How the Readiness Check works
Deterministic JavaScript in your browser — no LLM anywhere in v1, no server, no account, no cookies. The scoring rubric below is the whole story; there is nothing hidden to game.
| Dimension | Items |
|---|---|
| Understand AI | 3 items — objective scenario MCQs |
| Use AI tools | 3 items — objective scenario MCQs |
| Judge AI output | 2 items — objective scenario MCQs |
| Build with AI | 2 items — objective scenario MCQs |
| AI self-efficacy (self-report) | 2 items — self-report, never mixed into the knowledge score |
Bands per dimension: Curious < 35% · User < 65% · Practitioner < 90% · Builder ≥ 90%. Overall = plain mean of the four knowledge dimensions. Self-efficacy is self-report and shown separately — research (01/2026) shows self-assessed AI literacy correlates badly with tested literacy, so mixing them would flatter you and lie.
Item sources & attribution
Objective items: original scenario MCQs informed by GLAT-style scenario testing and mapped to DigComp 3.0 competence areas (CC BY 4.0). Self-efficacy items: adapted from the MAILS AI self-efficacy scale (CC BY 4.0, Carolus et al.). Attribution shown on the methodology page. Every item passes editorial approval before appearing here. Physical and psychological traits are deliberately not scored: personality belongs to you — the optional PrinciplesYou link-out keeps those results in your hands.
Compliance, stated plainly
A deterministic quiz is not an AI system (Commission definition guidelines, 02/2025) — no AI Act scope in v1. Any future AI-generated feedback will be a clearly labelled opt-in (transparency duties under Art. 50 apply from 02/08/2026). GDPR: client-side only, rxed processes no personal data from this check. No emotion inference, no pressure patterns — supportive routing only.