Trusted AI for Transparent Public Governance fostering Democratic Values

Informations projet

AI4Gov

N° de convention de subvention: 101094905

DOI

10.3030/101094905

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

Other (2)

The WHY in Business Processes: Discovery of Causal Execution Dependencies

Auteurs: Fournier, Fabiana; Limonad, Lior; Skarbovsky, Inna; David, Yuval
Publié dans: 2023
DOI: 10.48550/arxiv.2310.14975

How well can large language models explain business processes?

Auteurs: Dirk Fahland, Fabiana Fournier, Lior Limonad, Inna Skarbovsky, Ava J.E. Swevels
Publié dans: 2024
DOI: 10.48550/arXiv.2401.12846

Conference proceedings (1)

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