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CORDIS

Trusted AI for Transparent Public Governance fostering Democratic Values

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

AI4Gov Holistic Regulatory Framework V1 (opens in new window)

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 (opens in new window)

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 (opens in new window)

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

AI4Gov Holistic Regulatory Framework V2 (opens in new window)

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 (opens in new window)

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

Reference Architecture and Integration of AI4Gov Platform V1 (opens in new window)

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 (opens in new window)

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 (opens in new window)

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 (opens in new window)

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 (opens in new window)

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 (opens in new window)

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 (opens in new window)

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 (opens in new window)

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

Publications

Mitigating Bias in Time Series Forecasting for Efficient Wastewater Management (opens in new window)

Author(s): Konstantinos Mavrogiorgos, Athanasios Kiourtis, Argyro Mavrogiorgou, Alenka Gucek, Andreas Menychtas, Dimosthenis Kyriazis
Published in: 2024 7th International Conference on Informatics and Computational Sciences (ICICoS), 2024
Publisher: IEEE
DOI: 10.1109/ICICOS62600.2024.10636931

Combining Explainable Artificial Intelligence (Xai) With Blockchain Towards Trustworthy Data-Driven Policies (opens in new window)

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

Time Series Forecasting for Touristic Policies (opens in new window)

Author(s): Konstantinos Mavrogiorgos, Athanasios Kiourtis, Argyro Mavrogiorgou, Dimitrios Apostolopoulos, Andreas Menychtas, Dimosthenis Kyriazis
Published in: ITISE 2025, 2025
Publisher: MDPI
DOI: 10.3390/CMSF2025011004

The WHY in Business Processes: Unification of Causal Process Models (opens in new window)

Author(s): Yuval David, Fabiana Fournier, Lior Limonad, Inna Skarbovsky
Published in: Lecture Notes in Business Information Processing, Business Process Management Forum, 2025
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-032-02929-4_3

Towards a Benchmark for Causal Business Process Reasoning with LLMs (opens in new window)

Author(s): Fabiana Fournier, Lior Limonad, Inna Skarbovsky
Published in: Lecture Notes in Business Information Processing, Business Process Management Workshops, 2025
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-78666-2_18

Selecting the Right Llm for Egov Explanations (opens in new window)

Author(s): Lior Limonad, Fabiana Fournier, Hadar Mulian, George Manias, Spiros Borotis, Danai Kyrkou
Published in: 2025 Eleventh International Conference on eDemocracy & eGovernment (ICEDEG), 2025
Publisher: IEEE
DOI: 10.1109/ICEDEG65568.2025.11081620

A Question Answering Software for Assessing AI Policies of OECD Countries (opens in new window)

Author(s): Konstantinos Mavrogiorgos, Athanasios Kiourtis, Argyro Mavrogiorgou, Georgios Manias, Dimosthenis Kyriazis
Published in: The 4th European Symposium on Software Engineering (ESSE 2023), 2023
Publisher: ACM
DOI: 10.1145/3651640.3651651

Bias in Machine Learning: A Literature Review (opens in new window)

Author(s): Konstantinos Mavrogiorgos; Athanasios Kiourtis; Argyro Mavrogiorgou; Andreas Menychtas; Dimosthenis Kyriazis
Published in: Applied Sciences, 2024, ISSN 2076-3417
Publisher: MDPI
DOI: 10.3390/APP14198860

Orphanet Journal of Rare Diseases (opens in new window)

Published in: Orphanet Journal of Rare Diseases, 2024, ISSN 1750-1172
Publisher: Springer Nature
DOI: 10.1186/S13023-024-03293-9

The WHY in Business Processes: Discovery of Causal Execution Dependencies (opens in new window)

Author(s): Fabiana Fournier; Lior Limonad; Inna Skarbovsky; Yuval David
Published in: KI - Künstliche Intelligenz, 2025, ISSN 0933-1875
Publisher: Springer Nature
DOI: 10.48550/ARXIV.2310.14975

Data and Knowledge Engineering (opens in new window)

Author(s): Dirk Fahland; Fabiana Fournier; Lior Limonad; Inna Skarbovsky; Ava J.E. Swevels
Published in: Data and Knowledge Engineering, 2025, ISSN 0169-023X
Publisher: Elsevier BV
DOI: 10.48550/ARXIV.2401.12846

The WHY in Business Processes: Discovery of Causal Execution Dependencies (opens in new window)

Author(s): Fournier, Fabiana; Limonad, Lior; Skarbovsky, Inna; David, Yuval
Published in: 2023
DOI: 10.48550/arxiv.2310.14975

How well can large language models explain business processes? (opens in new window)

Author(s): Dirk Fahland, Fabiana Fournier, Lior Limonad, Inna Skarbovsky, Ava J.E. Swevels
Published in: 2024
DOI: 10.48550/arXiv.2401.12846

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