Project description
Rethinking how AI adapts to the real world
Machine learning powers everything from medical diagnostics to climate models. However, moving from the lab to the real world is not easy. Data shifts, unforeseen conditions, and human complexity can challenge even the best algorithms. The ERC-funded ODD-ML project aims to solve this problem by putting people back at the centre of machine learning. Instead of relying solely on past data, ODD-ML will design AI systems that actively learn from human experts. Specifically, the machines will capture human intuition, experience, and even biases. By bridging human insight and machine reasoning, the project seeks to create AI that adapts more intelligently to new situations, boosting trust, reliability, and real-world impact.
Objective
ODD-ML addresses the open secret of machine learning (ML), which is that model deployment often fails. The problem arises because deployment contexts may differ from the data used to train ML models in unexpected ways. In an increasingly data-driven era, this severely impedes progress in ML-powered R&D and our ability to tackle societal grand challenges with existing ML tools.
To solve this pervasive issue, I propose a radical alternative to current ML approaches, placing human experts at the core of iterative design-build-test-learn (DBTL) loops. My approach comprises the interlinked steps of re-conceptualizing the deployment issue as a need for active learning from domain experts and other indirect sources and, to succeed here, recognizing the imperfect and often tacit knowledge and limited time of human experts, designing ML systems that can rapidly reverse-engineer expert knowledge.
I will achieve this with a combination of ideas transformative for human-AI collaboration: human inductive biases will be inferred from computational-rationality-based cognitive models, amortized on pre-computed solutions for speed, allowing interactive online use. I envision widespread impact in ML, on complex decision-making, and broadly across R&D domains.
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.
This project's classification has been human-validated.
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.
This project's classification has been human-validated.
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.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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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-ERC - HORIZON ERC Grants
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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) ERC-2024-ADG
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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.
02150 Espoo
Finland
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.