AI Slop Is Eating the Internet: The 2026 Guide to Spotting It, Avoiding It, and Not Publishing It

AI Slop Is Eating the Internet: The 2026 Guide to Spotting It, Avoiding It, and Not Publishing It

Published on 2026-02-09

Last updated on 2026-02-09

By Jesus Iniesta

Updated: February 9, 2026

Your feed feels off lately, doesn't it? Same faces, same voice, same "10 surprising things" energy, same glassy-eyed certainty—and somehow less useful than spam from 2007.

There's a name for that feeling: AI slop.

Not "AI content." Not "synthetic media." Not "generative AI." Slop. The word stuck because we needed a short, sharp label for a very specific kind of internet pollution: cheap-to-make, easy-to-scale, low-to-zero value content that clogs discovery systems and burns everyone's time.

Let's define it cleanly, explain why people are suddenly searching for it, and then get to the practical part: how to spot it, how to avoid it, and how not to become the person shipping it.

Quick definition: what "AI slop" means

AI slop = low-quality, low-effort AI-generated content published at scale to farm attention or money.

It's the spam playbook, but with fluent grammar and an infinite content budget. (Simon Willison's Weblog)

This isn't about judging AI tools themselves—it's about the quality and intent behind publishing unreviewed output (or "barely reviewed" output) when volume is the strategy.

The term has gone mainstream—major dictionaries are now tracking it:

  • Merriam‑Webster picked "slop" as its 2025 Word of the Year and defines it as low-quality digital content produced in quantity, usually by AI. (Merriam-Webster)
  • The American Dialect Society also selected "slop" as 2025 Word of the Year, explicitly calling out the AI context and how "slop" is now a productive building block for more terms. (American Dialect Society)
  • Australia's Macquarie Dictionary chose "AI slop" as its 2025 Word of the Year, framing it as a real societal shift in how people navigate information. (The Guardian)

This isn't just a niche insult on tech Twitter anymore. It's a cultural artifact.

Table of contents

How we know what we know (without becoming the slop)

Intellectual honesty demands we separate verified facts from informed guesses. Here's the breakdown.

1) Verified facts (supported by sources)

  • "Slop" is now formally defined by Merriam‑Webster as low-quality digital content produced in quantity, usually by AI. (Merriam-Webster)
  • The American Dialect Society selected "slop" as Word of the Year for 2025 and ties the term to high-volume, low-value AI content. (American Dialect Society)
  • Simon Willison publicly pushed "slop" as the analog to "spam" for unwanted AI-generated content in May 2024. (Simon Willison's Weblog)
  • A Guardian report (Dec 2025) cites Kapwing research: over 20% of early recommendations on a fresh YouTube account were classified as AI slop; it also reports large-scale channel metrics and revenue estimates. (The Guardian)
  • Google's Search documentation says mass-generating pages primarily to manipulate rankings is "scaled content abuse," regardless of whether it's made by AI; Google also publishes specific guidance for using generative AI content responsibly. (Google for Developers)

2) Widely accepted expert consensus (broadly agreed, not tied to one citation)

  • Lower production costs plus algorithmic distribution tend to increase content volume (and therefore incentives for low-quality volume strategies).
  • Humans are bad at auditing everything they scroll past; attention is a scarce resource; platforms optimize for engagement.

3) Informed reasoning (based on facts + incentives)

  • Search spikes for "AI slop" correlate with mainstream coverage and dictionary announcements because that's when non‑specialists need a term to describe what they're experiencing. The timing lines up with "Word of the Year" coverage and broader reporting. (AP News)
  • Platform monetization (ads, creator payouts) makes slop a rational strategy for some actors, even if it degrades the ecosystem. (The Guardian)

4) Speculation (plausible, but uncertain)

  • Slop will increasingly be personalized ("made for you") and harder to detect with surface-level cues as generation quality improves.
  • Some platforms may pivot to stronger provenance requirements once ad buyers and regulators apply pressure.

I'll label speculative sections as we go.

What AI slop is not

The fastest way to argue about slop badly is to define it as "anything made with AI."

That's not how the term is being used in mainstream definitions or in the reporting that popularized it. The point isn't the tool—it's the outcome.

AI-assisted work can be high quality

If someone uses an LLM to outline or rewrite for clarity, then adds original reporting, data, experiments, citations, and editorial judgment—that's not slop. That's a workflow.

Human-made content can also be slop

Humans invented low-effort junk long before diffusion models. AI just made it cheap enough to industrialize.

The core markers of slop

  • Volume is the strategy
  • Verification is absent
  • Originality is missing
  • The user is the product (attention, ad views, affiliate clicks)

That's why early advocates explicitly compared "slop" to "spam." (Simon Willison's Weblog)

Where AI slop shows up

Those weird Facebook images? They're just one tentacle of something much bigger.

1) Search results and "how-to" pages

This is the classic content farm: pages that look like answers but don't actually solve anything. The Guardian's "zombie internet" framing captures this perfectly—webpages that imitate usefulness to attract clicks and ad revenue. (The Guardian)

2) Social feeds: images, memes, and "engagement bait"

Washington Post described a flood of bizarre AI images on Facebook, explicitly using "slop" as the term of art for this image-spam genre. (The Washington Post)

3) Short-form video: the new industrial scale

Here's where it gets weird. Reporting describes a fast-growing business of low-effort AI video made to trigger clicks and watch time on TikTok/Instagram/YouTube. (The Washington Post)

The Guardian/Kapwing numbers (as reported) suggest the recommendation engine can surface a lot of this to brand-new accounts. (The Guardian)

4) Books and "guides" (including dangerous ones)

When slop is merely boring, it's annoying. When it's wrong in areas like health, safety, or legal guidance, it becomes a hazard. Coverage has highlighted AI-generated books and guides that may be unreviewed and can contain dangerous misinformation—for example, foraging and mushroom identification advice. (The Guardian)

5) Comments, reviews, and "community"

The most depressing version: synthetic people cheering on synthetic content. "Zombie internet" is partly about that blur—bots, humans, and accounts that behave like bots mixing into one gray soup. (The Guardian)

Why people are searching for "AI slop" now

This isn't random. Search behavior usually spikes when two things happen:

  1. People experience something ("why is my feed full of garbage?")
  2. They see a label ("oh, this is called AI slop?")

Several real-world triggers line up:

Trigger A: "Slop" went mainstream via Word-of-the-Year coverage

When Merriam‑Webster names a Word of the Year, people look it up. That's part of the mechanism: it's tied to public attention and lookup trends. (Merriam-Webster)

When the American Dialect Society picks the same word, it amplifies the signal across media and linguistics coverage. (American Dialect Society)

Macquarie's "AI slop" selection did the same in Australia. (The Guardian)

What the data suggests: those announcements don't just reflect interest; they create it, because they give people a handle for a messy experience.

Trigger B: The "slop era" got a narrative people could repeat

Journalists started treating slop as a real phenomenon with economics behind it (not just "lol AI is weird"). Max Read's reporting framed it as an underground economy clogging the web. (New York Magazine)

Once a phenomenon becomes a story, people start searching it as a concept.

Trigger C: Platforms started shipping more AI into the core experience

Google rolling out AI-generated summaries ("AI Overviews") put "AI-generated content" in the front door of the internet for many people. (The Guardian)

Google's AI search features have also expanded massively by audience size, per reporting. (The Verge)

And Google has even tested an "AI-only" search mode, per Reuters. (Reuters)

That doesn't automatically create slop, but it changes incentives and primes people to notice AI-ish output everywhere.

Trigger D: Video slop became hard to ignore

When a mainstream outlet reports that a fresh YouTube account sees ~20% slop in early recommendations (as classified by a study), people will search the term. (The Guardian)

Not because they love the concept—because they're trying to explain what's happening.

The economics: why AI slop exists even when everyone hates it

Skip the philosophy—this is pure economics.

The slop equation

  • Cost to produce content → approaches zero (text, images, voice, now video)
  • Cost to distribute content → handled by platforms (recommendation engines)
  • Revenue per view/click → small but real
  • Scale → unlimited

If you can produce 10,000 pieces of content for the cost of 10, and a tiny fraction hit the algorithm, you profit. The Guardian's early "slop" framing explicitly connects slop to advertising revenue and search attention. (The Guardian)

Reporting on AI video slop describes creators using cheap tools to generate high-volume content and monetize through platform systems. (The Washington Post)

Why it gets worse on platforms built for A/B testing

Platforms like YouTube and Meta are essentially giant feedback loops:

  1. Publish a batch
  2. See what sticks
  3. Clone the pattern
  4. Scale the output

The Guardian quotes this "A/B testing machine" logic when describing how creators scale what works. (The Guardian)

What the data suggests: slop thrives not because it's good, but because it's adaptable. The content is disposable; the distribution pattern is the product.

"Is the internet really half slop now?" The data is messy, but trends are clear

People toss around numbers like confetti. Let's pin down what's actually been published.

Graphite published analysis claiming that by November 2024, AI-generated articles being published on the web surpassed human-written articles, and that about 39% of articles published were AI-generated after 12 months. (Graphite)

Axios reported on Graphite's charting, describing a decline in the share of human-created articles and a rise in AI-generated articles over time. (Axios)

Important nuance: Graphite also reported that search rankings and LLM citations skew heavily toward human-written articles—for example, their report says most pages ranking in Google Search are still human-written. (Graphite)

So two things can be true at once:

  • The web can be flooded with AI-generated pages.
  • Discovery systems may still preferentially surface human-made material (at least for now).

That "at least for now" is doing a lot of work.

Why AI slop works on humans

Here's the uncomfortable truth: slop isn't always "obviously bad" at a glance. It's often just good enough.

Slop optimizes for "frictionless consumption"

It tends to be:

  • Simple, familiar, low cognitive load
  • Emotionally tuned ("heartwarming," "outrage," "shocking")
  • Formatted like something you've learned to trust (guides, explainers, "news")

Widely accepted consensus: humans use heuristics (mental shortcuts) online because auditing everything is impossible. Slop exploits that.

What the evidence suggests: a lot of slop is "optimized for the feed," not "optimized for truth."

The harms: what AI slop breaks (beyond your vibe)

1) It wastes attention at scale

Spam didn't just annoy people; it forced the creation of filters, policies, and defensive habits. The "slop as spam" analogy is explicitly part of the term's rise. (Simon Willison's Weblog)

2) It increases the risk of confident misinformation

The "Ottawa food bank" travel-guide example reported by The Guardian is a perfect slop failure mode: confident nonsense presented as helpful information. (The Guardian)

3) It can create real safety risks

Unreviewed guides on foraging, medicine, finance, or legal topics are not "harmless content." Even if only a small fraction is dangerous, scale makes it matter. Coverage has highlighted this concern in the context of AI-generated books and guides. (The Guardian)

4) It degrades search and discovery

Google's Search team has explicitly updated spam policies to target scaled content abuse, and their guidance warns that mass-generating pages without adding value can violate spam policies. (Google for Developers)

That's basically a formal way of saying: "Stop flooding the index with slop."

5) It creates a trust crisis (and then monetizes the crisis)

Once you assume anything could be synthetic, you start distrusting everything. That's socially expensive.

Looking ahead: long-term, "trust infrastructure" (provenance, verification, editorial reputation) becomes a competitive advantage again—because the alternative is informational anarchy.

How to spot AI slop fast

No magic detector required. Start with a checklist.

A practical "slop sniff test" for text

Red flags (one isn't proof; clusters matter):

  • No sources, no links, no citations for factual claims
  • Generic structure: intro → 10 bullet points → conclusion → FAQ, all saying nothing
  • Overconfident tone with vague evidence ("studies show" with no studies)
  • Repetition of phrases and patterns ("in today's fast-paced world…")
  • No firsthand details (no measurements, no photos, no specific experiences, no constraints)
  • Weird mismatches: the page ranks for a niche query but reads like it was written for everyone

A practical "slop sniff test" for images

  • Inconsistent text rendering inside images (still common, though improving)
  • Small anatomical weirdness (hands, teeth, jewelry continuity)
  • "Too-perfect" lighting plus generic composition, with no contextual mess
  • The image exists mainly to trigger engagement ("share if you agree")

This overlaps with what mainstream coverage described as the weird-but-real flood of AI images on Facebook. (The Washington Post)

A practical "slop sniff test" for video

  • The voice has the same cadence as every other AI voice
  • Captions are perfect but emotionally flat
  • The topic is optimized for compulsive viewing ("pressure cooker explosions," "endless catastrophes," "cute animals doing surreal things")
  • The channel output is unbelievably high-frequency and templated

The Guardian's Kapwing-described examples (absurd animals, disaster shorts, etc.) match this pattern. (The Guardian)

Account-level signals

  • Hundreds of uploads in a short timeframe
  • Recycled thumbnails/titles with tiny variations
  • A comment section full of generic praise that reads like more bots

What to do as a reader: defending your attention without becoming a bunker hermit

You don't need to quit the internet. You need friction.

1) Reward sources, not vibes

If a claim matters, look for:

  • Named author
  • Publication standards
  • Citations
  • A date
  • A correction policy (seriously)

2) Cross-check with at least one independent source

Slop collapses under cross-checking because it's rarely anchored to primary evidence.

3) Prefer "information with constraints"

A weirdly effective rule:

  • The more a piece contains numbers, dates, methods, and boundaries, the less likely it is to be slop.
  • The more it contains adjectives and vibes, the more suspicious you should be.

This aligns with one of the best antidotes I've seen stated plainly: introduce "friction with data" by anchoring content in verifiable sources and open data. (Datos.gob.es)

4) Curate inputs

  • Use RSS feeds for sources you trust.
  • Use newsletters from actual humans.
  • Use "following" rather than "For You" where possible.

What the evidence suggests: slop is an algorithm problem; opt out of maximum-algorithm settings and you reduce exposure.

What to do as a creator or publisher: how not to ship slop

This is the part most SEO "AI content" guides dodge because it's work: you need an editorial system.

The anti-slop publishing pipeline

  1. Start with a real question (not a keyword)
  2. Gather primary sources (docs, datasets, interviews, experiments)
  3. Use AI for structure and drafting (fine)
  4. Add original value
    • Data analysis
    • Screenshots
    • Comparisons
    • Field testing
    • Expert review
  5. Fact-check
    • Every number
    • Every quote
    • Every medical/legal claim (or don't publish it)
  6. Cite sources and show your work
  7. Ship fewer pages, better

If you're publishing thousands of pages because "scale," you're not building a site. You're manufacturing a landfill.

AI slop and SEO: what Google actually says (not what SEO Twitter says)

Google has been unusually direct here, and you should read the primary sources.

Google's position in one sentence

Automation is fine if it produces helpful content; automation is spam if it's primarily for manipulating rankings. (Google for Developers)

The policy that slop most closely maps to: "scaled content abuse"

Google defines scaled content abuse as generating many pages primarily to manipulate rankings and not help users—and it applies regardless of how the content is created. (Google for Developers)

Google's guidance on generative AI content

Google explicitly warns that using generative AI to create many pages without adding value may violate spam policies, and it points site owners to Search Essentials. (Google for Developers)

So if your "strategy" is:

  • Pick 5,000 keywords
  • Generate 5,000 pages
  • Add ads
  • Pray

That's not "AI SEO." That's "scaled content abuse with extra steps." (Google for Developers)

Can we fix the slop problem?

"Fix" is a strong word. But we can change incentives.

1) Platforms can stop paying for junk

If creator payouts reward watch time with no quality signals, slop will flourish. The Guardian reporting on the slop economy makes clear that monetization and distribution are central drivers. (The Guardian)

2) Provenance and watermarking can help (but won't solve it alone)

Watermarking/provenance systems can answer: "Did this come from model X?"

They often cannot answer: "Is this true?" or "Is this good?"

Widely accepted consensus: provenance helps with attribution, not truth. You still need verification.

3) Search engines are already trying to reduce incentives

Google's spam policy updates and scaled content abuse language are the institutional response to "the index is being flooded." (Google for Developers)

4) "Friction" is the real antidote

The best countermeasure is boring:

  • Data
  • Sources
  • Constraints
  • Review
  • Accountability

Which is exactly what slop tries to avoid.

The next phase: what happens after the slop wave

Here's the honest bit: nobody has perfect visibility. But we can reason through it.

Based on the evidence

  • If slop gets punished by ranking systems and monetization systems, creators will either (a) stop, or (b) evolve into higher-effort deception.
  • If slop keeps getting rewarded, it will expand into every content shape that can be cheaply generated.

Looking ahead (speculation)

  • We'll see more "stealth slop": content that looks carefully made but is still unverified and mass-produced.
  • We'll see more "licensed slop": AI-generated summaries and remixes that sit on top of licensed publisher content, shifting value away from original work.

Google's increasing integration of AI into search (Overviews, experiments like AI Mode) is a major variable here because it changes the surface area where synthetic content appears. (Reuters)

FAQ: Common Questions About AI Slop

Is AI slop the same thing as misinformation?

No. AI slop can be true and still be slop (because it's low-value filler). Misinformation is about falsehood; slop is about low-quality, mass-produced output. They overlap when slop is wrong—which happens a lot because verification is expensive. (The Guardian)

Is all AI-generated content slop?

No. Slop is a quality plus intent category, not a tool category. Merriam‑Webster's framing is about low quality produced in quantity. (Merriam-Webster)

Why call it "slop"?

Because it's vivid and accurate: something shoveled out in bulk, meant for consumption, not crafted for meaning. The term gained traction explicitly as the "spam" analog for unwanted AI-generated material. (Simon Willison's Weblog)

Why did searches spike in late 2025 and early 2026?

Verified drivers include Word-of-the-Year coverage and mainstream reporting, which creates lookup spikes and broader curiosity. (AP News)

Is AI slop actually taking over YouTube?

A Guardian report cites a Kapwing study claiming that over 20% of the first 500 recommendations to a new account were AI slop (as defined by their research), and it reports large channel-level totals. That's not "all of YouTube," but it's significant exposure in early recommendations. (The Guardian)

Does Google penalize AI content?

Google's documentation doesn't say "AI = penalty." It says scaled, low-value content made primarily to manipulate rankings violates spam policies (scaled content abuse), and it explicitly warns against mass-generating pages without adding value. (Google for Developers)

Can AI slop be copyrighted?

Copyright depends on jurisdiction and specifics. Practically, platforms and publishers care more about rights to inputs and commercial use policies than whether a piece of slop is "protected." (This is legal territory; treat this as general info, not legal advice.)

How do I protect kids from AI slop?

Use platform-level controls, supervised accounts, and curated subscriptions. The bigger issue is that slop often targets children with bright, compulsive, low-context content, as described in reporting about AI slop channels. (The Guardian)

Are there reliable AI detectors?

Detectors can help, but they're not definitive. Provenance signals ("created by model X") are generally more robust than "this looks AI-ish," and even provenance doesn't tell you whether something is accurate.

Is slop just a phase?

Maybe. Spam didn't go away; it got filtered. Slop might follow the same path: less visible in mainstream channels, more concentrated in shady corners, and constantly evolving. (Based on the spam analogy used by early proponents.) (Simon Willison's Weblog)

What's the simplest rule to avoid publishing slop?

Don't publish anything you wouldn't bet your reputation on. Add sources. Add constraints. Add review. If that sounds expensive, that's the point.

Bottom line

AI slop isn't "AI is bad."

AI slop is what happens when creating content becomes cheaper than quality control.

The web already fought one war against low-effort, high-volume garbage. We called it spam. We built filters, policies, reputations, and workflows around it.

Now we're doing it again—except the garbage can write in complete sentences.

Further reading (recent coverage and primary sources):

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