We trained the robot on broken rules — and now it corrects us with confidence.
The Traditional Rule:
Technology is neutral. Tools like AI grammar checkers, automated essay scorers, and language apps simply enforce the rules that already exist. Better tools mean better writing — right?
Why It’s Broken:
Because the "rules" AI learns are the same illogical, elitist, and outdated ones we've spent this book challenging.
Most AI language tools — from autocorrect to grammar bots like Grammarly and ChatGPT — are trained on standardized English corpora: newspapers, textbooks, academic essays, government memos. That means they're absorbing every weird, contradictory, exclusionary habit embedded in formal English.
Worse: they don’t question the rules. They enforce them with terrifying confidence.
Absurdities and Contradictions:
AI flags “ain’t” as wrong — even in dialogue.
It “corrects” contractions like “y’all” or “gonna” into lifeless formality.
It rejects African American Vernacular English (AAVE) patterns as “grammatical errors.”
It autocorrects “colour” to “color” — or vice versa — based on system settings, not user intent.
It penalizes passive voice, sentence fragments, and stylistic boldness — unless you're a famous writer, in which case it's considered “style.”
Real-World Examples:
Grammarly labels “He be working” as incorrect — despite it being a valid habitual tense in AAVE.
Chatbots offer “corrections” to Shakespearean lines, Dickensian idioms, and poetic metaphors — because they “don’t conform.”
AI grading tools reward formulaic five-paragraph structures over innovative or expressive writing.
British vs. American Variants:
AI models often default to American spelling and grammar — erasing UK variants like “organise,” “learnt,” or “the government are.”
Some tools allow toggles, but most still treat the “other” version as second-best or optional.
In international contexts, students often get “penalized” by algorithms trained on one variant of English over another.
The Reform Proposal:
Retrain AI on real, diverse, living language — not just academic corpora.
Teach machines to respect variation, not erase it.
Embed linguistic context, not just surface-level correctness.
Let users choose dialects, tones, and registers — and teach AI to respect them.
Replace “error detection” with “communication enhancement.”
How It Would Work in Practice:
Users can set “casual,” “dialect-rich,” “poetic,” or “multilingual” modes in AI writing tools.
AI explains why a phrase might be nonstandard — without suggesting it’s wrong.
Grammar checkers flag colonial leftovers and outdated rules as questionable — not mandatory.
AI helps expand expression, not police it.
Final Word: Don’t Let the Bots Become the New Pedants.
Technology can liberate language — or it can fossilize it. If we feed our machines the mistakes of our traditions, they’ll enforce them forever.
Let’s train AI not just to correct — but to understand. Not just to replicate — but to reform.
Let the future of English be smart, fair, curious — and gloriously human.