Project description
Building trustworthy, explainable and accountable AI across models
AI technologies have made advances in recent years, playing an increasingly important role in various industries and research fields. Unfortunately, along with this role have come issues and doubts regarding their accountability, explainability, and transparency. Overcoming this issue has been a challenging task due to the varying requirements of different AI models and architectures. The EU-funded AIXPERT project will develop an innovative approach to creating AI systems that are accountable, explainable, and transparent through the creation of an architecture-agnostic, situation-aware AI-agentic platform. This platform will increase trustworthiness by utilising a consistent framework that can provide explainability and accountability across different model types, including multi-agent systems, multimodal foundation models, and real-time human feedback.
Objective
The AIXPERT project proposes a novel, comprehensive approach to developing explainable, accountable, and transparent AI systems. At its core, the project introduces an adaptable, situation-aware AI-agentic platform capable of encapsulating various AI models, regardless of their underlying architecture. This architecture-agnostic approach significantly enhances the trustworthiness of AI systems by providing a consistent framework for explainability and accountability across different model types. The project aims to address challenges in AI explainability, transparency, accountability, autonomy, and robustness by integrating multi-agent systems with multimodal foundation models and leveraging real-time human feedback. This integration enhances AI system trustworthiness and user-friendliness while maintaining flexibility in the choice of underlying AI models. The project will be implemented in a multi-layered architecture, with each layer focusing on specific aspects of AI interpretability and explainability: the Agent-World Interface Layer will define and coordinate AI agents, their situational awareness, and their interactions with real-world knowledge sources; the Dialogue Mediation Layer will control user-agent and agent-agent communications; and the Cognitive Foundation Layer will provide the base capabilities for the system based on explainable multimodal foundation models. The project will also focus on developing a framework for assessing AI trustworthiness, demonstrating the value of explainable AI through pilot demonstrations in healthcare, recruitment services, manufacturing, educational robotics, and creative industries, and ensuring the sustainability of its results. AIXPERT envisions delivering AI solutions that are not only transparent and ethical but also sustainable and adaptable to diverse user needs, ultimately fostering greater trust in AI across multiple industries and societal sectors.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.2.4 - Digital, Industry and Space
MAIN PROGRAMME
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HORIZON.2.4.5 - Artificial Intelligence and Robotics
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
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.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-CL4-2024-HUMAN-03
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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.
151 25 MAROUSSI
Greece
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.