Governance of Large Language Model Applications, Risks, and Ethics in Public Administration

The rapid advancement and adoption of Large Language Models (LLMs) represent a paradigm shift with profound implications for all sectors, particularly public administration and governance. Government agencies manage massive volumes of data, policy documents, and public inquiries, making them prime candidates for the efficiency gains promised by generative AI. From automated document summarization and legal compliance to enhancing citizen service chatbots, LLMs offer unprecedented opportunities to modernize public service and improve evidence-based decision-making.

However, the integration of LLMs into the government sector introduces unique and critical challenges. Public sector use cases carry a heightened risk profile because they can affect fundamental rights, national security, and public trust. Key barriers include model hallucination, data privacy for sensitive citizen information, algorithmic bias, and the need for robust explainability and accountability.

The GLARE workshop provides a specialized venue for peer review and publication of high-impact research at the intersection of governance, large language models, applications, risks, and ethics. The workshop is dedicated to curating research that establishes public-service-tailored evaluation benchmarks and rigorous frameworks for ethical and legal governance of LLMs.

• All submitted papers will undergo a rigorous peer review process by at least two expert reviewers from the Technical Program Committee.
• Acceptance decisions will be based on technical quality, novelty, and relevance to the workshop scope.
• Accepted papers will be submitted for inclusion in IEEE Xplore, following the standard AIBThings-2026 procedure, subject to meeting IEEE Xplore's scope and quality requirements.