The instinct to use AI as a first-pass editor — cleaning up grammar, restructuring paragraphs, suggesting headlines — before a human reads the draft is understandable given the speed benefits. But it introduces a systematic risk: AI editing tools optimise for surface qualities (readability, tone, grammar) while potentially missing or worsening deeper problems (accuracy, fairness, context). The human-first framework inverts this order deliberately.
Stage 1: Human Editorial Read (No AI)
The journalist or editor reads the draft as a human reader would, evaluating: Is the argument coherent? Are the sourced claims credible? Is the tone appropriate for the subject and audience? Are there any ethical concerns (privacy, fairness, conflict of interest)? This stage must be completed by a human, because AI tools systematically miss contextual and ethical issues that an experienced journalist catches immediately.
Stage 2: AI-Assisted Quality Enhancement
After the human editorial read and any substantive revisions, AI tools can be used to: improve sentence clarity, check grammar and house style, generate alternative headlines, optimise metadata and SEO signals, and flag any remaining factual claims for verification. At this stage, the AI is polishing a human-validated draft — not making substantive decisions.
Stage 3: Final Human Sign-Off
The final read is always human. The editor reviews AI suggestions, accepts or rejects each one, and takes editorial responsibility for the published version. This three-stage process typically adds 10–15 minutes compared to AI-only editing but significantly reduces the rate of embarrassing or damaging errors.