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FINDHR

Financiado

Cerrado

Fairness and Intersectional Non Discrimination in Human Recommendation

FINDHR is an interdisciplinary project that seeks to prevent, detect, and mitigate discrimination in AI. Our research will be contextualized within the technical, legal, and ethical problems of algorithmic hiring and the domain of... ver más

31/10/2025

UPF

3M€

Presupuesto del proyecto: 3M€

Líder del proyecto

UNIVERSITAT POMPEU FABRA No se ha especificado una descripción o un objeto social para esta compañía.

Total investigadores 322

Fecha límite participación Sin fecha límite de participación.

Ver 14 Participantes

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2022-06-20

HORIZON-CL4-2021-HUMAN-01-24: Tackling gender, race and other bia... ExpectedOutcome:Proposal results are expected to contribute to the following expected outcomes:

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

14 Participantes

UPF

709.84K€ | Lider

BELSPO

307.86K€ | Participante

ETICAS RESEARCH AND CONSULTI...

117.45K€ | Participante

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Duración del proyecto: 40 meses Fecha Inicio: 2022-06-20
Fecha Fin: 2025-10-31

Líder del proyecto

UNIVERSITAT POMPEU FABRA No se ha especificado una descripción o un objeto social para esta compañía.

Total investigadores 322

Presupuesto del proyecto 3M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto FINDHR is an interdisciplinary project that seeks to prevent, detect, and mitigate discrimination in AI. Our research will be contextualized within the technical, legal, and ethical problems of algorithmic hiring and the domain of human resources, but will also show how to manage discrimination risks in a broad class of applications involving human recommendation. Through a context-sensitive, interdisciplinary approach, we will develop new technologies to measure discrimination risks, to create fairness-aware rankings and interventions, and to provide multi-stakeholder actionable interpretability. We will produce new technical guidance to perform impact assessment and algorithmic auditing, a protocol for equality monitoring, and a guide for fairness-aware AI software development. We will also design and deliver specialized skills training for developers and auditors of AI systems. We ground our project in EU regulation and policy. As tackling discrimination risks in AI requires processing sensitive data, we will perform a targeted legal analysis of tensions between data protection regulation (including the GDPR) and anti-discrimination regulation in Europe. We will engage with underrepresented groups through multiple mechanisms including consultation with experts and participatory action research. In our research, technology, law, and ethics are interwoven. The consortium includes leaders in algorithmic fairness and explainability research (UPF, UVA, UNIPI, MPI-SP), pioneers in the auditing of digital services (AW, ETICAS), and two industry partners that are leaders in their respective markets (ADE, RAND), complemented by experts in technology regulation (RU) and cross-cultural digital ethics (EUR), as well as worker representatives (ETUC) and two NGOs dedicated to fighting discrimination against women (WIDE+) and vulnerable populations (PRAK). All outputs will be released as open access publications, open source software, open datasets, and open courseware.

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