Meta AI Literacy Scale (MAILS)

In short

A self-rating questionnaire on AI skills that also asks how confident people feel about learning and solving problems with AI. Use it beside a knowledge test, not in place of one.

For whoever runs the assessment: an HR or operations lead, an internal project team, or an outside consultant.

What it measures

How people rate their own AI literacy: using and applying AI, understanding it, spotting it, judging its ethics and creating with it. It then adds something most scales leave out: how confident people are that they can learn about AI and solve problems with it, and how well they manage their own reactions to it.

Those extra parts are useful for planning training. People who doubt they can learn need a different start from people who are only short of knowledge.

How to use it

1. Use it together with a knowledge test.
2. Read the confidence scores first when you plan training.
3. Compare the self-rating with the test result. The gap shows who is overconfident and who underrates themselves.
4. Do not compare scores between language versions.

What it does not measure

• Actual knowledge. It is a self-rating. Self-ratings differ from test results, in both directions.
• Skill in a particular job.

How it was tested

• The full version was tested on 300 adults in Germany. The parts appeared as intended.
• A second paper reports three further studies and builds the 10-question short version. The results supported the scale overall. Some findings were unexpected, and the authors say the short version needs more testing.
• A Greek version was tested on two samples of early-years teachers (133 and 342 people) and showed the same nine-part structure. That study did not test whether Greek and original scores can be compared directly.

Licence and access

Mind the two licences. The short version is open for translation and adaptation. The full version may be shared unchanged for non-commercial purposes, and a translation counts as a change.

Alternatives

Other assessments with a similar job, and when to prefer each.

• What do staff know about AI? Scale of Artificial Intelligence Literacy for All (SAIL4ALL) Prefer it when you want to test what people know, not ask them. Staff, each taking a test · 56 questions in 4 parts. Each part can be used on its own Free to use and adapt Testing: Moderate AI knowledge tests and self-ratings
• What do staff know about AI, including generative AI? AI Competency Objective Scale (AICOS) Prefer it when you want a test that covers generative AI. Staff, each taking a test · A full and a short version. The number of questions is not established Free to use and adapt Testing: Moderate AI knowledge tests and self-ratings

Practices that use it

• Test AI knowledge instead of asking staff to rate their own People judge their own skills poorly. To find out what your staff know about AI, use a short knowledge test or a second opinion, not only a self-rating. Do next · Effort: medium (weeks, a few people) Evidence: Moderate People and skills · Adopt

The details

Testing

Strong The full version was tested on 300 adults in Germany and again in three further studies. A separate team tested a Greek version and found the same structure. The short version needs more testing, as its authors say.

Looks at

Person

How the answers are collected

A survey in which each person rates their own skills.

Length

34 questions; short version 10 questions

Cost

Free

Licence

Full version: CC BY-NC-ND 4.0. Short version: CC BY 4.0.You may translate and adapt the 10-question short version with credit. Translating or changing the 34-question full version needs the authors’ consent.

Languages

Published in English; tested in Germany. A Greek version exists.

By

Carolus and colleagues, 2023; short version by Koch and colleagues, 2024

Sources

1. Carolus, Koch, Straka, Latoschik and Wienrich (2023). MAILS – Meta AI literacy scale: Development and testing of an AI literacy questionnaire based on well-founded competency models and psychological change- and meta-competencies. Computers in Human Behavior: Artificial Humans. doi:10.1016/j.chbah.2023.100014
2. Koch, Carolus, Wienrich and Latoschik (2024). Meta AI literacy scale: Further validation and development of a short version. Heliyon. doi:10.1016/j.heliyon.2024.e39686
3. Papadakis, Vatou and Andreadakis (2026). Early Childhood Educators’ AI Literacy: Validation of the Meta-AI Literacy Scale in a Greek Context. Education Sciences. doi:10.3390/educsci16071117

Related studies on this site

• A review of 16 questionnaires that measure AI knowledge Lintner (2024). A systematic review of AI literacy scales. npj Science of Learning, 9, 50.
• Self-rated digital skills versus test results in 629 students Luna, Ocaña, Ortiz-Colón and Rodríguez Moreno (2026). From Self-Perception to Reality in Digital Competence: Findings from the DigComp 2.2 Framework. The Electronic Journal of e-Learning, 24(3), 137–153.