Do you use AI responsibly and inclusively? — an honest two-minute self-check across 6 conditions.

Methodology

How this self-check works

What does this self-check measure?

This self-check looks at 6 conditions: Bias awareness, Human in the loop, Transparency, Accessibility, Data care and Modelling. Underneath those sit 4 axes — Awareness, Oversight, Openness and Inclusion — and where you land on each axis builds your type code, one of 16 archetypes.

How many questions are there?

Each run draws 12 questions — 2 per condition — at random from a bank of 36, then shuffles both the question order and the answer options. No two runs look quite the same; the scoring underneath is identical.

How is it scored?

Every answer carries a value from 0 to 100. Each condition's score is the plain average of your answers for that condition, and your overall score is the average of the condition scores — everything lands on the same 0–100 scale. Your overall score places you in one of 4 bands, from At risk to Exemplary. The axis scores behind your archetype are weighted averages of the same answers.

What are the lenses?

Before you start you can pick the seat you're answering from — I use AI tools, I build / configure AI, I choose / buy AI tools and I set AI direction. The lens simply tags your result, which is handy when a whole team compares notes; it never changes the questions or the scoring.

Is this a validated psychometric?

It was built by Joanne Lockwood — the Inclusive Culture Expert and founder of SEE Change Happen — from her work with organisations on inclusion and belonging. It is a self-reflection instrument, not a validated psychometric: it is designed to hold up an honest mirror and start a better conversation, not to certify you. Treat your result as a prompt for reflection, not a verdict.