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EXUS as partner

Multi-Attribute, Multimodal Bias Mitigation in AI Systems

Adding fairness and mitigating bias in AI

Artificial intelligence (AI) offers great promise for solving business and social problems, but it also risks inadvertently discriminating against minority and marginalised groups. The EU-funded MAMMOth project tackles this bias by focusing on multi-discrimination mitigation for tabular, network and multimodal data.

Numbers

11/2022 - 10/2025

Project duration

3,304,975,00 €

Overall Budget

CL4-2021-HUMAN-01-24

Topic

Impact

Working with computer science and AI experts, the project will create tools for fairness-aware AI which ensure accountability with respect to protected attributes like gender, race and age. The project will also engage with communities of vulnerable and/or underrepresented groups in AI research to ensure that user needs and pains are truly at the centre of the agenda. The end goal is to develop pilot projects for finance/loan applications, identity verification and academic evaluation

ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS (Greece)

UNIVERSITAET DER BUNDESWEHR MUENCHEN (Germany)

COMPLEXITY SCIENCE HUB VIENNA CSH -VEREIN ZUR FORDERUNG WISSENSCHAFTLIWISSENSCHAFTLICHER FORSCHUNG IM BEREICH KOMPLEXER SYSTEME (Austria)

ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA (Italy)

Partners

RIJKSUNIVERSITEIT GRONINGEN (Netherlands)

EXUS SOFTWARE MONOPROSOPI ETAIRIA PERIORISMENIS EVTHINIS (Greece)

TRILATERAL RESEARCH LIMITED (Ireland)

ARIADNEXT (France)

CSI CENTER FOR SOCIAL INNOVATION LTD (Cyprus)

ASSOCIACIO FORUM DONA ACTIVA 2010 (Spain)

VSI DIVERSITY DEVELOPMENT GROUP (Lithuania)

IASIS (Greece)

Partners

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