You’ve probably been there. You're reading a blog post or an email that feels just a little too polished. Maybe it’s a bit too rhythmic. Or maybe it’s just too... nice? You stop and wonder: did ChatGPT write this? It’s a question that has basically redefined how we consume information online over the last few years.
Honestly, the "vibe check" is becoming the most important skill in the digital age. Back in 2023, you could spot an AI because it talked like a high schooler trying to hit a word count by using "furthermore" every three sentences. Now? It’s harder. OpenAI, Anthropic, and Google have spent billions making their models sound like us. They’ve added "ums," they've added quirkiness, and they’ve learned to mimic specific brand voices with terrifying accuracy. But they still have tells.
If you’re looking for a simple "yes" or "no" button, I’ve got bad news. AI detectors like GPTZero or Originality.ai are in a constant arms race with the models themselves. One week they’re 99% accurate; the next, a software update makes them flag the US Constitution as AI-generated. Identifying AI isn't about running a scan; it's about looking for the "ghost in the machine."
The Logic Loop: Why AI Still Struggles with Reality
The biggest giveaway isn't the grammar. It’s the logic.
Large Language Models (LLMs) don’t actually "know" things. They predict the next most likely word in a sequence based on a massive dataset. This leads to something experts call "hallucination," but I prefer to call it "confident lying." When you're asking yourself did ChatGPT write this, look for factual assertions that feel slightly off or oddly generic. An AI will tell you a restaurant is "known for its cozy atmosphere and delicious menu," which is a sentence that says absolutely nothing. A human will tell you the floor is sticky and the waiter has a weird tattoo of a dolphin on his neck.
Specificity is the enemy of the algorithm.
The Problem with "Average" Writing
Think about what an AI is. It’s a statistical average of the entire internet. Because it’s trained on the middle of the bell curve, its output tends to gravitate toward the most "average" possible version of a thought. It avoids strong opinions unless you explicitly tell it to be edgy. It rarely uses slang correctly—it either uses none at all or uses "no cap" in a way that makes you want to crawl into a hole.
If a piece of writing feels like it was written by a committee of very polite HR managers, there’s a high chance it’s synthetic. Humans are messy. We have biases. We use sentence fragments. Like this. We get distracted.
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Spotting the Patterns: Did ChatGPT Write This?
There are certain words that AI just loves. It has "favorites" because those words appeared frequently in its training data as transitions. If you see the word "delve," "tapestry," "testament," or "vibrant" in a context that feels a bit formal, your AI alarm should be ringing.
- The Sandwich Structure: AI loves to tell you what it’s going to tell you, tell you it, and then tell you what it just told you. It’s the classic essay format we were taught in fifth grade, and the AI hasn't quite shaken it off yet.
- Perfect Balance: Look at the paragraph lengths. Are they all roughly four lines long? Is there a bulleted list with exactly five items, each starting with a bolded verb? Humans are erratic. We write a long, winding paragraph about our childhood and then follow it up with a one-sentence punchline.
- Lack of Recency: Even with "live" browsing features, AI often misses the very latest cultural nuance. It might know a news event happened, but it doesn't always understand the "meme-level" reaction to it. It lacks the "now."
The "As Of My Last Knowledge Update" Trap
While 2026 models are much better at real-time data, they still have a fundamental detachment from the physical world. If you ask a human about a local coffee shop, they’ll mention the construction noise outside. An AI will scrape a Yelp review from 2022. When you suspect did ChatGPT write this, look for a lack of sensory detail. Can the writer "smell" the room? Do they mention the weather? Do they have a personal anecdote that feels too specific to be fake?
Why Accuracy Matters (And Why AI Fails It)
Let’s talk about the "Expert" problem. People use AI to write about complex topics like medicine or law because it sounds authoritative. But as researchers like Margaret Mitchell and Timnit Gebru have pointed out in their work on "Stochastic Parrots," these models don't have a grounding in truth. They have a grounding in probability.
In 2023, a lawyer famously got in trouble for using ChatGPT to write a legal brief that cited non-existent cases. The AI didn't "lie" in its own mind; it just predicted that "Smith v. Jones" sounded like a very plausible name for a court case. If you're reading technical documentation and a "fact" seems just a bit too convenient, verify it. If the source doesn't exist, you've found your bot.
The Future of Identification
We’re entering an era of "watermarking." Companies like Google and OpenAI are working on embedding invisible signals into the text they generate. These are mathematical patterns in word choice that are invisible to us but obvious to a computer.
But even then, people will find ways to "jailbreak" or "spin" the content to hide the watermark. It’s a game of cat and mouse. So, how do you stay ahead? You look for the "soul."
The most human thing we do is make mistakes that aren't grammatical. We make mistakes of passion. We get angry. We get excited. We use sarcasm that is so layered it barely makes sense. AI can do "nice." It can do "informative." It struggle with "biting irony" or "genuine grief."
Actionable Steps for Verification
If you really need to know if a piece of text is AI-generated, don't just guess. Use a multi-pronged approach:
- Check for "AI-isms": Search the document for words like "unleash," "shaping the future," or "comprehensive." If you find more than three in a short text, be suspicious.
- Verify the Weirdest Fact: Pick the most specific, obscure claim in the article. If you can't find a primary source for it anywhere on Google, the AI probably hallucinated it to fill a gap.
- The "So What?" Test: Read the conclusion. Does it actually take a stand, or does it just summarize everything in a neutral, boring way? If it sounds like a Wikipedia summary of a debate rather than an opinion, it’s likely a bot.
- Check the Metadata: Sometimes, if you copy and paste text from a LLM, it carries over hidden formatting or strange characters. It’s rare now, but it still happens.
- Use a Probing Question: If you're talking to someone you think is a bot, ask them something nonsensical. "How do you feel about the color yellow's taste?" A human will say "What?" or give a creative answer. An AI might try to logically explain why colors don't have flavors.
Identifying AI isn't about being a Luddite. It’s about being a conscious consumer. We’re living in a world where "truth" is becoming a premium product. The more we rely on these tools, the more we need to value the messy, inconsistent, and brilliant nature of human thought.
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Next time you see a headline and think did ChatGPT write this, don't just look at the words. Look for the person behind them. If you can't find one, you probably have your answer. Use these observation techniques to audit your own reading list. Start by checking the "About" pages of the blogs you follow; if the bios are generic and the photos look like stock photography, it’s a content farm. High-quality human content will always have a paper trail of real-world experience. Verify your sources by looking for their social media presence or previous work in reputable publications. This manual "vibe check" is currently your most reliable defense against the flood of synthetic text.