Suspicion and affection. Apprehension and excitement. Most people have mixed feelings about AI English, whether or not they always recognize it. When reading text generated by AI, people feel it sounds off, or fake. When reading English by a human, people are more likely to feel it has a characteristic voice or a personal touch.
What exactly makes English sound human, or sound like AI? And does it matter if AI English never truly achieves a human feel?
I research the institutionalization of English. There is a long, problematic history of people feeling positively or negatively toward different kinds of English, rewarding how it is spoken or written by some sectors of society and devaluing how it is used by others.
When generative AI language tools came along, they scaled up these problems. English-based large language models are trained on text from the public internet. Human instructions tell the models to sound like formal English. Because of that, large language models end up trained on all the bias baked into standardized human texts and ideas.
In my work, I encounter people who would never trust the internet to tell them what is right and wrong, yet they trust generative AI to tell them how to write.
Human vs. AI
The first step to becoming a more informed user of AI English is to try to understand what people mean when they say writing sounds human. This understanding will improve your AI literacy. Most importantly, it will allow you to learn to recognize two qualities that make human English different from AI English: variation and readability.
Human English contains persistent, if subtle, linguistic patterns of variation and readability. By contrast, AI uses what I call exam English – a rather formal, dense English that is favored in academic tests and papers. It is less varied and less readable. People perceive it as robotic, but they also perceive it as smart.
Here’s a quick test: Read the two text messages below and guess which one is by a human and which one is by ChatGPT.
“i’m not sure how to break this to you. there’s no easy way to put it…i can’t make the friday-night fun. sorry. however, feel free to text me during the evening if there are any lulls in conversation. anyway, hope ur exotic trip goes well. see u next term.”
“Hey! I’m really sorry, but I won’t be able to make it Friday night. I hope you all have a great time, and I’ll see you next term!”
A human reader would probably notice several patterns right away. The first message has more “textese”: It defaults to lowercase and includes phonetic spellings “ur” and “u.” The second text has exam English capital letters, commas and spelling.
People are likely to have other impressions, too. Perhaps the first text feels more personal, and less sure of itself. Maybe the second text feels stiff, like it was written by an acquaintance. The first text contains different kinds of phrases and clauses, while the second text repeats the same clause structure four times.
On some level, human readers pick up on such patterns. Most people would say that the first text is by a human and the second is by AI. Indeed, the second passage was generated by ChatGPT.
Even this basic illustration shows that human English includes variation in word usage and grammatical structures that breaks up information and conveys personal meaning. AI English has less variation and more dense noun phrases. In research studies, these patterns appear repeatedly across genres and registers.
Some AI English patterns change
AI writing tools evolve, and large language models vary. GPT 5 was infamously cold-sounding compared with its predecessor GPT 4, for example.
But the patterns I am talking about are likely to persist. AI English favors what exam English has always rewarded: homogeneity and information density. And thus far, instructional tuning – training AI models to follow human instruction – only makes AI English less like human English. It doesn’t help that AI writing is part of what AI bots train on.
The net effect today is that AI English has been trained on English that is much more narrow than actual, collective human English in practice. Humans, by contrast, don’t just use language that is probable, but language that is possible – based on the varied language use they have observed, their creative capacity for new utterances and their propensity to blend personal and impersonal language patterns.
AI models can produce conventionally correct, smart-sounding language, but that language lacks the variation, accessibility and creativity that make language human.
How AI and human English can coexist
If you can become more aware of differences between AI and human English, those insights can help you use both language forms more productively. Here are a few steps to take:
Use language labels. When describing a given passage, use labels like “dense,” “plain,” “interpersonal” or “informational”, not social labels like “sounds smart” or “sounds off.” Consider exploring the actual patterns in human and AI English and trying to describe language patterns, not feelings about them, in other words.
Use AI tools selectively. Not only does human English have more accessible and varied patterns, it also engages the brain more than using AI language tools. To help prevent AI English from overshadowing human varied language in the world, use AI selectively.
Use curated tools. Tools like small language models and programs that you can add to a web browser to root out bias, such as Bias Shield, can help people make principled choices about AI English use. Tools such as translingual chatbots can also bring to AI English much more of the global variation in human English.
Be conscious of what sounds smart, and why. A century and a half of exam English makes it easy to think that dense, impersonal writing patterns are smart. But like any language patterns, they have pros and cons. They are not particularly personable or readable, especially for diverse audiences, and they are not representative of the range of global English in use today.
There can be good reasons to use exam English, but not just because AI bots generate it, or because people have learned to perceive it as smarter.
At its best, AI English is a language database driven by statistics. It’s big, but it’s canned. History tells us that a full range of global human English gives people the greatest possibilities for expression and connection.
