SOURCE-LINKED INTELLIGENCE

Multi-Attribute, Multimodal Bias Mitigation in AI Systems

CORDIS · observation · Publication date unknown

Multi-Attribute, Multimodal Bias Mitigation in AI Systems Artificial Intelligence (AI) is increasingly employed by businesses, governments, and other organizations to make decisions with far-reaching impacts on individuals and society. This offers big opportunities for automation in different sectors and daily life, but at the same time it brings risks for discrimination of minority and marginal population groups on the basis of the so-called protected attributes, like gender, race, and age. Despite the large body of research to date, the proposed methods work in limited settings, under very constrained assumptions, and do not reflect the complexity and requirements of real world applications. To this end, the MAMMOth project focuses on multi-discrimination mitigation for tabular, network and multimodal data. Through its computer science and AI experts, MAMMOth aims at addressing the associated scientific challenges by developing an innovative

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recordType

award

status

SIGNED

region

EU

value

3304975

unit

EUR