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Fairness and Intersectional Non-Discrimination in Human Recommendation

Project description

DEENESFRITPL

Dealing with discrimination in algorithmic hiring

Algorithmic hiring is the usage of tools based on Artificial intelligence (AI) for finding and selecting job candidates. As other applications of AI, it is vulnerable to perpetuate discrimination. Considering technological, legal, and ethical aspects, the EU-funded FINDHR project will facilitate the prevention, detection, and management of discrimination in algorithmic hiring and closely related areas involving human recommendation. FINDHR aims to create new ways to ascertain discrimination risk, produce less biased outcomes, and meaningfully incorporate human expertise. Moreover, it aims to create procedures for software development, monitoring and training. On completion, the project’s publications, software, courseware and datasets will be made freely available to the public under free and open licenses.

Objective

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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Programme(s)

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Call for proposal

HORIZON-CL4-2021-HUMAN-01

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Funding Scheme

RIA - Research and Innovation action

Coordinator

UNIVERSIDAD POMPEU FABRA
Net EU contribution
€ 709 838,00
Address
Placa de la merce, 10-12
08002 Barcelona
Spain

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Region
Este Cataluña Barcelona
Activity type
Higher or Secondary Education Establishments
Links
Other funding
€ 0,00

Participants (11)

Partners (1)

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EC signature date 20 June 2022
Last update: 4 September 2022

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Permalink: https://cordis.europa.eu/project/id/101070212

European Union, 2023