The use of automated systems to reach a decision is increasingly widespread, and more and more automated systems have been involved in the formulation of decisions that have a significant impact on individual and collective lives, especially since the beginning of the COVID-19 pandemic. Automation in decision-making has proved to be able to produce extremely positive results in terms of greater efficiency and speed in decision-making, but often conceals the risk of discrimination, longstanding and newly minted.Based on an analytical examination of the legal provisions on the subject and a close comparison with the stances of law scholars, and the European Court of Justice jurisprudence, the study examines the topic of discriminatory automated decisions in the light of data protection law, in order to ascertain whether the European General Data Protection Regulation (GDPR) provides effective tools for counteracting them.

The Bad Algorithm. Automated Discriminatory Decisions in the European General Data Protection Regulation

Alfio Guido Grasso
2022

Abstract

The use of automated systems to reach a decision is increasingly widespread, and more and more automated systems have been involved in the formulation of decisions that have a significant impact on individual and collective lives, especially since the beginning of the COVID-19 pandemic. Automation in decision-making has proved to be able to produce extremely positive results in terms of greater efficiency and speed in decision-making, but often conceals the risk of discrimination, longstanding and newly minted.Based on an analytical examination of the legal provisions on the subject and a close comparison with the stances of law scholars, and the European Court of Justice jurisprudence, the study examines the topic of discriminatory automated decisions in the light of data protection law, in order to ascertain whether the European General Data Protection Regulation (GDPR) provides effective tools for counteracting them.
978-88-495-5023-8
GDPR; automated decisions; automated decision-making; discriminations; profiling; credit scoring
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/538060
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