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LinkedIn Built a Report Button That Pays the Person Clicking It

TL;DR: LinkedIn shipped a one-click “Seems like AI slop” flag. Over a million clicks in two weeks, and flagged content is down 40% in views. Nobody has defined the term, nobody clicking it was trained, and there’s no notification or appeal. The deeper flaw is structural: this is the first moderation button where the person clicking gains from the outcome. Suppressing a competitor’s post makes room for yours in a feed with fixed attention. Every other report button pays the reporter nothing.

Two weeks ago LinkedIn added an option to the three-dot menu on every post and comment. Seems like AI slop. One click, any member, no explanation required. Hari Srinivasan, LinkedIn’s Chief Product Officer, published the early numbers. More than a million clicks inside two weeks, and content the platform classifies as AI slop now receives about 40% fewer views than it did before the button existed. He framed it as progress, with good intent, multiple signals feeding the decision, and safeguards in place.

I write for a living, I’m against AI slop, and this button is still a terrible idea. A platform that lets anybody bury anybody with one anonymous click has handed its whole membership a weapon and labeled it quality control. The people who lose the most are the ones with the least reach to spare.

Richard van der Blom, who has spent years measuring how the LinkedIn algorithm behaves, was one of the few people in the field who didn’t cheer. His newsletter this week takes the update apart, and his objection is the right one: the platform handed a consequential judgment to a crowd with no training, no accountability, and no shared definition of the thing they’re judging.

He’s correct and I want to push the argument one step further, because there’s a defect underneath the ones already named, and it’s the reason this button will behave worse over time instead of better.

What makes the AI slop button different from other report buttons?

Think about what happens when you flag something on any platform. Spam, harassment, a fake profile, a scam DM. You click, the thing may or may not come down, and you get nothing out of it. Your position is unchanged. The only motive available to you is that the content shouldn’t be there.

Now consider this button in a feed where attention is fixed and supply isn’t.

Every post competes with every other post for the same finite pool of eyeballs. If a rival’s post gets 40% fewer views, that reach doesn’t evaporate.

It goes somewhere, and some of it goes to the people still visible. Which means the person clicking the flag has a direct material interest in the outcome, and the size of that interest scales with how well the flagged post was performing.

That’s a new thing. LinkedIn has built the first moderation control where the reporter is paid, in the only currency the platform trades in, for a successful report.

You don’t need a conspiracy for that to matter. You need ordinary human behavior under an incentive. Nothing in any system is more reliable than that. A tool that rewards its own use gets used more, and it gets used for the reward whatever the stated purpose was.

Van der Blom noticed the symptom without naming the cause. In the comments on the Chief Product Officer’s own post, a member joked that he personally accounted for close to half the million clicks. The pride is the ugly part. Somebody felt good enough about mass-flagging other people’s work to announce it in public, underneath the executive who built the feature, on a system designed to reward him for doing it.

Is LinkedIn’s AI slop button moderation or a dogpile?

I’ve written before about how a pile-on works, and the shape is always the same. First a label makes somebody acceptable to hurt, because once a person is an AI grifter or a slop merchant they stop being quite a person and the ordinary rules switch off. Then the group senses permission. Then people rush in, because there’s no cost to landing a blow and real reward for landing one.

Read that back with the new button in mind. The platform supplies the label. The permission is official. The cost is zero, since flagging is anonymous and requires no justification. And now, for the first time, the reward is measurable in reach.

The same machinery drives review bombing, which authors have been dealing with for years. A coordinated group decides a book shouldn’t do well, and a mechanism designed for honest signal becomes a weapon because the mechanism can’t tell motive from judgment.

Nothing about LinkedIn’s version prevents that. A competitor with a network can bury a post, and neither the author nor the platform will ever know it happened.

Can both LinkedIn statements be true?

LinkedIn maintains that no single click determines distribution. LinkedIn also confirms that content classified as AI slop is getting 40% fewer views. Both can be technically true and the combination still tells you nothing useful. Sure, one click may not sink a post. Ten might. Or the click may feed a classifier that then makes the call, in which case the click is still sinking the post at one remove and the disclaimer is a technicality.

What’s missing is the thing that would settle it. There’s no notification.

You’re not told your post was flagged, by how many people, or whether the reduction applied. There’s no appeal, because there’s no accusation to answer. The penalty is real and invisible, which is the worst possible design: a punishment you can’t detect, contest, or learn from.

I’d call a silent penalty cowardly design. A platform confident in its own judgment would tell the author what happened and let them answer it.

What is the button measuring?

Nobody has defined AI slop. Not the platform, not the people clicking. There’s no agreed line between AI-written, AI-assisted, and AI slop, and yet millions of members are now drawing that line in about two seconds, on instinct, with no training whatsoever.

So what fills the gap? How the writing feels: even sentence lengths, tidy transitions, a certain evenness of tone.

That’s the exact error the publishing industry is making right now with detection tools, which I wrote about when book deals started collapsing over suspicion and a score. That polish is what professional editing produces. A well-structured post from somebody who took the trouble to organize their thinking reads more like a machine than a rushed one from somebody who didn’t.

The penalty is real and invisible, which is the worst possible design: a punishment you can’t detect, contest, or learn from.

Who pays for this most? Van der Blom points it out. Non-native English speakers get hit hardest. Somebody with twenty years of real expertise who uses a tool to make that expertise legible in a second language gets flagged for the polish while the substance goes unexamined. I think that’s the ugliest consequence of the whole design. The button punishes the accommodation and lets an empty post through as long as it’s rough enough.

It also kills the learning curve. A member experimenting with these tools for the first time produces something rough, gets flagged and buried, and never finds out why or how to improve. The correction arrives as a silent penalty instead of as feedback. That’s not correction at all.

Does LinkedIn sell the tools it punishes people for using?

Yes, and the paid AI features tip it from poorly designed into indefensible. LinkedIn will rewrite your About section with AI. LinkedIn will turn your comment into a post with AI. Parts of that sit inside paid subscriptions. The platform built the features, sold them, and then handed members a button to punish content that sounds like the features.

A company can’t ship the tool, charge for the tool, and then treat the tool’s output as a violation. Pick one.

What does the spam comparison tell you?

One detail Van der Blom includes makes the priorities visible. Flagging genuine spam, a fake profile, a scam DM, takes five or six steps and days of waiting, and in his experience comes back with no violation found roughly nine times in ten. He reported a clearly fake account offering Sales Navigator seats at twenty dollars a month. LinkedIn found nothing wrong.

So the platform can ship a one-click control that cuts distribution by 40% inside a fortnight, while an obvious scam survives a multi-step report and a human review.

The AI slop button in three numbersThree headline figures from the post. The button drew more than a million clicks in its first two weeks, and content classed as AI slop gets about 40% fewer views. Meanwhile genuine spam reports, in Richard van der Blom's experience, come back with no violation found roughly nine times in ten.The AI slop button in three numbers1 million+flag clicks in the first two weeks40%fewer views for content classedas slop9 in 10spam reports returned with noviolation found
The AI slop button in three numbersThree headline figures from the post. The button drew more than a million clicks in its first two weeks, and content classed as AI slop gets about 40% fewer views. Meanwhile genuine spam reports, in Richard van der Blom's experience, come back with no violation found roughly nine times in ten.The AI slop button in three numbers1 million+flag clicks in the first two weeks40%fewer views for content classed as slop9 in 10spam reports returned with no violation found

A one-click flag cut reach by 40% in a fortnight while most multi-step spam reports found nothing wrong.

The priorities are easy to read: the thing that makes the feed look bad gets a one-click fix, and the thing that takes money from members gets a multi-step form and a shrug. A company that can build the first can build the second, so I read the gap as a choice about what counts as urgent.

What would a good version look like?

The problem the button is aimed at is real. There’s a flood of empty content on every platform, and I have put numbers to it. Being against this implementation isn’t being against the goal.

The alternatives Van der Blom proposes are better than what shipped, and they share one property: each names something checkable instead of something felt. This contains no real experience or evidence. This is misleading, exaggerated, or questionable on the facts. This is repetitive engagement bait or recycled content.

A member reading any of those has to point at something in the post. That’s a higher bar than a vibe, and a higher bar is exactly what removes the value of a spite click. I’d add three more, all aimed at the incentive problem instead of the definition problem. Make the flag cost something. A required sentence, even one nobody reads, changes who bothers. Free actions attract volume and volume is what a bad-faith clicker has to offer.

Weight flags by the flagger’s history. Somebody whose flags are usually upheld should count more than somebody who flags everything. This is solved technology and every mature moderation system uses it. Tell the author. A penalty applied in silence teaches nobody anything and can’t be appealed. If the goal is a better feed instead of a quieter one, the person who wrote the post needs to know.

Flaws in the AI slop button and the proposed fixes
Flaw Proposed fix Why it helps
No shared definition of AI slop Flag checkable things: no real experience, misleading claims, engagement bait or recycled content The flagger has to point at something in the post
Flagging costs nothing Require a written sentence with each flag Free actions attract volume, and volume is what a bad-faith clicker offers
Every flag counts the same Weight flags by the flagger’s history Someone whose flags are usually upheld should count more
The penalty is silent Tell the author when a post is penalized A silent penalty teaches nobody and can’t be appealed

My take

A report button that rewards the person clicking it is a weapon. On a feed with fixed attention, flagging a competitor’s post clears room for yours, and LinkedIn built that with no definition and no appeal. I’d make every flag cost a written sentence. Weight flags by the flagger’s track record, and tell authors when they’ve been penalized. Until LinkedIn fixes it, expect good posts to lose 40% of their views with no notice to the author.

What should you do about the AI slop button this week?

Stop editing posts for tone and start stress-testing them for substance: that’s Van der Blom’s advice, and his three questions are good enough that I’ll pass them on instead of invent worse ones. Could you defend this to somebody’s face who wanted to tear it apart, backing every claim with a number, a name, or a specific moment? Is there a sentence in here that only you could have written, one requiring your exact experience and your exact failure? Would this survive somebody flagging it out of spite, holding up under real scrutiny?

The third is the one that counts, and notice what it implies. If the accusation would feel almost fair, the problem was never the flag.

My own version of the test is shorter. Every piece carries something nobody could fake: a number, a name, a date, a client outcome, a specific afternoon. That rule is why a small consistent cadence beats a large one, since you can’t produce that many genuine specifics in a day and pretending otherwise is how people end up producing the thing the button was built for.

The button is badly built and it’ll get abused, because it pays the people abusing it. LinkedIn should be ashamed of shipping a penalty with no notice and no appeal while it sells the same AI features the penalty targets, and I’d pull the button until both of those are fixed. Until then, the only protection I know of is a post rooted in a life nobody else lived, and that’s worth building whether the button survives or not.

From the author
Sins of the Internet by Richard Lowe

Sins of the Internet
Sins of the Internet covers the choices platforms made to amplify anger over empathy. A one-click flag with no rules is the same design logic, and the book names the seven sins behind it.

Frequently Asked Questions

What is LinkedIn’s “Seems like AI slop” button?
A feedback option added to the three-dot menu on posts and comments, letting any member flag content in one click with no explanation. LinkedIn’s Chief Product Officer reported over a million clicks in the first two weeks, and content the platform classifies as AI slop now receives roughly 40% fewer views.
Does one flag reduce your LinkedIn reach?
LinkedIn says no single click determines distribution, while also confirming that flagged content sees about 40% fewer views. Both can be technically true if clicks feed a classifier that makes the decision. There’s no notification and no appeal, so an author can’t tell whether a drop in reach came from flags or from anything else.
How is the LinkedIn report button different from other reporting options?
It’s the first moderation control where the person reporting benefits from the outcome. Attention on a feed is finite, so suppressing a competitor’s post makes room for yours. Reporting spam or harassment pays the reporter nothing. That’s why those systems resist abuse better.
Who gets hurt most by AI slop flagging?
Non-native English speakers using AI to make real expertise legible, newcomers whose early attempts get buried before they learn to improve, and anybody whose writing is well-organized enough to read as polished. The flag responds to polish, and polish is what careful editing produces.
Does LinkedIn sell the AI tools it punishes people for using?
Yes. The platform offers AI rewriting for profile sections and AI conversion of comments into posts, some of it inside paid subscriptions. Members then get flagged for content that sounds like the tools LinkedIn built and sold them.
How do you protect your posts from being flagged?
Put something in every post that nobody could fake: a number, a name, a date, a client outcome, a specific afternoon from your own working life. A post rooted in experience only you have doesn’t read as slop to anybody reasonable reviewing the flag, and that’s the only defense available.

About the Author
Richard Lowe, professional ghostwriter

Richard Lowe is a professional ghostwriter and author with 113+ books authored and 54+ ghostwritten. Before writing full time he spent 33 years in enterprise technology, including 20 years as Director of Computer Operations and Technical Services at Trader Joe's. He writes nonfiction, fiction and memoir, and works with executives and experts on books that build authority.

More about Richard Lowe →

Disclaimer

The views and opinions expressed in this blog post are solely those of Richard Lowe and are based on personal experience and research. This content is for informational purposes only and should not be construed as professional legal, financial, accounting, or business advice. Always consult with qualified professionals before making important business or legal decisions. Richard Lowe is not a lawyer, accountant, or licensed professional advisor, and this content does not establish any professional relationship.

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