I’ve been using AI chatbots since ChatGPT launched in November 2022. As a scholar with a background in both technology and linguistics, I’ve been closely observing how these AI systems generate text.
It’s an incredible achievement—one that has fundamentally changed how we interact with machines. For the first time in history, we have a technology that can produce human-like text, engage in conversations, write music and poetry, and even mimic an individual’s writing style if given enough samples.
Of course, like any transformative technology, AI has sparked its share of fear and even panic, particularly in fields that are traditionally slow to adapt to change—education being a prime example.
In the U.S., several school districts rushed to ban ChatGPT outright, fearing students would misuse it to offload cognitive tasks like writing essays and completing homework (some have reversed this ban later on).
Meanwhile, a booming industry of AI detection software emerged, with schools investing heavily in tools designed to catch AI-generated content.
But these tools quickly proved unreliable—false positives and false negatives were rampant, and news stories surfaced of students being wrongly accused of using AI to complete assignments.
The reality is, we’re in a transitional phase. AI is reshaping education, and with any major shift comes uncertainty and chaos. As a former classroom teacher, I understand the concerns. It’s not easy to navigate this change.
But as I always say, the best approach isn’t resistance—it’s adaptation. Investing in professional development and building AI literacy is no longer optional; it’s essential. If we don’t understand how this technology works, we can’t make informed decisions about how to integrate it into learning.
Now, back to AI content detection. In a previous post, I discussed how teachers—once familiar with ChatGPT’s output can recognize its tell-tale signs simply by observing the repetitive linguistic structures and syntactic patterns it tends to use. I even created a table outlining commonly overused words and phrases that can serve as a guide in identifying AI-generated text.
To be clear, I’m not against students using ChatGPT. What matters is how they use it. AI can be an incredible co-thinking partner, helping students explore ideas and refine their work.
But simply outsourcing cognitive effort—letting ChatGPT do the work and then passing it off as one’s own—is neither ethical nor pedagogically sound. That’s why I write analytical posts like this—to help educators develop a nuanced approach to AI in the classroom.
In this post, I take things a step further and explore the visual cues that reveal ChatGPT’s writing style. These subtle signs, beyond just words and phrases, can help educators detect AI-generated content more effectively.
Identifying ChatGPT-Written Text Through Its Visual Traits
Every time OpenAI rolls out a new update, I check it, test the new features, and come away with the same conclusion: GPT seems to have hit a plateau in its writing style. Whether it’s GPT-4, GPT-4o, or now GPT-4.5, the differences are barely noticeable.
The same overused phrases, predictable structures, and preferred lexicon keep showing up almost like a linguistic fingerprint we’ve all learned to recognize.
I suspect the issue lies in the training data. If we want a real breakthrough in writing quality, large language models (LLMs) need access to richer, more diverse datasets.
Imagine if major AI companies (e.g., OpenAI, Google, and Anthropic) struck deals with key academic journals and research libraries to incorporate high-quality scholarly language into their training.
That could push AI-generated writing to a new level!
Sam Altman recently hinted that an upcoming update will significantly improve creative writing. We’ll see. But so far, AI-generated text remains easy to spot.
In previous posts, I’ve talked about the linguistic patterns that give ChatGPT away, certain structures and word choices that make AI-generated text recognizable. But there’s more to it than just words. ChatGPT has visual tell-tale signs too, like its frequent use of specific icons.
Here’s a list of icons that keep showing up in ChatGPT’s responses. Next time you see them in a student’s paper, pause for a closer look, it might just be AI-generated.
: Notepad
: Lightbulb
: Target
: Magnifying glass
: Pushpin
: Books
: Bar chart
: Tools
: Rocket
: Link
: Checkmark
: Cross mark.
: Speech bubble
: Warning
: Graduation cap
: Hourglass
: Robot
Final thoughts
This isn’t meant to be a formal, rigorous study—it’s simply a heuristic I’ve put together based on my own extensive interactions with ChatGPT. I’ve likely spent more hours engaging with ChatGPT than most people reading this, given my work as both an AI researcher and a reviewer of AI tools for education.
I interact with these technologies daily, and at this point, I can usually tell within a minute—often less—whether a piece of text was AI-generated. I’ve developed a linguistic intuition for it, and trust me, AI-generated content is everywhere online.
Teachers, the linguistic and visual analysis tools I’ve shared here can help you make more informed, data-driven decisions about whether students are misusing ChatGPT. And if you’re using AI detection software, try cross-referencing its results with these tell-tale signs before jumping to conclusions.
Remember, generative AI itself isn’t the problem—it’s how it’s used that matters!
The post A Guide to Identifying ChatGPT-Written Text Through Its Visual Traits appeared first on Educators Technology.
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