Why AI Loves Binary Oppositions (and Why You Shouldn’t)

I’ve been on an AI bender lately—webinars, product pilots, and even devouring The AI-Driven Leader. Here’s the truth: AI might be the most transformational technology I’ll see in my lifetime.

(Pro tip: treat it as your thought partner, not your thought leader—that’s still your job!)

Like many who’ve been exploring AI, I’ve started noticing its “fingerprints” all over content creation.

People often joke about AI’s love affair with em dashes (a tragedy for me, since I use them constantly) and semicolons (which I’ve long avoided for fear of getting them wrong). But an even bigger giveaway?

Binary Oppositions.

Binary opposition is a writing habit where AI frames ideas as pairs of opposites, like not only X, but also Y. It’s how large language models (LLMs), such as GPT or Claude, organize data. 

LLMs don’t “understand” concepts the way humans do. Instead, they work by predicting the next word in a sequence based on probabilities derived from billions of examples of human language.

In that training data, specific linguistic patterns recur frequently, and one of the most common is the pairing of contrasting ideas. For an LLM, oppositional phrasing is a shortcut for organizing meaning. But in human writing, it often sounds forced. Humans rarely speak or write that way. 

Why do Binary Oppositions seem so off?

Think about how you’d say this to a colleague:

“We need to bring on a new freelancer—not just for immediate coverage, but to strengthen future proposals.”

Versus the far more straightforward way you’d probably say it:

“We need to bring on a new freelancer to handle current and future work.”

The second one sounds more like you talking. The first feels oddly formal and a bit robotic because it’s trying to do too much at once.

Binary oppositions can make writing feel unnecessarily complex. Instead of making ideas more transparent, they often distract the reader and break the natural flow of language.

Why It Becomes a Tell

While humans sometimes use these structures, we don’t use them everywhere. And we’re usually more selective and conversational. LLMs, in contrast, often overapply these patterns, making writing feel formulaic and uninspiring.

That’s why frequent binary oppositions in writing are a subtle “tell” that a piece of text might be AI-generated.

What do you do about it? 

If you’re using AI tools for content development, watch for these patterns and edit for simpler, more human language. As you are becoming more advanced in “training” your bots to work with you as a thought partner, you can tell them to avoid binary opposition in their responses. 

Any tool should work for you—AI included—and this trick can ensure your writing stays authentically yours. 

Simplicity often wins and sounds far more human.

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