An Analysis of AI Literacy Scales: Which Ones Are Suitable for Public Administration?

Allgemeines

Art der Publikation: Conference Paper

Veröffentlicht auf / in: Informatik 2026

Jahr: In Press

Verlag (Publisher): Gesellschaft für Informatik e.V.

Autoren

Xiao Xiao Wu

Nico Gießmann

Tim Schrills

Anna-Katharina Dhungel

Moreen Heine

Zusammenfassung

The growing adoption of artificial intelligence (AI) in public administration necessitates reliable methods for assessing AI literacy among civil servants. This study presents an analysis of existing AI literacy scales to evaluate their suitability for public administration contexts. Based on a scoping review, 16 validated scales were identified and analyzed in this study. The scales were mapped to AI literacy requirements derived from the AI4Gov canvas. The results show that most scales focus on core AI literacy, self-reports, multiple-choice knowledge tests and emerging generative AI literacy assessments, but largely neglect applied, governance-related, and context-specific skills. Overall, the findings suggest that existing AI literacy scales provide a useful foundation for assessing AI literacy among civil servants, but need to be extended to capture the governance-oriented, organizational, and context-specific competencies required for responsible AI adoption in public administration.

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