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Project: Fair, Effective, and Sustainable Talent Management using Conditional Network Embedding

2021-04-01 – 2022-09-30


The ongoing industrial revolution poses significant challenges to the job market regarding upskilling and re-education, job-matching, curriculum advice, strategic workforce management, and more. To help tackle these challenges, the conditional network embedding (CNE) method enables the building of an innovative AI platform that unifies the diverse information related to human talent and the job market. This platform is naturally capable of compensating any existing biases in the data, thus avoiding unfairness or discrimination when it is deployed. The EU-funded proof-of-concept FEAST project will leverage results from the European Research Council project FORSIED and develop this platform in close collaboration with the private and public sectors. FEAST will evaluate the platform, investigate the intellectual property rights and conduct a market study.

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