Institutional Self-Assessment Tool for Ethical AI
This deliverable reports on the design, implementation, and initial deployment of the ADMIT self-assessment tool for the ethical use of Generative AI in higher education. It describes how the ethical taxonomy developed in D.5.2 was operationalised into a set of indicators, transformed into three role-specific questionnaires, and linked to tailored feedback messages. The document outlines the methodological choices made in formulating items and feedback, the technical realisation of the web-based application, and illustrative use scenarios for students, educators, and institutional leaders. It also highlights how the tool can be embedded into broader institutional strategies for responsible GenAI adoption and briefly points to its current limitations and planned extensions within the ADMIT project.
Authors
- Loukas Triantafyllopoulos (ORCID: https://orcid.org/0000-0002-7687-5642)
- Achilles Kameas (ORCID: https://orcid.org/0000-0002-1004-7860)
- Dimitris Kalles (ORCID: https://orcid.org/0000-0003-0364-5966)
- Alessandra Antonaci (ORCID: https://orcid.org/0000-0002-9157-4450)
- Vasiliki Takouli
- Andreas Panagiotopoulos
Institutions
- Hellenic Open University (GR)
- European Association of Distance Teaching Universities (NL)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-12-09
- DOI
- https://doi.org/10.5281/zenodo.17864328
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00