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CELS guest research webinar: dr Joanna Mazur (University of Warsaw) 'Automated Decision-Making Systems as a Challenge for Effective Legal Protection in EU law'


Event details

Abstract

The hypothesis of this article is that algorithms used for automated decision-making (ADM) should be subject to the right to access information when their implementation impacts areas crucial for the EU’s legal order. The analysis of the Court of Justice of the European Union (CJEU)’s case law shows that access to information is a prerequisite for assessing the compliance of the judiciary’s organisation with EU values. The example of the Polish system of case allocation presented in the article illustrates how the implementation of ADM in the judiciary can hinder the possibilities to receive information on its organisation and assess the extent of judicial independence. However, the current interpretation of the right to access information in EU law does not allow for considering this right as a solution facilitating the assessment of compliance with the effective legal protection standards. The article presents the consequences of this interpretation and proposes an alternative approach.

Dr Joanna Mazur (analyst at DeLab, University of Warsaw, Poland), will be speaking on the topic of 'Automated Decision-Making Systems as a Challenge for Effective Legal Protection in EU law'. Our guest speaker has recently published on this topic in the European Law Review (2021, issue 2), but generally has many publications on this topic, and a grant to further pursue it.

At DELab UW, she works on analyzing the legal aspects of building a digital single market, primarily personal data protection and copyright initiatives. She is also interested in issues of human rights protection in the digital space. Please find below the abstract of her paper.

The webinar will take place on Zoom. Again please feel free to invite your students to participate in this research meeting.

Join Zoom Meeting
https://Universityofexeter.zoom.us/j/93682158494?pwd=Nk1JeEE5aElKc0pFUHZyRFErNG5mQT09

Meeting ID: 936 8215 8494
Password: 500499