Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Cadmus, EUI Research...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
SSRN Electronic Journal
Article . 2025 . Peer-reviewed
Data sources: Crossref
versions View all 2 versions
addClaim

Extrajudicial and Judicial Remedies in Algorithm-Assisted Decision-Making: The Case of EU IT Systems for Migration and Security

Authors: KARAISKOU, Alexandra; VAVOULA, Niovi;

Extrajudicial and Judicial Remedies in Algorithm-Assisted Decision-Making: The Case of EU IT Systems for Migration and Security

Abstract

This paper aims to examine the challenges posed by the introduction of algorithm-assisted decision-making in the forms of profiling and automated data matching in interoperable EUwide large-scale IT systems vis-à-vis accesss to extrajudicial and judicial remedies. Focus is placed on two EU-wide large-scale IT systems processing personal data of third-country nationals, namely the European Travel Information and Authorisation Systems (ETIAS) and the Visa Information Systems (VIS), both of which will employ algorithms to assist in the examination of applications for visas and travel authorisations. The paper critically assesses the effectiveness of existing safeguards contained in the underlying legal framework in light of European and international efforts to regulate Artificial Intelligence (AI) and the relevant case law of the Court of Justice of the European Union (CJEU). In particular, it looks into the opportunities for short-stay travellers subject to ETIAS or VIS rules to exercise the individual rights under EU data protection law, which are vital considering that their personal data will be used for automated data matching against other European and international databases. It further examines the extent to which the output informed by algorithms can be effectively challenged before courts by looking into the information that the individual will receive following a negative decision on their application for travel authorisation and visas. By doing so, this paper makes a threefold contribution. Firstly, it provides a taxonomy of extrajudicial and judicial remedies provided by EU data protection and administrative law as well as the AI Act. Secondly, it offers an in-depth assessment of the remedial mechanisms foreseen by the ETIAS and revised VIS rules. Thirdly, it highlights important shortcomings of the relevant rules and suggests possible solutions. The paper concludes that the EU’s eagerness to employ advanced technologies in the field of migration management raises significant challenges for individuals affected, as they will have limited and ineffective extrajudicial and judicial remedies, which are not sufficiently adjusted to the new algorithm-assisted era of migration decision-making.

Country
Italy
Related Organizations
Keywords

Machine Learning, Artificial Intelligence (AI), Algorithmic decision-making, Interoperability, EU large-scale IT systems

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
Related to Research communities