Project description
Building secure and fair AI systems for industry and beyond
In recent years, advances in AI have benefited most industries, driving key insights and breakthroughs across sectors such as healthcare, transportation, finance, and manufacturing. The EU-funded TRUMAN project aims to develop generic methodologies and technologies that enhance AI system resilience against privacy, fairness, and security threats, while also increasing user trust. To achieve this, the research will focus on large language models, continual learning, and knowledge graph learning and representation, developing solutions tailored to diverse scenarios.
Objective
Artificial Intelligence (AI) has become the main driver of growth in information technology, touching all sectors in the industry, ranging from healthcare, to finance, and transport. The goal of TRUMAN is to design and develop generic technologies and methodologies for improving AI systems’ resilience against security, privacy, and fairness attacks, as well as to increase the trust that their users have in these systems, while accounting for different phases of the AI life cycle, starting from data collection through training and deployment. TRUMAN will encompass three major AI architectures: knowledge graph (KG) representation and learning, continual learning, and large language models (LLMs). These three approaches will be investigated with the goal of designing solutions aimed for scenarios involving dynamic data collection, distributed model training, and scenarios that involve human-in-the-loop (HITL) design principles. TRUMAN will develop customized robustness solutions for both existing and newly developed privacy, adversarial, and fairness attacks. The project will also consider the impact of these solutions on humans, how to explain to them the underlying technologies and the risks, and employ their help in the improvement of these models. These technologies will be evaluated against four use cases illustrating scenarios from different sectors, i.e. marketing, IT, finance, and healthcare. Moreover, the TRUMAN project will strive to generate generic/holistic guidelines and recommendations for building trustworthy and robust AI systems.
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.
- natural sciences computer and information sciences software software applications simulation software
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
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.
-
HORIZON.2.4 - Digital, Industry and Space
MAIN PROGRAMME
See all projects funded under this programme -
HORIZON.2.4.5 - Artificial Intelligence and Robotics
See all projects funded under this programme
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
See all projects funded under this funding scheme
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
See all projects funded under this callCoordinator
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.
06410 BIOT
France
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.