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NoBIAS SIGNED

Artificial Intelligence without Bias

Total Cost €

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EC-Contrib. €

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Partnership

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 NoBIAS project word cloud

Explore the words cloud of the NoBIAS project. It provides you a very rough idea of what is the project "NoBIAS" about.

credit    solutions    anytime    rights    reaching    transparency    compliance    move    individuals    innovation    bias    employed    medical    media    consultancy    good    everywhere    embed    telecommunication    provenance    practical    academia    nowadays    artificial    deployment    collected    cohort    nobias    biases    decision    people    law    government    expertise    capacity    marketing    esrs    counter    benefiting    head    ai    machine    worse    predictive    performance    variety    algorithms    stage    stages    arise    soft    industry    optimized    unfairly    skills    leadership    denied    sectors    disciplinary    15    principles    learning    risks    considerations    impacts    computer    start    fairness    automatically    acquire    news    miss    treating    turn    intelligence    understand    train    core    decisions    human    document    treatment    software    entailing    give    contravene    job    finance    society    ethical    social    training    everyone    interdisciplinary    broadly    data    underperform    chances    businesses    science   

Project "NoBIAS" data sheet

The following table provides information about the project.

Coordinator
GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET HANNOVER 

Organization address
address: Welfengarten 1
city: HANNOVER
postcode: 30167
website: www.uni-hannover.de

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Germany [DE]
 Total cost 3˙994˙775 €
 EC max contribution 3˙994˙775 € (100%)
 Programme 1. H2020-EU.1.3.1. (Fostering new skills by means of excellent initial training of researchers)
 Code Call H2020-MSCA-ITN-2019
 Funding Scheme MSCA-ITN-ETN
 Starting year 2020
 Duration (year-month-day) from 2020-01-01   to  2023-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET HANNOVER DE (HANNOVER) coordinator 758˙365.00
2    UNIVERSITY OF SOUTHAMPTON UK (SOUTHAMPTON) participant 909˙517.00
3    UNIVERSITA DI PISA IT (PISA) participant 522˙999.00
4    GESIS-LEIBNIZ-INSTITUT FUR SOZIALWISSENSCHAFTEN EV DE (MANNHEIM) participant 505˙576.00
5    ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS EL (THERMI THESSALONIKI) participant 486˙035.00
6    THE OPEN UNIVERSITY UK (MILTON KEYNES) participant 303˙172.00
7    KATHOLIEKE UNIVERSITEIT LEUVEN BE (LEUVEN) participant 256˙320.00
8    SCHUFA HOLDING AG DE (WIESBADEN) participant 252˙788.00

Map

 Project objective

Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impacts on individuals and society. Their decisions might affect everyone, everywhere and anytime entailing risks, such as being denied a credit, a job, a medical treatment, or specific news. Businesses might miss chances, because biases make AI-driven decisions underperform; much worse, they may contravene human rights when treating people unfairly. Bias may arise at all stages of AI-based decision making processes: (i) when data is collected, (ii) when algorithms turn data into decision making capacity, or (iii) when results of decision making are used in applications. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in the training, design and deployment of AI algorithms to ensure social good while still benefiting from the potential of AI. NoBIAS will develop novel methods for AI-based decision making without bias by taking into account ethical and legal considerations in the design of technical solutions. The core objectives of NoBIAS are to understand legal, social and technical challenges of bias in AI-decision making, to counter them by developing fairness-aware algorithms, to automatically explain AI results, and to document the overall process for data provenance and transparency. We will train a cohort of 15 ESRs (Early-Stage Researchers) to address problems with bias through multi-disciplinary training and research in computer science, data science, machine learning, law and social science. ESRs will acquire practical expertise in a variety of sectors from telecommunication, finance, marketing, media, software, and legal consultancy to broadly foster legal compliance and innovation. Technical, interdisciplinary and soft-skills will give ESRs a head start towards future leadership in industry, academia, or government.

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The information about "NOBIAS" are provided by the European Opendata Portal: CORDIS opendata.

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lastchecktime (2020-10-24 17:28:32) correctly updated