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Proofreading with AI means asking a model to find and fix errors in text you wrote, with instructions that limit how much it may change.
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The key skill is separating grammar-only corrections from style edits and asking for a list of changes, so you can accept or reject each one and keep your own voice.
Editing has levels. Proofreading fixes spelling, grammar and punctuation. Copyediting adds consistency, clarity and style-guide rules. Line and developmental editing change sentences, structure and argument. If you ask an AI to 'improve this', it will usually do all of them at once, rewriting sentences you liked and changing your tone. So name the level you want. A grammar-only prompt might be: 'Correct only spelling, grammar and punctuation errors. Do not change word choice, sentence order or tone. List each change with the reason.' A style prompt is different: 'Suggest edits to make this clearer and more concise. Keep my informal voice. Show changes, do not silently rewrite.' Asking for tracked-change style output, such as a table of edits or strikethrough-and-bold markup, keeps you in control. You can also paste the AI's version into a new document and use Microsoft Word's Compare feature to see every difference as tracked changes. For non-native English writers, AI proofreading can be a strong learning tool if you ask for explanations, specify US or UK English, and say which features to keep. Two cautions apply. AI tends to smooth writing into a generic register, removing voice. And research by Liang and colleagues at Stanford, published in 2023, found that several AI-text detectors frequently misclassified essays by non-native English writers as AI-generated, so a detector flag is not proof that someone used AI, and detector results are weak evidence either way. Common misconceptions: that AI catches every error (it misses some and introduces others), that its changes never alter meaning (they can), and that grammar help is always allowed in school. Many instructors allow it; some do not. Check the policy.
A student asks for spelling, grammar and punctuation fixes only, returned as a table with the original phrase, the correction and a one-line reason, then fixes her essay herself.
A non-native English speaker drafting a work email asks the AI which phrases sound unnatural to a native reader and why, so he learns the pattern instead of just copying a rewrite.
A blogger asks for a style edit shown as markup, with deletions in ~~strikethrough~~ and additions in bold, and rejects the changes that make her casual tone sound corporate.
A grant writer asks the AI to check a 12-page proposal only for consistency: the same spelling of the program name, matching dates, and consistent use of 'participants' versus 'clients'.
Writing tools in word processors and browsers increasingly combine traditional grammar checking with generative suggestions, and the line between proofreading and rewriting is becoming harder to see in the interface. Features that show edits as reviewable suggestions, rather than replacing text, are the safer design and are likely to matter more in schools and workplaces with disclosure rules. Detection of AI-assisted writing remains unreliable, so policies will probably keep shifting toward process evidence, such as drafts and edit history, rather than detector scores.
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Proofreading with AI means asking a model to find and fix errors in text you wrote, with instructions that limit how much it may change. The key skill is separating grammar-only corrections from style edits and asking for a list of changes, so you can accept or reject each one and keep your own voice.
Una solicitud abierta invita a corregir, corregir y reescribir juntos. Nombrar el nivel que desea evita cambios no deseados.
Un mensaje solo gramatical limita explícitamente el alcance y prohíbe cambios en la redacción, el orden y el tono.
Los modelos regeneran el texto token por token, por lo que pueden introducirse pequeños cambios no solicitados. Comparar versiones con una diferencia los detecta.
Comparar muestra las diferencias entre su versión original y la de IA como cambios registrados que puede aceptar o rechazar.
La investigación encontró que varios detectores a menudo marcaban los ensayos de escritores no nativos como generados por IA, lo que muestra que los resultados del detector son evidencia débil.
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