Hybrid Human Artificial Collective Intelligence in Open-Ended Decision Making

Informazioni relative al progetto

HACID

ID dell’accordo di sovvenzione: 101070588

DOI

10.3030/101070588

Progetto chiuso

Data della firma CE 3 Giugno 2022

Data di avvio 1 Settembre 2022

Data di completamento 28 Febbraio 2026

Finanziato da

• Digital, Industry and Space

Costo totale

€ 2 164 500,00

Contributo UE

€ 1 877 250,00

Coordinato da

CONSIGLIO NAZIONALE DELLE RICERCHE
Italy

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documents, reports (8)

Communication and dissemination plan
Requirements from climate services

A technical report that outlines key findings from user research with METO and prototype requirements for deploying the HACID-DSS to climate services.

Report on dissemination and outreach activities - Year 1

Annual report on dissemination and outreach activities - year 1

IPR management plan - mid term revision

Mid term revision of the IPR management plan

Ethics check report

A report is requested for the ethics check at M3 to address the following:PERSONAL DATA. The description states that a minimum amount of personal data is collected and processed. Clarifications need to be provided on the types of personal data collected and processed.PERSONAL DATA. The beneficiary must confirm that it has appointed a Data Protection Officer (DPO) and the contact details of the DPO are made available to all data subjects involved in the research. For beneficiaries not required to appoint a DPO under the GDPR, a detailed data protection policy for the project must be submitted.NON-EU COUNTRIES. Human participants for the climate service case will be selected from the UK Met office -a non-EU country- as well as one of the evaluators (NESTA), therefore the beneficiary must provide details on the personal data which will be imported to/exported from EU and confirm that the adequate authorizations have been obtained and are kept on file.

IPR management plan

Report about the IPR management practices

Exploitation Plan

Plan for exploitation activities

Top-down and bottom-up approaches to domain knowl- edge engineering

The deliverable describes the methods and results related to knowledge engineering for building the DKG.

Data Management Plan (2)

Data management plan

First version of the data management plan

Data management plan - mid term revision

Mid-term revision of the data management plan

Websites, patent fillings, videos etc. (1)

Project website and social media channels

Pubblicazioni

Conference proceedings (8)

Ontogenia: Ontology Generation with Metacognitive Prompting in Large Language Models

Autori: Lippolis, Anna Sofia; Ceriani, Miguel; Zuppiroli, Sara; Nuzzolese, Andrea Giovanni
Pubblicato in: Lecture Notes in Computer Science ISBN: 9783031789519, 2025
Editore: Springer, Cham
DOI: 10.1007/978-3-031-78952-6_38

Large Language Models Assisting Ontology Evaluation

Autori: Anna Sofia Lippolis, Mohammad Javad Saeedizade, Robin Keskisärkkä, Aldo Gangemi, Eva Blomqvist, Andrea Giovanni Nuzzolese
Pubblicato in: Lecture Notes in Computer Science, The Semantic Web – ISWC 2025, 2025
Editore: Springer Nature Switzerland
DOI: 10.48550/ARXIV.2507.14552

Does AI mean we need to do climate services differently?

Autori: Fai Fung, Neha Mittal
Pubblicato in: 2024
Editore: Copernicus GmbH
DOI: 10.5194/EMS2024-489

Ontology Generation Using Large Language Models

Autori: Anna Sofia Lippolis, Mohammad Javad Saeedizade, Robin Keskisärkkä, Sara Zuppiroli, Miguel Ceriani, Aldo Gangemi, Eva Blomqvist, Andrea Giovanni Nuzzolese
Pubblicato in: Lecture Notes in Computer Science, The Semantic Web, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-94575-5_18

Assessing the Capability of Large Language Models for Domain-Specific Ontology Generation

Autori: Anna Sofia Lippolis, Mohammad Javad Saeedizade, Robin Keskisarkka, Aldo Gangemi, Eva Blomqvist, Andrea Giovanni Nuzzolese
Editore: CEUR-WS

Expertise Trees Resolve Knowledge Limitations in Collective Decision-Making

Autori: Abels A.; Lenaerts T.; Trianni V.; Nowe A.
Pubblicato in: Proceedings of the 40th International Conference on Machine Learning, Numero 202:79-90, 2023
Editore: PMLR

Boosting collective intelligence in medical diagnostics: Leveraging decision similarity as a predictor of accuracy when answers are open-ended rankings

Autori: Nikolas Zöller, Stefan M. Herzog, RalfH.J.M. Kurvers
Pubblicato in: HCOMP-CI 2023 Works-in-Progress and Demonstrations, 2023
Editore: ACM Press

Hybrid Collective Intelligence for Decision Support in Complex Open-Ended Domains

Autori: Vito Trianni; Andrea Giovanni Nuzzolese; Jaron Porciello; Ralf H. J. M. Kurvers; Stefan M. Herzog; Gioele Barabucci; Aleksandra Berditchevskaia; Fai Fung
Pubblicato in: Frontiers in Artificial Intelligence and Applications, 2023
Editore: IOS Press
DOI: 10.3233/faia230079

Peer reviewed articles (8)

Proceedings of the National Academy of Sciences of the United States of America

Autori: Ralf H. J. M. Kurvers; Andrea Giovanni Nuzzolese; Alessandro Russo; Gioele Barabucci; Stefan M. Herzog; Vito Trianni
Pubblicato in: Proceedings of the National Academy of Sciences of the United States of America, 2023, ISSN 0027-8424
Editore: National Academy of Sciences
DOI: 10.1073/pnas.2221473120

Collective Intelligence Increases Diagnostic Accuracy in a General Practice Setting

Autori: Matthew D. Blanchard, Stefan M. Herzog, Juliane E. Kämmer, Nikolas Zöller, Olga Kostopoulou, Ralf H. J. M. Kurvers
Pubblicato in: Medical Decision Making, Numero 44, 2025, ISSN 0272-989X
Editore: SAGE Publications
DOI: 10.48350/195923

Combining Multiple Large Language Models Improves Diagnostic Accuracy

Autori: Gioele Barabucci, Victor Shia, Eugene Chu, Benjamin Harack, Kyle Laskowski, Nathan Fu
Pubblicato in: NEJM AI, Numero 1, 2024, ISSN 2836-9386
Editore: Massachusetts Medical Society
DOI: 10.1056/AICS2400502

Human–AI collectives most accurately diagnose clinical vignettes

Autori: Nikolas Zöller, Julian Berger, Irving Lin, Nathan Fu, Jayanth Komarneni, Gioele Barabucci, Kyle Laskowski, Victor Shia, Benjamin Harack, Eugene A. Chu, Vito Trianni, Ralf H. J. M. Kurvers, Stefan M. Herzog
Pubblicato in: Proceedings of the National Academy of Sciences, Numero 122, 2025, ISSN 0027-8424
Editore: Proceedings of the National Academy of Sciences
DOI: 10.1073/PNAS.2426153122

Proceedings of the National Academy of Sciences of the United States of America

Autori: Zöller, N; Berger, J; Lin, I; Fu, N; Komarneni, J; Barabucci, G; Laskowski, K; Shia, V; Harack, B; Chu, EA; Trianni, V; Kurvers, RHJM; Herzog, SM
Pubblicato in: Proceedings of the National Academy of Sciences, 2025, ISSN 0027-8424
Editore: Proceedings of the National Academy of Sciences
DOI: 10.1073/PNAS.2426153122

Automating hybrid collective intelligence in open-ended medical diagnostics

Autori: Ralf H. J. M. Kurvers, Andrea Giovanni Nuzzolese, Alessandro Russo, Gioele Barabucci, Stefan M. Herzog, Vito Trianni
Pubblicato in: Proceedings of the National Academy of Sciences, Numero 120, 2024, ISSN 0027-8424
Editore: Proceedings of the National Academy of Sciences
DOI: 10.1073/PNAS.2221473120

Logic Augmented Generation

Autori: Aldo Gangemi, Andrea Giovanni Nuzzolese
Pubblicato in: Journal of Web Semantics, Numero 85, 2025, ISSN 1570-8268
Editore: Elsevier BV
DOI: 10.48550/ARXIV.2411.14012

How large language models can reshape collective intelligence

Autori: Jason W. Burton; Ezequiel Lopez-Lopez; Shahar Hechtlinger; Zoe Rahwan; Samuel Aeschbach; Michiel A. Bakker; Joshua A. Becker; Aleks Berditchevskaia; Julian Berger; Levin Brinkmann; Lucie Flek; Stefan M. Herzog; Saffron Huang; Sayash Kapoor; Arvind Narayanan; Anne-Marie Nussberger; Taha Yasseri; Pietro Nickl; Abdullah Almaatouq; Ulrike Hahn; Ralf H. J. M. Kurvers; Susan Leavy; Iyad Rahwan; Divya Siddarth; Alice Siu; Anita W. Woolley; Dirk U. Wulff; Ralph Hertwig
Pubblicato in: Nature Human Behaviour, 2024, ISSN 2397-3374
Editore: Nature Portfolio
DOI: 10.1038/S41562-024-01959-9