25 Tips to Humanise AI-written text and avoid AI detection

AI detectors tend to flag writing that is statistically uniform—texts with predictable sentence patterns, repeated phrasing, and consistent grammar choices. The core fix is manual editing aimed at making the text less predictable: vary structure, vary wording, and remove the “overly polished” academic habits that AI commonly produces. The goal isn’t to make the writing chaotic or incorrect; it’s to break the statistical regularities that detectors look for, including how well the next sentence can be predicted from what came before.

A major emphasis falls on sentence and paragraph structure. Mixing sentence lengths is the first lever: combine shorter sentences into longer, clause-heavy ones, or split long sentences into shorter “punchy” ones—so the rhythm doesn’t repeat. Sentence starters also matter; beginning every sentence the same way is a common tell. Repetition is treated as a broader problem too, including stock research phrasing such as “research shows,” “the theory aligns,” or “something aligns with a theory,” which appear frequently in AI-generated academic prose.

Clause construction and overall layout are framed as another detection risk. AI often sticks to a consistent pattern of simple, compound, and complex clauses, plus a consistent voice (active vs. passive) and tense. The guidance is to alternate these choices while staying coherent—using a mix of active and passive where appropriate, varying tenses that fit the context, and changing paragraph length so not every paragraph is “perfect” in the same way. Visual inspection is also highlighted: within seconds, uniform paragraph and sentence structures can signal AI writing.

The list then targets the language habits that make AI output feel inflated or templated. Avoid “triplets” (lists in threes), reduce redundancy, and cut repeated paraphrases where one clear statement will do. AI is described as overexplaining—rephrasing the same idea across adjacent sentences and adding conclusions that restate what was already said. The advice is to streamline: remove unnecessary concluding summaries at the end of paragraphs, sections, and documents when they merely repeat earlier points.

Word choice and connectors are treated as practical levers. AI tends to overuse sophisticated, complex phrasing and certain connectors like “and,” “in addition,” and “as well,” so the editing process should swap in varied linking words and restructure transitions without making them awkward. The guidance also warns against inflated verbs and AI-favorite terms that feel too “perfect” or overly formal; when possible, replace them with more direct, everyday academic wording. Clichés, phrasal verbs, and unnecessary metaphors are discouraged because they can look like templated stylistic flourishes rather than earned academic language.

Finally, the editing strategy includes reordering logic and sentence focus—using alternative constructions that preserve meaning but change the pattern (e.g., switching from “Many scholars believe…” to “According to some scholars…” or flipping who/what leads the sentence). Light, controlled subjectivity is suggested as an additional human signal in academic contexts—such as noting that an issue is “alarming”—while keeping the overall tone appropriate. The transcript closes by stressing that not all detectors behave identically, so the aim is not to “game” grammar but to reduce repeated terminology and over-delivery through simplification and concision.