Project description
Making AI smarter, transparent and trustworthy
In the world of AI, understanding causation is vital, especially in fields like healthcare and finance, where decisions impact lives and economies. Current AI models often lack transparency, relying on opaque methods that make it challenging for experts to verify or contest findings. Addressing this gap, the ERC-funded CArLA project aims to revolutionise causal discovery–the task of uncovering causal relationships from data. Building on robust methodologies and explainable AI (XAI) principles from the ERC ADIX project, CArLA’s platform will make causal discovery more transparent, interactive and contestable. The project will develop demonstrators in healthcare and finance, enabling experts to influence and verify AI-generated insights, thus fostering a more reliable, human-aligned AI approach for high-stakes decision-making.
Objective
Causal AI is widely perceived as crucial in the current AI landscape as it allows capturing causal effects amongst features in data, rather than simple correlations. Causal discovery is an important aspect of machine learning as it paves the way towards achieving Causal AI. It amounts to extracting causal graphs from data, encoding the structure of causal relations amongst features in data. There is a gap in the state-of-the-art in AI as concerns causal discovery, in that most approaches are black-boxes, hard to understand and explain, and unable to engage domain experts to integrate and possibly contest the learnt graphs when they are misaligned with human knowledge and values. CArLA aims at developing a platform for transparent, explainable, interactive and contestable causal discovery, based upon an existing principled methodology and prototype, as well as XAI techniques, developed within the ERC Advanced ADIX project. CArLA’s platform will support understanding the causal discovery process from data and experts while being able to influence it. Any developer or user of applications in high-stakes domains will benefit from using this uniquely trustworthy platform. CArLA aims to develop two demonstrators of the beneficial use of the platform in the high-stakes domains of healthcare and finance, to pave the way to commercialisation with a spinout.
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.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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-ERC-POC - HORIZON ERC Proof of Concept Grants
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) ERC-2024-POC
See all projects funded under this callHost institution
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.
SW7 2AZ London
United Kingdom
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.