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

AI literacy requires multiple interconnected competencies: The research identifies eight distinct dimensions of AI literacy—including understanding AI, using it ethically, detecting AI systems, creating AI, and psychological factors like self-efficacy and emotional regulation—suggesting that responsible AI engagement demands more than just technical knowledge.

Psychological skills are as important as technical knowledge: The study found that psychological competencies such as problem-solving ability, learning capacity, and emotion regulation are essential components of AI literacy, indicating that people need emotional and cognitive resilience to navigate AI-driven change responsibly.

AI ethics is a measurable, core competency: The questionnaire treats "AI Ethics" as a distinct, measurable facet of AI literacy alongside practical skills, validating that ethical reasoning about AI systems can and should be systematically assessed and developed in populations.

A modular approach enables flexible, context-specific assessment: The instrument's design allows different facets to be used independently depending on professional needs, meaning organizations can assess and develop AI literacy tailored to their specific contexts rather than requiring one-size-fits-all training.

Self-efficacy in AI learning matters for adoption: By measuring confidence in one's ability to learn and problem-solve with AI, the research highlights that people's belief in their capacity to engage with AI systems is a critical factor in whether they will actually develop AI literacy skills.