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Bayesian Models and Algorithms for Fairness and Transparency

Project description

Novel Bayesian approach for fair, lawful and transparent data processing

The General Data Protection Regulation (GDPR) states data should be processed lawfully, fairly and transparently. With this in mind, the EU-funded BayesianGDPR project aims to integrate the legal non-discriminatory principles of GDPR into automated machine-learning systems in a transparent manner. It will do so by using a novel Bayesian approach to model all sources of uncertainty, and taking into account feedback from humans and future consequences of their outputs. BayesianGDPR will provide organisations that rely on machine learning technologies with concrete tools allowing them compliance with the non-discriminatory principles of GDPR and similar laws. The project's achievements will have an impact on computational law research and its integration into mainstream legal practice. It will also promote public confidence in machine learning systems.

Host institution

THE UNIVERSITY OF SUSSEX
Net EU contribution
€ 1 329 947,00
Address
Sussex House Falmer
BN1 9RH Brighton
United Kingdom

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Region
South East (England) Surrey, East and West Sussex Brighton and Hove
Activity type
Higher or Secondary Education Establishments
Other funding
€ 0,00

Beneficiaries (2)

THE UNIVERSITY OF SUSSEX
United Kingdom
Net EU contribution
€ 1 329 947,00
Address
Sussex House Falmer
BN1 9RH Brighton

See on map

Region
South East (England) Surrey, East and West Sussex Brighton and Hove
Activity type
Higher or Secondary Education Establishments
Other funding
€ 0,00
BCAM - BASQUE CENTER FOR APPLIED MATHEMATICS
Spain
Net EU contribution
€ 113 750,00
Address
Al Mazarredo 14
48009 Bilbao

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Region
Noreste País Vasco Bizkaia
Activity type
Research Organisations
Other funding
€ 0,00