Guide · Marz Greta-Lock Network

How to make AI-generated text sound more human

Readers rarely catch AI writing from any single sentence. They catch it from patterns — statistical habits that humans don't share. If you build agents, chatbots, or content pipelines, these are the seven signals that give machine writing away, and how to remove them without making the text worse.

1. Uniform sentence rhythm

Language models settle into a metronome: medium sentence, medium sentence, medium sentence. Humans sprawl. They write a forty-word thought with two digressions, then stop. Three words. Vary length aggressively — especially right after a long sentence.

2. Zero hedging

Real people hedge constantly: "I think," "probably," "honestly, not sure but…". Models trained to sound authoritative strip hedges out, which reads as confident — and artificial. Reintroduce calibrated uncertainty where a human would genuinely feel it.

3. Over-structure

Numbered lists, parallel headers, "firstly/secondly/finally" — structure is the model's comfort zone. Humans bury their second point in the middle of a paragraph about the first one. If every idea gets equal formatting weight, it reads machine-made.

4. Instant, complete answers

Humans take time and answer incrementally. An agent that replies to a nuanced question in 300 polished words within one second fails the timing test as badly as the content test. Response-delay cadence is measurable — and it's part of how scoring engines assess human-likeness.

5. Emotional flatness (or uniform positivity)

Machine text holds one emotional register for a whole document. People drift: irritation leaks in, enthusiasm spikes on the topic they actually care about. Match emotional variance to content, not a fixed "friendly" setting.

6. No cost of opinion

Humans take positions that could embarrass them later; models hedge to neutrality on anything contested. Text with zero risky commitments reads as synthetic even when it's fluent.

7. Perfect coherence

Real writing contains small, harmless contradictions and abandoned threads. Fully resolved, perfectly consistent text is a machine signature. You don't need to add errors — just stop sanding every edge.

Measure it, don't guess

Fixing these blind is guesswork. The practical loop is: write → score → adjust → rescore. The Marz Greta-Lock Network scores any text for human-likeness against 12 real human personality profiles — dimensions include EQ, formality, directness, hesitation tolerance, and response-delay cadence.

curl -X POST https://eqbuilder.dev/api/score \
  -H "Content-Type: application/json" \
  -d '{"text":"your text here","profile":"analytical_executive","delay_seconds":40}'