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This book assesses the normative and practical challenges for
artificial intelligence (AI) regulation, offers comprehensive
information on the laws that currently shape or restrict the design
or use of AI, and develops policy recommendations for those areas
in which regulation is most urgently needed. By gathering
contributions from scholars who are experts in their respective
fields of legal research, it demonstrates that AI regulation is not
a specialized sub-discipline, but affects the entire legal system
and thus concerns all lawyers. Machine learning-based technology,
which lies at the heart of what is commonly referred to as AI, is
increasingly being employed to make policy and business decisions
with broad social impacts, and therefore runs the risk of causing
wide-scale damage. At the same time, AI technology is becoming more
and more complex and difficult to understand, making it harder to
determine whether or not it is being used in accordance with the
law. In light of this situation, even tech enthusiasts are calling
for stricter regulation of AI. Legislators, too, are stepping in
and have begun to pass AI laws, including the prohibition of
automated decision-making systems in Article 22 of the General Data
Protection Regulation, the New York City AI transparency bill, and
the 2017 amendments to the German Cartel Act and German
Administrative Procedure Act. While the belief that something needs
to be done is widely shared, there is far less clarity about what
exactly can or should be done, or what effective regulation might
look like. The book is divided into two major parts, the first of
which focuses on features common to most AI systems, and explores
how they relate to the legal framework for data-driven
technologies, which already exists in the form of (national and
supra-national) constitutional law, EU data protection and
competition law, and anti-discrimination law. In the second part,
the book examines in detail a number of relevant sectors in which
AI is increasingly shaping decision-making processes, ranging from
the notorious social media and the legal, financial and healthcare
industries, to fields like law enforcement and tax law, in which we
can observe how regulation by AI is becoming a reality.
This book assesses the normative and practical challenges for
artificial intelligence (AI) regulation, offers comprehensive
information on the laws that currently shape or restrict the design
or use of AI, and develops policy recommendations for those areas
in which regulation is most urgently needed. By gathering
contributions from scholars who are experts in their respective
fields of legal research, it demonstrates that AI regulation is not
a specialized sub-discipline, but affects the entire legal system
and thus concerns all lawyers. Machine learning-based technology,
which lies at the heart of what is commonly referred to as AI, is
increasingly being employed to make policy and business decisions
with broad social impacts, and therefore runs the risk of causing
wide-scale damage. At the same time, AI technology is becoming more
and more complex and difficult to understand, making it harder to
determine whether or not it is being used in accordance with the
law. In light of this situation, even tech enthusiasts are calling
for stricter regulation of AI. Legislators, too, are stepping in
and have begun to pass AI laws, including the prohibition of
automated decision-making systems in Article 22 of the General Data
Protection Regulation, the New York City AI transparency bill, and
the 2017 amendments to the German Cartel Act and German
Administrative Procedure Act. While the belief that something needs
to be done is widely shared, there is far less clarity about what
exactly can or should be done, or what effective regulation might
look like. The book is divided into two major parts, the first of
which focuses on features common to most AI systems, and explores
how they relate to the legal framework for data-driven
technologies, which already exists in the form of (national and
supra-national) constitutional law, EU data protection and
competition law, and anti-discrimination law. In the second part,
the book examines in detail a number of relevant sectors in which
AI is increasingly shaping decision-making processes, ranging from
the notorious social media and the legal, financial and healthcare
industries, to fields like law enforcement and tax law, in which we
can observe how regulation by AI is becoming a reality.
Das Recht der Informationssicherheit berührt Grundfragen
rechtsstaatlicher Regulierung unter den Bedingungen von
Digitalisierung und Globalisierung: Wie wirkt territorial
radiziertes Recht in der globalen Konstellation? Wie generiert der
Staat in einem hochdynamischen technischen Umfeld
Regulierungswissen? In welchem Verhältnis stehen Staat und
Private? Diese Fragen erfahren im Angesicht von Cyberbedrohungen
eine besondere Zuspitzung, ist die Gewährleistung von Sicherheit
doch Kernfunktion von Staatlichkeit und Indikator staatlicher
Souveränität. Vor diesem Hintergrund analysiert Thomas Wischmeyer
die Dimensionen der Aufgabe Informationssicherheit und entwickelt
dogmatische Bausteine eines Informationssicherheitsrechts. Dabei
lotet er aus, inwieweit die Bemühungen des Staates um die
Cybersicherheit mit seinen Bestrebungen kollidieren,
Sicherheitslücken für eigene Zwecke zu nutzen.
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