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

Project description

A future where human-AI collaboration takes centre stage

Can humans and artificial intelligence (AI) work together in ever-changing, unstructured environments? This is a critical question in a world where AI plays a vital role in decision-making. In this context, the EU-funded HumAIne project will create an operating system for human-AI collaboration. The aim is to empower the development of advanced decision-making applications across various industrial sectors. This will enable AI solution integrators to create collaborative systems that outperform isolated AI systems and human efforts. The project will integrate four essential components: active learning, neuro-symbolic learning, swarm learning and explainable AI. These cutting-edge paradigms place the human operator at the centre, offering complete control and understanding of the operations performed, and ensuring seamless collaboration between humans and AI.

Objective

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.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-CL4-2022-HUMAN-02

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Coordinator

GFT ITALIA SRL
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 725 000,00
Address
VIA SILE 18
20139 Milano
Italy

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Region
Nord-Ovest Lombardia Milano
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 725 000,00

Participants (16)

Partners (1)

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