Project description
Researching the impact of AI on human rights and equality
Is the legal framework for equality protection in the EU adapted to, and capable of, tackling algorithmic discrimination? The EU-funded PROFILE project aims to address this issue by advancing socio-legal research on the impact of AI on human rights, and in particular equality and non-discrimination. Specifically, it will study two key issues: how algorithmic profiling increases risks of inequality and discrimination, and how algorithmically induced discrimination risks escaping the neat legal categories of discrimination law. The PROFILE project will therefore explore how these new forms of technology-driven discrimination disrupt and challenge the EU’s anti-discrimination legal framework, and will consider which regulatory solutions can be proposed.
Objective
As the number and reach of artificial intelligence (AI) applications are rapidly growing, empirical evidence and global awareness about the structural and systemic risks of discrimination (‘algorithmic bias’) linked to these technologies have increased over the past years. One AI technology has attracted particular attention: based on data mining, algorithmic profiling uses big data to target citizens based on their preferences, behaviors, but also social membership and status. In so doing, algorithms externally and autonomously ascribe profiles to citizens based on fragments of data. The algorithms freeze citizens’ identities and exacerbate their differences, thus shaping their reality by affecting the distribution of goods, services, and opportunities available. The PROFILE project address two key issues related to AI: 1) algorithmic profiling increases risks of inequality and discrimination and, 2) algorithmic data-based discrimination takes on different forms than human discrimination, thus casting doubt on the adequateness of existing legal remedies. These issues forms the base for PROFILE’s core research question: Is the legal framework for equality protection in the European Union (EU) adapted to and capable of tackling algorithmic discrimination? I will address the problem of algorithmic discrimination through three central inquiries: 1) How does algorithmic discrimination differ from human discrimination? 2) How do these new forms of technology-driven discrimination disrupt and challenge the anti-discrimination legal framework in place in EU? 3) What regulatory solutions can be proposed within and outside EU anti-discrimination law in order to efficiently remedy algorithmic discrimination? My ambition is both to advance legal research on AI and human rights and to concretely inform societal and policy responses to the challenge of AI regulation. The proposed project is highly topical in the light of the rapid development and use of AI applications.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence
- natural sciences computer and information sciences data science big data
- natural sciences computer and information sciences data science data mining
- social sciences sociology social issues social inequalities
- social sciences law human rights
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2019
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
1165 KOBENHAVN
Denmark
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.