Unable to determine - insufficient data
201
Samples Analyzed
46,867
Total Words
4
Languages
insufficient
Corpus Quality
Writing style compared to average AI output
Intrinsic stylometry metrics
Vocabulary Richness
TTR 0.20
Writing Rhythm
Moderate
Sentence Range
words
Signature Punctuation
Every sample follows the same tight architecture: problem statement, numbered or bulleted breakdown, call to action — the skeleton never changes regardless of language or format.
“"1) Clarity is becoming a baseline expectation... 2) Tone is getting more intentional... 3) First drafts are getting cheap..." mirrors exactly the French "Les messages sont plus nets... La barrière de la langue diminue... Le temps de réponse s'accélère"”
Across every genre — blog, social post, email, Slack — the subject matter loops back to the same singular topic: AI and workplace communication, which reflects the source material rather than any personal voice.
“Blog intro, social posts (EN/FR/ES/JA), and even the formal email context all orbit "AI reshaping communication" without exception.”
Each long-form sample plants an identical "personal story" device in roughly the same structural position — a brief vignette about a difficult message that AI helped improve — suggesting a template rather than authentic voice.
“EN: "I was about to send a message to a cross-functional group" / FR: "je devais envoyer un message délicat" / ES: "Tenía que enviar un mensaje delicado" / JA: "言いづらいフィードバックが'言える'ようになった" — four nearly identical anecdotes.”
Each sample type (formal email, casual email, social post, blog intro) appears as near-identical translations across English, French, Spanish, and Japanese, confirming these are generated variants of the same prompt rather than distinct personal writing.
“Formal emails in all four languages share identical structure: apology → revised date → mitigation actions → offer to discuss → sign-off, with no meaningful voice variation between them.”
Long-form samples consistently soften strong claims with qualifiers and balanced concessions, producing a cautious, non-committal tone that avoids any sharp or potentially controversial stance.
“"Not everyone naturally writes the same way" / "when used thoughtfully" / "la responsabilité du message sigue siendo nuestra" / "最終判断は人間" — every sample ends with a safety-valve caveat.”
Clear, accessible language
Measured, professional tone
Conversational, approachable style
Gray line = average AI output. Purple bar = their writing. The bigger the difference, the more distinctive the voice.
Voice does not shift meaningfully across languages — all four formal emails are structural clones, suggesting these were generated from a single template rather than written in a native or personally preferred register.
Casual emails are notably shorter and lighter, but the "voice" here is indistinguishable from a generic friendly-colleague template; no humor, idiosyncrasy, or personal signature appears in any language variant.
These are the longest and most developed samples, but they read as LinkedIn-optimized content with heavy bolding, numbered lists, and standardized CTAs — a format designed for algorithmic performance, not authentic personal expression.
Ironically, the blog intros are about avoiding generic AI writing, yet they are themselves structurally interchangeable across three languages — each follows the exact same three-paragraph arc: problem, cause, solution.
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