Definitions of AI literacy

Broadly speaking, the term AI literacy is used to describe "a core set of knowledge, skills, and values for interacting ethically and effectively with AI in the present" (UNESCO, 2024, p.11).

AI literacy is more precisely described through frameworks. These may support defining AI-literacy goals for students at the program and course levels.

Dutch AI Literacy in Education Framework

In 2025, an AI literacy framework for teachers and students was developed in the Netherlands within the Npuls framework. This framework is called AI-Go! (AI-Geletterdheid in het Onderwijs; Renkma et al., 2025). Other than providing a framework appropriate to higher education and the Dutch context, this framework synthesises previous scientific literature on AI literacy and complements it with an evidence-informed approach. Therefore, we suggest building on this framework in our Guidelines for the Systematic Integration of AI Literacy into UT Curricula.

The AI-Go! framework (see the figure below) conceptualises AI literacy as the combination of knowledge, skills, attitudes, and ethical awareness. Within each of these categories, specific indicators are defined.

The framework also identifies pedagogical and contextual factors that affect the development of AI literacy in educational contexts.

Figure: AI-Go! Framework

Implications of AI for Digital Competencies

The European Union's Digital Competence Framework for Citizens (DigComp 2.2) demonstrates how AI literacy is interrelated with the development of digital competencies, especially information and data literacy. This may have important implications for education as it suggests a need for updating courses related to information and data literacy to integrate relevant AI literacy dimensions.

Competency Area	Description
Browsing, searching, and filtering	Effectively querying Generative AI tools must become part of citizens’ digital skills. At the same time, citizens must be aware of the challenges in filtering AI-generated output.
Evaluating information	Citizens must become aware of potential biases in AI datasets, the risk of algorithms creating "echo chambers," as well as AI's ability to skew information, misrepresent meanings, and produce "deepfake" content.

Figure: European Union’s digital competence framework (DigiComp 2.2). Click on the image to enlarge.

DigiComp 2.2