Aithos is not a generic AI quiz. The Literacy block is structured directly on the definition of AI literacy that the EU AI Act itself uses. Here AI literacy is defined as skills, knowledge and understanding.
We could have invented our own definition of "good at AI". Instead, we have built this block on the legal core concepts of Article 3(56) of the AI Act: skills, knowledge and understanding. This means that a result from Aithos is speaks directly to the understanding of competence that the legislation itself works from.
You can be good at AI and still have a clearly negative attitude towards it. That does not have to be a problem - but it can become a challenge if it means that new tools never really get adopted in practice. This block gives you that picture without turning it into a verdict: a candidate with low openness is not a worse candidate, just a different starting point.
Article 3(56) of the AI Act defines AI literacy as three interconnected parts. Without knowledge, no skills - without skills, no understanding. Aithos' Literacy block follows the same three-part structure, item by item.
The practical ability to use AI in a concrete work task - to formulate an instruction that gives a usable result, not just any result.
Professional insight into how the tools actually work - and where their answers can sound convincing without being so.
The ability to judge when AI is the right tool for the task - and when it clearly is not, no matter how convincing the output looks.
The openness block builds on the Big Five, the most widely used model in personality psychology. Aithos carries the thinking over to a technological context.
The Big Five describes personality as five broad traits: openness, conscientiousness, extraversion, agreeableness and emotional stability. Each trait is a spectrum, not a box.
Openness contains several facets. Aithos uses the one concerned with the willingness to try something new, and carries it over from new activities in general to new technologies and tools.
The answers have no answer key. They place the candidate on a scale in five categories, from Waits and sees to Tries first, and the report shows the category, not a score. A candidate who waits and sees is not a worse candidate.
The questions build on established research and recognised frameworks.
Long & Magerko (2020) describe AI literacy as a set of competencies that let people evaluate AI critically, collaborate with AI and use AI as a tool. The questions are also linked to the European competence framework DigComp 2.2 and to ISO/IEC 22989, 23894 and 24028.
The openness questions build on Costa & McCrae (1997), NEO-PI-R, and on research into technology readiness and adoption: Parasuraman & Colby (2015), Rogers (2003) and Venkatesh & Davis (2000).
Developed with help from, among others, Lone Bak Strandgaard, Ph.D. in Innovation and Associate Professor at Copenhagen Business School (CBS), as well as subject-matter experts from AAU and CBS and professionals from the business world.
Article 4 of the AI Act requires companies to ensure "a sufficient level" of AI literacy among employees who work with AI - but the law itself does not prescribe how that level is measured in practice.
Dansk Standard has published this specification as a translation of Article 4's requirements into concrete competence areas, aimed at organisations that use - but have not themselves developed - AI systems. Aithos' Literacy block is built on the same structure.
The DS/PAS series are guiding specifications from Dansk Standard - recommendations and guidelines, not in themselves a mandatory certification scheme.
It is important to us to be clear about what a result in Aithos actually documents - and what it does not.
Article 4 itself does not require a company to guarantee a particular competence level in each individual employee. The obligation is to make an effort "to their best extent" - not to achieve a particular test result. A high Aithos result is therefore not in itself a guarantee against sanctions under the AI Act: compliance depends on your overall efforts, including documentation, training and organisational routines. Aithos is intended as one contribution to that effort, not as proof that stands alone.
The results should be one element in an overall assessment of a candidate, not the sole basis for a hiring decision.
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