Openfund

CORDIS · HumAIne

Hybrid Human-AI Decision Support for Enhanced Human Empowerment in Dynamic Situations

Code
HumAIne
Programme
HORIZON
Call
HORIZON-CL4-2022-HUMAN-02-01
Status
SIGNED
Period
2023-10-01 – 2026-09-30
Total cost (whole consortium)7 658 375 €
EU contribution (whole consortium)7 658 375 €
EU contribution to Bulgarian participants208 750 €

Official data · CORDIS · synced 2026-10-17 10:16 · official record

Participants

OrganisationsRoleCountryGrant
GFT ITALIA SRLcoordinatorIT725 000 €
INSTITUT JOZEF STEFANparticipantSI838 375 €
UNIVERSITY OF PIRAEUS RESEARCH CENTERparticipantEL594 375 €
DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBHparticipantDE587 500 €
UBITECH ENERGYparticipantBE549 656 €
IBM ISRAEL - SCIENCE AND TECHNOLOGY LTDparticipantIL536 250 €
УНИВЕРСИТЕТ ГРЬОНИНГЕНparticipantNL535 000 €
INNOVATION SPRINTparticipantBE530 000 €
INNOV-ACTS LIMITEDparticipantCY456 250 €
UNPARALLEL INNOVATION LDAparticipantPT430 000 €
LEANXCALE SLparticipantES366 594 €
EBIT S.R.L.participantIT362 500 €
CHAROKOPEIO PANEPISTIMIOparticipantEL334 375 €
IMMERSIVELIVES LDAparticipantPT325 000 €
INNEUROPE INITIATIVE S.L.participantES278 750 €
VILABS BG LTDparticipantBG208 750 €
QLECTOR, RAZVOJ CELOVITIH RESITEV ZA PAMETNE TOVARNE DOOthird partySI0 €
NOVOVILLE LIMITEDassociated partnerUK

Description

HumAIne will research, develop, validate and promote a novel operating system for Human-AI collaboration, which will enable the development of advanced decision making applications in dynamic, unstructured environments in different industrial sectors. The HumAIne OS will empower AI solution integrators to implement Human-AI collaboration systems that outperform AI systems and humans when working in isolation. HumAIne’s developments will be integrated into a single OS platform, which will coordinate four interwind components offering Active Learning (AL), Neuro-Symbolic Learning, Swarm Learning (SL) as well eXplainable AI (XAI) capabilities. These advanced AI paradigms are ideal for exploiting true Human-AI collaboration since, in each of them, the worker is the key actor with complete control and understanding of the performed operations. AL enables the development of effective Human-in-the-Loop systems that involve humans when AI faces increased uncertainty. Neuro-Symbolic Learning combines DL with semantics and rules to complete highly complex tasks with high accuracy while requiring considerably less training data than current AI models. Advanced XAI models will be made available, providing explanations of models’ predictions while considering the global context instead of just analysing the feature importance of a single AI model. HumAIne’s XAI will provide guidance to humans to enable the timely optimisation of AL and SL models where human participants provide feedback dynamically as well as fine-tuning of Neuro-Symbolic models. The platform will handle various types of structured and unstructured data, including inputs from humans that will be semantically correlated through ontologies, knowledge graphs, and semantic interoperability. HumAIne will complement its platform with complementary resources (e.g., training) and will be build a vibrant community of interested parties around it, to drive exploitation and wider use of the project's results.

Official data · CORDIS · synced 2026-10-17 10:16 · official record · Licence: © European Union, CC BY 4.0 (Commission reuse policy).