize purely for algorithmic heuristics.
• Prioritize lived experiences. Sponsor local events, pop-ups, and physical media releases. Lived cultural experiences generate stories and social proof that algorithms can’t fully fake.
• Be transparent about AI and paid amplification. Label AI-generated content and disclose paid partnerships. Transparency builds trust and differentiates brands as platforms grow more opaque.
• Hybridize algorithmic reach with curator oversight. Use AI for distribution efficiency, but let human editors set cultural direction and standards. This reduces the risk of boxed, bland output dominating your brand voice.

Starter three-step “taste audit”

1. Inventory signals: List your top 20 cultural touchpoints (channels, influencers, playlists). Note how each is acquired and whether activity is organic or paid.
2. Measure depth: Track return interactions, referral sources and sentiment over six months rather than one-week virality windows.
3. Reallocate budget: Shift a portion of short-term performance spend (e.g., programmatic) to curator partnerships and events. Test for retention uplift.

Pushback and trade-offs

There are counterarguments worth acknowledging. Recommendation algorithms do enable niche discovery—subreddits, specialist podcasts, and micro-communities can reach global audiences precisely because algorithms surface them. And AI can help scale genuinely creative workflows when used as an assistant rather than a replacement.

But the trade-off is clear: optimization for scale tends to favor what works for the average user, not the enthusiast. If your strategy relies only on algorithmic reach, you’ll win fast attention and lose durable loyalty. Taste that matters is slower, messy, and expensive—but it compounds.

“Algorithms favor content that is easy to consume and non‑disruptive, which leads to the most accessible but least meaningful culture rising to the surface.”
— Kyle Chayka

Where to start this quarter

Pick one initiative you can launch in 90 days:

• Sign a three-month paid editorial partnership with a newsletter or local venue and measure subscriber LTV.
• Run a constraint-driven campaign (limited release, region-first) and compare retention against a standard paid campaign.
• Label any AI-generated creative across owned channels, and publish a short explainer about why you made that choice.

Small, deliberate moves recalibrate how your brand participates in culture. They also hedge against the risks of manufactured virality and algorithm fatigue.

Key takeaways

• Algorithmic personalization and AI-generated content shape modern taste. Feeds favor repeatable, low-friction content, producing fast microtrends and sameness.
• Much online enthusiasm can be engineered. Coordinated campaigns and stealth amplification can mimic grassroots momentum.
• Authenticity is a strategic advantage. Curator-led models, local experiences and editorial relationships buy durable cultural capital.
• For leaders: measure depth, not only reach. Invest in slow cultural labor—events, curators, transparency—and treat taste as a long-term asset.

Question: How much of my taste is actually my own?

A significant slice is shaped by feeds and recommender systems, but your personal history, context and deliberate offline discovery still matter. Intention recovers individuality.

Question: Can taste survive in an era of AI-generated content?

Yes—taste survives where people have time, community and constraints to develop preferences. AI makes cheap content abundant, but it cannot fully reproduce the texture of lived experience.

Question: Should companies chase algorithmic virality or cultivate curatorship?

Short-term visibility favors algorithmic stunts; long-term brand equity favors authentic curation, transparent practices and investment in community.

If you lead marketing or product, perform a taste audit this quarter. Taste is under siege—but it is also an opportunity: companies that fund real cultural labor will win the long game.