Law Enforcement and Data-Driven Predictions at the National and EU Level

  • Galli F
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Abstract

Technologies have always led to turning points for social development. In the past, different technologies have opened the doors towards new phase of growth and change while influencing social values and principles. Algorithmic technologies fit within this framework. Although these technologies have positive effects for the entire society by increasing the capacity of individuals to exercise rights and freedoms, they have also led to new constitutional challenges. The opportunities of new algorithmic technologies clash with the troubling opacity and lack of accountability. We believe that constitutional law plays a critical role to address the challenges of the algorithmic society. New technologies have always challenged, if not disrupted, the social, economic legal and, to an extent, the ideological status quo. Such transformations impact constitutional values, as the state formulates its legal response to the new technologies based on constitutional principles which meet market dynamics, and as it considers its own use of technologies in light of the limitation imposed by constitutional safeguards. The primary goal of this chapter is to introduce the constitutional challenges coming from the rise of the algorithmic society. The first part of this work examines the challenges for fundamental rights and democratic values with a specific focus on the right to freedom of expression, privacy and data protection. The second part looks at the role of constitutional law in relation to the regulation and policy of the algorithmic society. The third part examines the role and responsibilities of private actors underlining the role of constitutional law in this field. The fourth part deals with the potential remedies which constitutional law can provide to face the challenges of the information society

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APA

Galli, F. (2021). Law Enforcement and Data-Driven Predictions at the National and EU Level. In Constitutional Challenges in the Algorithmic Society (pp. 111–128). Cambridge University Press. https://doi.org/10.1017/9781108914857.008

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