Trusted AI for Transparent Public Governance fostering Democratic Values

Información del proyecto

AI4Gov

Identificador del acuerdo de subvención: 101094905

DOI

10.3030/101094905

Proyecto cerrado

Fecha de la firma de la CE 11 Diciembre 2022

Fecha de inicio 1 Enero 2023

Fecha de finalización 31 Diciembre 2025

Financiado con arreglo a

• Culture, creativity and inclusive society

Coste total

€ 3 000 000,00

Aportación de la UE

€ 3 000 000,00

Coordinado por

MAGGIOLI SPA
Italy

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

Demonstrators, pilots, prototypes (8)

AI4Gov Holistic Regulatory Framework V1

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

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

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

AI4Gov Holistic Regulatory Framework V2

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

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

Reference Architecture and Integration of AI4Gov Platform V1

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

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

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

Documents, reports (5)

Assessment tools, training activities, best practice guide V1

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

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

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

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

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

Publicaciones

Conference proceedings (14)

Mitigating Bias in Time Series Forecasting for Efficient Wastewater Management

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

"G. Manias et al., ""AI4Gov: Trusted AI for Transparent Public Governance Fostering Democratic Values,"" 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), Pafos, Cyprus, 2023, pp. 548-555, do"

Autores: George Manias, Dimitris Apostolopoulos, Sotiris Athanassopoulos, Spiros Borotis, Charalampos Chatzimallis, Theodoros Chatzipantelis, Marcelo Corrales Compagnucci, Tanja Zdolsek Draksler, Fabiana Fournier, Magdalena Goralczyk, Alenka Gucek, Andreas Karabet
Publicado en: In 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), ISSN 2325-2944
Editor: IEEE
DOI: 10.1109/DCOSS-IOT58021.2023.00090

Bridging Global Disparities: An Analytics Pipeline for Detecting Bias and Incompleteness in Rare Diseases Datasets

Autores: Alenka Guček, Matej Kovačič, Tanja Zdolšek Draksler
Publicado en: Meeting abstracts from the 12th European Conference on Rare Diseases and Orphan Products, 2024
Editor: BioMed Central
DOI: 10.1186/S13023-024-03293-9

Combining Explainable Artificial Intelligence (Xai) With Blockchain Towards Trustworthy Data-Driven Policies

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

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

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

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

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

Self-Explaining Neural Networks for Business Process Monitoring

Autores: Shahaf Bassan, Shlomit Gur, Sergey Zeltyn, Konstantinos Mavrogiorgos, Ron Eliav, Dimosthenis Kyriazis
Publicado en: ICSBT 2026 – 23rd International Conference on Smart Business Technologies
Editor: Springer
DOI: 10.48550/ARXIV.2503.18067

EXPLAIN YOURSELF, BRIEFLY! SELF-EXPLAINING NEURAL NETWORKS WITH CONCISE SUFFICIENT REASONS

Autores: Shahaf Bassan, Ron Eliav, Shlomit Gur
Publicado en: The Thirteenth International Conference on Learning Representations (ICLR), 2024
Editor: ICLR

A Question Answering Software for Assessing AI Policies of OECD Countries

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

Multilingual Classification of AI-Oriented Policy Documents based on Bias Types

Autores: George Manias, Chrysa Agapitou, Nemania Borovits, Alenka Guček, Andreas Karabetian, Matej Kovacic, Konstantinos Mavrogiorgos, Tanja Zdolšek Draksler, Willem-Jan van den Heuvel, Dimosthenis Kyriazis
Publicado en: Data for Policy 2025 (DfP’25) - Europe Book of Abstracts
Editor: Data for Policy CIC

eXplainable Random Forest

Autores: Guy Amit, Shlomit Gur
Publicado en: Proceedings of Workshop on Embracing Human-Aware AI in Industry 5.0 (HAII5.0 2024), 2024
Editor: CEUR-WS (CEUR Workshop Proceedings)

Fostering Fundamental Human Rights and Trustworthiness though the Utilization of Emerging Technologies: the AI4Gov Platform

Autores: George Manias; Spiros Borotis; Charalampos Chatzimallis; Tanja Zdolsek Draksler; Alenka Gucek; Fabiana Fournier; Andreas Karabetian; Dimitris Kotios; Matej Kovacic; Danai Kyrkou; Lior Limonad; Konstantinos Mavrogiorgos; Dimitris Ntalaperas; Xanthi S. Papa
Publicado en: Proceedings from the 2024 Global Conference on AI and Human Rights, 2024
Editor: Litteralis Ltd

Peer reviewed articles (3)

Bias in Machine Learning: A Literature Review

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

The WHY in Business Processes: Discovery of Causal Execution Dependencies

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

How well can a large language model explain business processes as perceived by users?

Autores: Dirk Fahland, Fabiana Fournier, Lior Limonad, Inna Skarbovsky, Ava J.E. Swevels
Publicado en: Data & Knowledge Engineering, Edición 157, 2025, ISSN 0169-023X
Editor: Elsevier BV
DOI: 10.1016/J.DATAK.2025.102416