When AI writes posts for ordinary people, not bot farms, can counting posts per day still catch them?

This explores whether moderation that watches posting volume (rate limits, flood detection, flagging accounts that post too much) can catch AI-written original posts. One caveat first: no paper in the corpus evaluates volume-based moderation head-on. What the corpus does show is that the AI-generated posts that matter most don't have to look like a flood at all.

The case against volume is mostly about who is doing the posting. Much AI content arrives through ordinary people using writing assistants, not bot farms. One study found that writers edited AI-generated paragraphs only 23% of the time, and the edits they did make left the text about 96% the same Do writers actually edit AI-generated text before publishing?. A person posting once a day with an AI draft looks like a normal user to a rate limiter. Yet the total effect is large: about 35% of newly published websites were AI-generated or AI-assisted by mid-2025 How much of the internet is AI-generated now?. The flood is spread across many ordinary accounts, not concentrated in a few.

You can't fall back on human judgment either. A review of 30 studies found that people spot AI content at roughly chance levels across text, images, and voice Can people reliably spot content made by AI?. Detection that works looks at how a post is written, not how many get posted. Cheap, transparent linguistic features caught LLM-written arguments on r/ChangeMyView with 99% accuracy. The giveaways were textbook-style argument markers and a tendency to bend toward whatever the prompt asked for Can simple linguistic features detect AI-written arguments?. In fiction, structural choices such as how characters act and how time unfolds separated AI from human stories with 93% accuracy, even after all stylistic cues were stripped out. That makes this signal hard to 'humanize' away with light edits Can AI stories be detected without analyzing writing style?.

The more surprising signal is in how other people respond. AI-written top-level posts tend to collect likes without starting conversations. Their comprehensive, confident tone earns approval but leaves little to argue with, so replies dry up Why do AI posts get likes without inviting conversation?. That shape of engagement (many likes, few replies) could be a better tell than posting rate. It also points to a harm that volume caps can't reach: the posts push aside human voices and earn visibility without building anyone's lasting reputation Does AI content displace human influencers on social media?.

That leads to the corpus's sharpest point. The real damage may not be any single bad post. It may be the loss of conversation itself, the back-and-forth that makes social media social. One note argues this erosion happens below the level that content moderation, fact-checking, or recommender tuning can reach Does AI threaten social media's conversational function?. So even a perfect volume filter would be guarding against the wrong problem. Rate limits can slow down spam, but the corpus suggests that AI-written top-level posts are better caught by writing and engagement patterns. Even then, catching them may not fix what they are doing to the platform.