Which open research outputs published since 2021 can help a public-sector innovation officer scope responsible AI in public administration, and which records are sufficiently documented for follow-up?
released
8records inspected
6follow-up fields complete
144source-bound claims
publication2025-09-16CC BY
rejected
Artificial Intelligence and the Future of Public Administration: Navigating Ethics, Efficiency, and Democratic Accountability in Algorithmic Governance
No description in the Graph record.
Human review: Title is relevant, but the OpenAIRE record has no description, so its content cannot be assessed from the available evidence.
Public portrait of the uses of AI in the Quebec public administration
Dans une perspective de transparence et pour assurer la cohérence de l'action gouvernementale en matière d'intelligence artificielle (IA), le ministre de la Cybersécurité et du Numérique a pris, le 28 février 2024, l'arrêté numéro 2024-01 concernant des exigences en matière de ressources informationnelles au regard de l'utilisation de l'intelligence artificielle par les organismes publics. Cette nouvelle obligation a permis au ministère de la Cybersécurité et du Numérique (MCN) de documenter les cas d'utilisations de l'IA dans l'administration publique et d'en établir un portrait. Les informations contenues dans le fichier proviennent donc d'une collecte réalisée auprès des organismes publics. Le portrait présente l'ensemble des initiatives qui sont actuellement en développement ou en production au sein des organismes publics. Tou…
Human review: Official Quebec public-administration AI dataset; accepted for follow-up while the missing PID and licence remain explicit metadata gaps.
publication2024-03-15CC BY NCfollow-up fields complete
accepted
AI Readiness Level in Public Administration: Case of the Russian Federation
The study explores approaches to the analysis of measurable indicators of artificial intelligence and its use in the system of sectoral public administration. As a part of the research the author developed the methodological basis for assessing the likelihood of the emergence of artificial intelligence. The research proposed analysis of the external base, technology, statistical reliability, education, labor market, citizens’ perspectives and development of the index of readiness for the emergence of artificial intelligence in sectoral public administration. The author carried out analysis of state functions and tasks for the introduction of artificial intelligence technologies, monitoring of measurable results of the introduction of artificial intelligence, analysis of government programs and cases of digital transformation based on AI technologies. It is shown, that currently, when …
Human review: Directly relevant case study of AI readiness in Russian public administration with complete configured metadata.
National AI Safety Framework for Bangladesh (2026–2035) The National AI Safety Framework for Bangladesh is a comprehensive risk-based governance and regulatory framework designed to ensure the safe, ethical, secure, and responsible development, deployment, and use of Artificial Intelligence across Bangladesh. Developed by Atlas AI Institute, the framework establishes national standards for AI safety, transparency, accountability, human rights protection, innovation governance, and risk management. The framework introduces a five-tier AI risk classification model, sector-specific governance requirements, national oversight mechanisms, compliance obligations, and institutional structures to guide AI adoption across healthcare, finance, agriculture, education, public administration, law enforcement, critical infrastructure, and national security sectors. Aligned with international best p…
Human review: This self-published framework is not clearly an official Government of Bangladesh source; exclude it to avoid implying official status.
Artificial Intelligence in Public Administration: A Bibliometric Analysis from 2015-2026 Based on Scopus Data
Background: The rapid advancement of artificial intelligence (AI) has driven a significant transformation in modern public administration practices; however, comprehensive bibliometric mapping focused on the explosive period of the last decade remains highly limited. Objectives: This study aims to analyze the developmental landscape of scientific literature on AI in public administration during the 2015-2025 period, encompassing annual publication trends, geographical and institutional distributions, international collaboration networks, as well as the thematic and conceptual structures dominating academic discourse in this field. Methods: This study employs a quantitative bibliometric approach combined with a systematic literature review based on the PRISMA framework. Data were retrieved from the Scopus database using advanced search queries with the keywords "artificial intelli…
Human review: Relevant bibliometric mapping; retain with caution because the title says 2015-2026 while the description states 2015-2025.
Artificial intelligence implementation strategies in public administration: best practices and challenges
This article explores the implementation of artificial intelligence in public administration through thelens of strategy, ethics, and public engagement. It reveals how innovations in the field of AI can transformmanagement processes, improving the level of services and simplifying the solution of complex tasks.Prospective directions and potential risks are discussed, with special emphasis on the importance ofan ethical approach and active involvement of citizens in decision–making processes. A critical analysisof current publications is provided, emphasizing the need for a deeper understanding of this dynamicfield. Also, this article examines the international experience of using artificial intelligence in publicadministration, provides examples of such use and a brief analysis. In conclusion, recommendationsare formulated for the development of more effective strategies for the use o…
Human review: Directly addresses implementation strategies, ethics and public engagement in public administration.
publication2025-02-20CC BY NC NDfollow-up fields complete
rejected
AI-Driven Governance: Enhancing Transparency and Accountability in Public Administration
Artificial Intelligence (AI) is transforming public administration by improving efficiency, enhancing transparency, and facilitating data-driven decision-making. This paper explores the integration of AI in government decision-making, examining its applications, challenges, and policy recommendations. The study highlights the role of AI in policy analysis, administrative efficiency, financial management, and public participation. Key challenges such as algorithmic bias, data privacy concerns, explainability issues, and regulatory gaps are discussed. The paper proposes a set of policy recommendations, including the establishment of AI ethics councils, implementation of explainability standards, enhancement of public AI literacy, and the creation of AI transparency laws. Future research should focus on hybrid human-machine governance models to ensure AI adoption aligns with democratic p…
Human review: Broad governance essay with unclear methodology and limited evidence detail for this decision-oriented shortlist.
The inclusion and participation of actors involved in artificial intelligence governance applied to public administrative systems and procedures
The primary objective was to build a model that complements the provisions of the recent European Union AI regulation, the National Institute of Standards and Technology (NIST) Artificial Intelligence Risk Management Framework—which operationalizes the US President’s Executive Order 14110—and the first international standard for the Artificial Intelligence Management Systems (ISO/IEC 42001:2023) of the International Standardization Organization (ISO). This objective was a priority because Responsibility Articles 28 and 57 of the recent European Union regulations have set a deadline of August 2025 and August 2026 for designating an authority responsible for evaluations and testing before artificial intelligence (AI) systems are put into service. The previous objective analyzes the above regulations and provisions from the perspective of AI governance (AIG). That is, the approach seeks …
Human review: Directly addresses stakeholder participation in public-sector AI governance and relates EU, NIST and ISO governance frameworks.