Wikipedia editors are quietly winning the fight against AI-generated content, and they’ve published a detailed playbook showing exactly how. Their guide, “Signs of AI Writing,” was built by WikiProject AI Cleanup over thousands of hours reviewing AI-submitted articles. It runs nearly 15,000 words. And while it was written for editors trying to catch undisclosed AI text, it’s become one of the most useful resources available for anyone trying to get AI to write more like a human. Here’s the thing: if you understand what gives AI away, you can tell your AI exactly what not to do. This article breaks down the key patterns Wikipedia identified, what they actually mean for your writing, and the exact prompts you can use to train Claude, ChatGPT, or Gemini to stop doing them. The Important Caveat First Before the list, Wikipedia is clear about one thing: no single sign proves something was AI-written. Humans use em dashes. Humans write in threes. Humans say “crucial” sometimes. The problem is cumulation. When you see three or four of these patterns stacked in the same paragraph, the probability shifts. The guide is a pattern detector, not a checklist. Keep that in mind as you read this, and as you edit your own AI-assisted drafts. The Patterns Wikipedia Identified 1. The Banned Word List (and It Changes by Model) This is the one everyone knows about. Certain words show up in AI output at rates wildly above what human writers produce. Wikipedia’s editors have tracked how the list has evolved across model generations: GPT-4 era (2023 to mid-2024): delve, intricate, tapestry, pivotal, underscore, meticulous, testament, vibrant, garner, bolstered, interplay, landscape. GPT-4o era (mid-2024 to mid-2025): pivotal, fostering, crucial, align with, emphasizing, highlighting, showcasing, enhance, enduring, vibrant. GPT-5 era (mid-2025 onward): emphasizing, enhance, highlighting, showcasing. Grok is its own category. It leans toward pseudoscientific vocabulary: causal, empirical, correlate, and continues to overuse underscore as of 2026. The practical takeaway is that “delve” becoming a meme in 2023 actually worked. OpenAI tuned it out. The patterns shift with each new model, but they never fully disappear. New tells emerge to replace old ones. Also worth noting: Wikipedia is specific that a word being overused by AI does not mean its synonyms are overused too. The problem is the exact word, in the exact pattern, at an unnatural frequency. 2. The Em Dash Situation This one has caused more arguments than almost anything else in writing circles. AI uses em dashes far more than most human writers do, and more specifically, it uses them in places where a comma or parenthesis would be more natural. A sentence like “The startup raised $5 million — its first institutional round — from a UAE-based fund” is a reasonable use of em dashes. The problem is AI drops them into nearly every other sentence as a way of adding emphasis or inserting a subordinate clause. At that frequency, it reads as mechanical rather than stylistic. Some AI companies have reportedly started suppressing em dash usage in newer models because the pattern became so widely known. But the underlying tendency remains: AI reaches for em dashes when a human writer would use simpler punctuation. The fix is straightforward. Replace em dashes with commas or parentheses wherever the clause can handle it. Keep em dashes for genuinely emphatic breaks where nothing else works as well. 3. The “Not X, But Y” Structure AI loves contrast-reframe sentences. “It’s not a product. It’s a movement.” “It’s not a setback. It’s an opportunity.” “This isn’t about speed. It’s about precision.” Human writers use this construction occasionally, because it works well for emphasis. AI uses it constantly because it produces the appearance of depth without requiring any. The Wikipedia guide calls these “negative parallelisms,” and they are among the most recognizable patterns in AI-generated content precisely because they pile up quickly within a single piece. If you find yourself reading a paragraph where two or three consecutive sentences follow this pattern, the writing almost certainly came from an AI with no editing afterward. 4. The Rule of Three AI defaults to groupings of three almost everywhere: adjectives, benefits, examples, takeaways. “Innovative, transformative, and groundbreaking.” “The platform is fast, reliable, and secure.” Lists with exactly three bullets. Paragraphs with three supporting points. This isn’t wrong on its own. The rule of three is a legitimate rhetorical device that predates AI by centuries. The problem is that AI applies it mechanically, in every paragraph, whether three items are the right number or not. Human writers sometimes give two examples. Sometimes five. The number matches the content, not a formatting preference.
