Project description
Trustworthy AI through better uncertainty quantification
As machine learning systems are increasingly used to support high-stakes decisions, there is a growing need to ensure that their predictions are reliably quantified in terms of uncertainty, fairness and real-world decision value. Supported by the Marie Skłodowska-Curie Actions programme, the GUIDDE project investigates how to make machine learning predictions more trustworthy by focusing on predictive uncertainty quantification. While recent advances enable calibrated probabilities and reliable prediction sets, a key open question remains: how these guarantees improve decisions in practice. The project will study trade-offs between fairness and sharpness, and when calibration leads to better outcomes, testing findings in exoplanet detection. It will deliver tailored methods, open-source tools and applications in healthcare and industry.
Objective
As machine learning (ML) is prevalent today to support decision-making, the European approach is to create an environment of trust for a fair AI through a unified regulatory framework, to ensure trust from both ‘‘people and companies’’. In line with this ambition, recent research efforts from the statistics and ML communities have been devoted to equipping ML models with provably valid tools for predictive uncertainty quantification (UQ), via methodological developments. We can now turn any point prediction into a guaranteed prediction set, or post-process estimated probabilities to get calibrated ones.
Yet, a crucial question remains: what does this offer to the downstream pipeline? This project targets this gap by: A) characterizing the trade-offs between the two UQ holy grails, namely fairness (via conditional validity) and tight evaluation of the underlying model’s error (via sharpness); thus helping any decision-maker to accurately interpret UQ performance, and B) qualifying under which conditions calibration allows decision-makers to take better decisions. Based on mathematical statistics tools, the theoretical outputs of A) and B) will be confronted with a real-world scientific application: exoplanet detection, where UQ is a critical step directly influencing detection capability. They will guide the design choices of a tailored UQ method, given the specificities of the application, in the form of open-access code.
The outgoing supervisor, a UQ expert, and the returning one, skilled in applying ML to real-world scientific applications, will help the PF grow into an independent researcher.
This interdisciplinary project will also benefit the industry through a concrete exploitation plan, targeting France's main electricity producer and supplier, and a public-private consortium working with 16 hospitals to improve the care of severe trauma patients. The communication plan will directly contribute to raising public awareness of the possibilities for robust ML.
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.
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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)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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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.
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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-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships
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(opens in new window) HORIZON-MSCA-2025-PF
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78153 Le Chesnay Cedex
France
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