Project description
Hybrid collective intelligence for decision support in medical diagnostics and climate services
The EU-funded HACID project is developing a hybrid collective intelligence based on the synergy between humans and machines to find solutions to real-world open-ended problems. The solutions to these problems are not constrained to a limited set of alternatives, and span many knowledge domains. HACID will explore a new approach that brings together human experts and AI-supported knowledge representation to create new tools for decision making. Two case studies will be considered. The first one will address knowledge fragmentation in medicine, helping medical professionals make more accurate diagnoses. The second one will provide support to policy makers in defining urban adaptation strategies to face future impacts of climate change.
Objective
HACID develops a novel hybrid collective intelligence for decision support to professionals facing complex open-ended problems, promoting engagement, fairness and trust. A decision support system (HACID-DSS) is proposed that is based on structured domain knowledge, semi-automatically assembled in a domain knowledge graph (DKG) from available data sources, such as scientific and gray literature. Given a specific case within the addressed domain, a pool of experts is consulted to (i) extract supporting evidence and enrich it, generating a case knowledge graph (CKG) as a subset of the DKG, and (ii) provide one or more solutions to the problem. Exploiting the CKG, the HACID-DSS gathers the expert advice in a collective solution that aggregates the individual opinions and expands them with machine-generated suggestions. In this way, HACID harnesses the wisdom of the crowd in open-ended problems, relying on a traceable process based on supporting evidence for better explainability. A set of evaluation methods is proposed to deal with domains where ground truth is not available, demonstrating the suitability of the proposed approach in a wide range of application domains. Demonstrations are provided in two compelling case studies contributing to the UN Sustainable Development Goals: crowd-sourcing medical diagnostics and climate services for urban adaptation.
Programme(s)
Funding Scheme
HORIZON-IA - HORIZON Innovation ActionsCoordinator
00185 Roma
Italy