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CORDIS - Resultados de investigaciones de la UE
CORDIS

Trusted AI for Transparent Public Governance fostering Democratic Values

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

AI4Gov Holistic Regulatory Framework V1 (se abrirá en una nueva ventana)

will study and list common antecedents for biases, unfairness and non-inclusiveness and list of vulnerable (intersectional) groups by UC and design the HRF of the project (T2.2).

Decentralized Data Governance, Provenance and Reliability V1 (se abrirá en una nueva ventana)

will architect the decentralized Blockchain-based applications in governance and will introduce, monitor and revise the DGF across the complete lifecycle of the project.

Trustworthy, Explainable, and unbiased AI V1 (se abrirá en una nueva ventana)

Prototype implementation of AI, XAI, SAX, FML and real-time analytics infrastructures.

AI4Gov Holistic Regulatory Framework V2 (se abrirá en una nueva ventana)

will study and list common antecedents for biases, unfairness and non-inclusiveness and list of vulnerable (intersectional) groups by UC and design the HRF of the project (T2.2).

Policies Visualization Services V1 (se abrirá en una nueva ventana)

Software implementations of policy modelling/interpretation/monitoring, and visualization services.

Reference Architecture and Integration of AI4Gov Platform V1 (se abrirá en una nueva ventana)

will identify the key components of AI4Gov and define the interfaces and interactions between them. It will also describe the integrations between the toolkits, libraries, frameworks and components of the project.

Decentralized Data Governance, Provenance and Reliability V2 (se abrirá en una nueva ventana)

will architect the decentralized Blockchain-based applications in governance and will introduce, monitor and revise the DGF across the complete lifecycle of the project.

Policy Recommendation Toolkit V1 (se abrirá en una nueva ventana)

will deliver a populated version of the catalogue for policies models and associated datasets to be exploited for reuse in different domains (T3.4).

Assessment tools, training activities, best practice guide V1 (se abrirá en una nueva ventana)

will introduce a set of (self) assessment tools and checklists, describe the training plan and activities with respect to different groups. Moreover, they will provide the material used in envisioned training courses and MOOCs, and a best practice guide and blueprint will be delivered covering ethical and technical aspects of AI development processes.

Specification of UC Scenarios and Planning of Integration and Validation Activities V2 (se abrirá en una nueva ventana)

Report on co-creation activities and specification design of the different UC scenarios. AI4Gov technologies’ experimentation and evaluation upon the different UCs.

Specification of UC Scenarios and Planning of Integration and Validation Activities V1 (se abrirá en una nueva ventana)

Report on co-creation activities and specification design of the different UC scenarios. AI4Gov technologies’ experimentation and evaluation upon the different UCs.

Input papers to facilitate the workshops on awareness raising V1 (se abrirá en una nueva ventana)

will provide the input papers with data on existing awareness-raising strategies to mitigate AI bias and discrimination and to enhance inclusiveness, representation, participation, openness, pluralism, and tolerance.

Dissemination, Communication, Standardization Activities Report V1 (se abrirá en una nueva ventana)

report (living document) on the outcomes of T7.1, T7.2 and T7.3, that will be delivered periodically.

Publicaciones

Mitigating Bias in Time Series Forecasting for Efficient Wastewater Management (se abrirá en una nueva ventana)

Autores: Konstantinos Mavrogiorgos, Athanasios Kiourtis, Argyro Mavrogiorgou, Alenka Gucek, Andreas Menychtas, Dimosthenis Kyriazis
Publicado en: 2024 7th International Conference on Informatics and Computational Sciences (ICICoS), 2024
Editor: IEEE
DOI: 10.1109/ICICOS62600.2024.10636931

Combining Explainable Artificial Intelligence (Xai) With Blockchain Towards Trustworthy Data-Driven Policies (se abrirá en una nueva ventana)

Autores: Konstantinos Mavrogiorgos, Shlomit Gur, Nikolaos Kalantzis, Konstantinos Tzelaptsis, Xanthi S. Papageorgiou, Andreas Karabetian, Georgios Manias, Argyro Mavrogiorgou, Dimosthenis Kyriazis, Celia Parra
Publicado en: 2025 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), 2025
Editor: IEEE
DOI: 10.1109/DCOSS-IOT65416.2025.00157

Time Series Forecasting for Touristic Policies (se abrirá en una nueva ventana)

Autores: Konstantinos Mavrogiorgos, Athanasios Kiourtis, Argyro Mavrogiorgou, Dimitrios Apostolopoulos, Andreas Menychtas, Dimosthenis Kyriazis
Publicado en: ITISE 2025, 2025
Editor: MDPI
DOI: 10.3390/CMSF2025011004

The WHY in Business Processes: Unification of Causal Process Models (se abrirá en una nueva ventana)

Autores: Yuval David, Fabiana Fournier, Lior Limonad, Inna Skarbovsky
Publicado en: Lecture Notes in Business Information Processing, Business Process Management Forum, 2025
Editor: Springer Nature Switzerland
DOI: 10.1007/978-3-032-02929-4_3

Towards a Benchmark for Causal Business Process Reasoning with LLMs (se abrirá en una nueva ventana)

Autores: Fabiana Fournier, Lior Limonad, Inna Skarbovsky
Publicado en: Lecture Notes in Business Information Processing, Business Process Management Workshops, 2025
Editor: Springer Nature Switzerland
DOI: 10.1007/978-3-031-78666-2_18

Selecting the Right Llm for Egov Explanations (se abrirá en una nueva ventana)

Autores: Lior Limonad, Fabiana Fournier, Hadar Mulian, George Manias, Spiros Borotis, Danai Kyrkou
Publicado en: 2025 Eleventh International Conference on eDemocracy & eGovernment (ICEDEG), 2025
Editor: IEEE
DOI: 10.1109/ICEDEG65568.2025.11081620

A Question Answering Software for Assessing AI Policies of OECD Countries (se abrirá en una nueva ventana)

Autores: Konstantinos Mavrogiorgos, Athanasios Kiourtis, Argyro Mavrogiorgou, Georgios Manias, Dimosthenis Kyriazis
Publicado en: The 4th European Symposium on Software Engineering (ESSE 2023), 2023
Editor: ACM
DOI: 10.1145/3651640.3651651

Bias in Machine Learning: A Literature Review (se abrirá en una nueva ventana)

Autores: Konstantinos Mavrogiorgos; Athanasios Kiourtis; Argyro Mavrogiorgou; Andreas Menychtas; Dimosthenis Kyriazis
Publicado en: Applied Sciences, 2024, ISSN 2076-3417
Editor: MDPI
DOI: 10.3390/APP14198860

Orphanet Journal of Rare Diseases (se abrirá en una nueva ventana)

Publicado en: Orphanet Journal of Rare Diseases, 2024, ISSN 1750-1172
Editor: Springer Nature
DOI: 10.1186/S13023-024-03293-9

The WHY in Business Processes: Discovery of Causal Execution Dependencies (se abrirá en una nueva ventana)

Autores: Fabiana Fournier; Lior Limonad; Inna Skarbovsky; Yuval David
Publicado en: KI - Künstliche Intelligenz, 2025, ISSN 0933-1875
Editor: Springer Nature
DOI: 10.48550/ARXIV.2310.14975

Data and Knowledge Engineering (se abrirá en una nueva ventana)

Autores: Dirk Fahland; Fabiana Fournier; Lior Limonad; Inna Skarbovsky; Ava J.E. Swevels
Publicado en: Data and Knowledge Engineering, 2025, ISSN 0169-023X
Editor: Elsevier BV
DOI: 10.48550/ARXIV.2401.12846

The WHY in Business Processes: Discovery of Causal Execution Dependencies (se abrirá en una nueva ventana)

Autores: Fournier, Fabiana; Limonad, Lior; Skarbovsky, Inna; David, Yuval
Publicado en: 2023
DOI: 10.48550/arxiv.2310.14975

How well can large language models explain business processes? (se abrirá en una nueva ventana)

Autores: Dirk Fahland, Fabiana Fournier, Lior Limonad, Inna Skarbovsky, Ava J.E. Swevels
Publicado en: 2024
DOI: 10.48550/arXiv.2401.12846

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