AI Usage Standard (AIUS)
Deterministic AI-involvement disclosure standard for written artifacts. Six dimensions × four levels → five-tier glance-readable badge, with strict frontmatter validation. Live across this site; mirror repo for adopters.
Usable but unstable. Breaking changes expected.
- ✓Spec v1.0 — 10-article constitution
- ✓Astro components (full + mini variants)
- ✓Zod schema + build-time validation
- ✓/standards/ai-usage canonical page
- ✓GitHub mirror repo (Phase 1)
- Phase 2 — npm package (@serkanaltuntas/ai-usage-badge) — after first external adopter or 6 months; Astro/React/Vue components
- Phase 2 — JSON Schema CLI validator
- Phase 3 — localized spec pages (/standards/ai-usage/tr, /fr) — after npm package stabilizes; canonical English unchanged
What
AIUS is a versioned, deterministic standard for declaring AI involvement
in published artifacts (blog posts, project pages, papers, READMEs).
Every artifact carries an <AIUsage /> badge derived from a frontmatter
declaration of six dimensions, each at one of four levels, plus a list
of models used.
The canonical spec lives at /standards/ai-usage. Anyone may adopt it under CC-BY-4.0 with attribution.
Why
Existing options each fall short:
- CRediT covers human authorship roles only.
- ICMJE / Nature / Springer / Elsevier policies require qualitative AI disclosure in Methods sections — no glance-readable signal.
- AI Usage Cards (Wahle et al. 2023) is the closest prior art but uses boolean flags across three dimensions; AIUS extends to six dimensions × four levels with deterministic tier derivation.
- C2PA / Content Credentials focuses on image provenance, not text or code authorship.
AIUS fills the gap of “at-a-glance disclosure with rule-based determinism” for written artifacts. A reader sees the bar meter and immediately understands the AI-involvement profile without reading prose. An adopter implements the spec from the canonical text and gets identical behavior across sites.
How
Three layers, all open-source:
- Spec layer — the constitution at
/standards/ai-usageplus a machine-readableschema.json. CC-BY-4.0. - Logic layer — a pure tier-derivation function and a frozen glyph table, fully unit-tested. MIT.
- Component layer —
<AIUsage />(full bar meter) and<AIUsageMini />(one-liner) Astro components, plus Zod-validated frontmatter that fails the build on any deviation from the spec.
Phase 2 plan
After Phase 1 stabilizes (or the first external adopter shows up):
- Publish an npm package with Astro, React, and Vue components.
- Ship a CLI that validates
aifrontmatter againstschema.json. - Tighten the JSON Schema’s
allOfconstraint withdependentRequiredif validators support it.
Phase 3 plan
Once the npm package stabilizes and external adopters exist:
- Add localized variants of the canonical page (
/standards/ai-usage/tr,/standards/ai-usage/fr, etc.). The English version stays canonical; localized pages are translations, not redefinitions.
Repo
Mirror repo: github.com/serkanaltuntas/ai-usage-badge. Contains the spec text in markdown form, the JSON Schema, both license files, and a self-contained Astro reference example.