Trusted AI for Transparent Public Governance fostering Democratic Values

Informations projet

AI4Gov

N° de convention de subvention: 101094905

DOI

10.3030/101094905

Projet clôturé

Date de signature de la CE 11 Decembre 2022

Date de début 1 Janvier 2023

Date de fin 31 Decembre 2025

Financé au titre de

• Culture, creativity and inclusive society

Coût total

€ 3 000 000,00

Contribution de l’UE

€ 3 000 000,00

Coordonné par

MAGGIOLI SPA
Italy

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

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.

Publications

Conference proceedings (14)

Mitigating Bias in Time Series Forecasting for Efficient Wastewater Management

Auteurs: Konstantinos Mavrogiorgos, Athanasios Kiourtis, Argyro Mavrogiorgou, Alenka Gucek, Andreas Menychtas, Dimosthenis Kyriazis
Publié dans: 2024 7th International Conference on Informatics and Computational Sciences (ICICoS), 2024
Éditeur: 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"

Auteurs: 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
Publié dans: In 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), ISSN 2325-2944
Éditeur: IEEE
DOI: 10.1109/DCOSS-IOT58021.2023.00090

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

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

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

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

Time Series Forecasting for Touristic Policies

Auteurs: Konstantinos Mavrogiorgos, Athanasios Kiourtis, Argyro Mavrogiorgou, Dimitrios Apostolopoulos, Andreas Menychtas, Dimosthenis Kyriazis
Publié dans: ITISE 2025, 2025
Éditeur: MDPI
DOI: 10.3390/CMSF2025011004

The WHY in Business Processes: Unification of Causal Process Models

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

Towards a Benchmark for Causal Business Process Reasoning with LLMs

Auteurs: Fabiana Fournier, Lior Limonad, Inna Skarbovsky
Publié dans: Lecture Notes in Business Information Processing, Business Process Management Workshops, 2025
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-78666-2_18

Selecting the Right Llm for Egov Explanations

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

Self-Explaining Neural Networks for Business Process Monitoring

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

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

Auteurs: Shahaf Bassan, Ron Eliav, Shlomit Gur
Publié dans: The Thirteenth International Conference on Learning Representations (ICLR), 2024
Éditeur: ICLR

A Question Answering Software for Assessing AI Policies of OECD Countries

Auteurs: Konstantinos Mavrogiorgos, Athanasios Kiourtis, Argyro Mavrogiorgou, Georgios Manias, Dimosthenis Kyriazis
Publié dans: The 4th European Symposium on Software Engineering (ESSE 2023), 2023
Éditeur: ACM
DOI: 10.1145/3651640.3651651

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

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

eXplainable Random Forest

Auteurs: Guy Amit, Shlomit Gur
Publié dans: Proceedings of Workshop on Embracing Human-Aware AI in Industry 5.0 (HAII5.0 2024), 2024
Éditeur: CEUR-WS (CEUR Workshop Proceedings)

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

Auteurs: 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
Publié dans: Proceedings from the 2024 Global Conference on AI and Human Rights, 2024
Éditeur: Litteralis Ltd

Peer reviewed articles (3)

Bias in Machine Learning: A Literature Review

Auteurs: Konstantinos Mavrogiorgos; Athanasios Kiourtis; Argyro Mavrogiorgou; Andreas Menychtas; Dimosthenis Kyriazis
Publié dans: Applied Sciences, 2024, ISSN 2076-3417
Éditeur: MDPI
DOI: 10.3390/APP14198860

The WHY in Business Processes: Discovery of Causal Execution Dependencies

Auteurs: Fabiana Fournier; Lior Limonad; Inna Skarbovsky; Yuval David
Publié dans: KI - Künstliche Intelligenz, 2025, ISSN 0933-1875
Éditeur: Springer Nature
DOI: 10.48550/ARXIV.2310.14975

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

Auteurs: Dirk Fahland, Fabiana Fournier, Lior Limonad, Inna Skarbovsky, Ava J.E. Swevels
Publié dans: Data & Knowledge Engineering, Numéro 157, 2025, ISSN 0169-023X
Éditeur: Elsevier BV
DOI: 10.1016/J.DATAK.2025.102416