Towards Responsible Generative AI Use in EU R&I Grants: A Self-Assessment Model and the path to a Governance Framework

This paper explores the transformative impact of Generative AI on EU Research and Innovation (R&I) grant preparation processes. It introduces a Self-Assessment Model aimed at promoting responsible AI use while paving the way for a Governance Framework. Drawing on insights from recent surveys and guidelines, the study analyzes the widespread adoption of Generative AI tools, highlighting their benefits and challenges. With 70% of surveyed stakeholders already utilizing these tools, issues such as transparency, accountability, originality, and institutional guidance are brought to the forefront. The paper seeks to address the current lack of standardized mechanisms for AI disclosure, proposing actionable strategies to safeguard research integrity without hindering innovation.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-27
DOI
https://doi.org/10.5281/zenodo.15291439
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Towards Responsible Generative AI Use in EU R&I Grants: A Self-Assessment Model and the path to a Governance Framework

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

Towards Responsible Generative AI Use in EU R&I Grants: A Self-Assessment Model and the path to a Governance Framework

article en

Abstract

This paper explores the transformative impact of Generative AI on EU Research and Innovation (R&I) grant preparation processes. It introduces a Self-Assessment Model aimed at promoting responsible AI use while paving the way for a Governance Framework. Drawing on insights from recent surveys and guidelines, the study analyzes the widespread adoption of Generative AI tools, highlighting their benefits and challenges. With 70% of surveyed stakeholders already utilizing these tools, issues such as transparency, accountability, originality, and institutional guidance are brought to the forefront. The paper seeks to address the current lack of standardized mechanisms for AI disclosure, proposing actionable strategies to safeguard research integrity without hindering innovation.

Zenodo (CERN European Organization for Nuclear Research)
Dublin City University (IE)
Industry, innovation and infrastructure
Openalex Percentile: Top 55%
Artificial Intelligence in Healthcare and Education
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