Opendata, web and dolomites

NoBIAS SIGNED

Artificial Intelligence without Bias

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 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.

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

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.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "NOBIAS" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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

More projects from the same programme (H2020-EU.1.3.1.)

GMOS-Train (2020)

Global Mercury Observation and Training Network in Support to the Minamata Convention

Read More  

I-DireCT (2019)

Immune DIREcted and Cancer-selective immunoTherapy

Read More  

FutureArctic (2019)

A glimpse into the Arctic future: equipping a unique natural experiment for next-generation ecosystem research

Read More