Content carries a legible mark of what made it — a label on the AI’s turn, a badge on the generated block, metadata in the file — so origin survives the distance between maker and reader.
Forms
Recurring forms: disclosure labels on AI turns and features, visual conventions (colour, iconography) reserved for machine output, watermarks readable by humans or software, and per-span authorship records in mixed documents.
Consequences
- origin is legible at the point of reading — labels, badges, marks, embedded metadata — so the reader's calibration has something to work from
- a mark only works while it survives the content's travels; copy, paste, export, and screenshot strip exactly the layer the mark lives in
- labelling the machine's output makes the unlabelled a claim of human origin — the default stops being neutral the moment anything is marked
Resources & references
- Shape of AI — Disclosure, Watermark, Color, Iconography
- AI UX Playground — Agent Identity, Responsibility Attribution
- AI Interaction Atlas — Data Provenance, Attribution Required
Appears in
Working on the same thing
- Seeing each other, step 1 — Sign each contribution
Calibrating reliance
- Making the output checkable, step 1 — Mark what made it
Memory and continuity
- Deciding what is kept, step 2 — Record who made each change and why
Related patterns
Complements
- Citation — who made it versus where it came from
Related to
- Collaboration — mixed human-machine authorship is where per-contribution origin matters most
- Annotation — the mark is an annotation about origin rather than content