General Laws of the State of Vermont Relating to Railroads
Title | General Laws of the State of Vermont Relating to Railroads PDF eBook |
Author | Vermont |
Publisher | |
Pages | 76 |
Release | 1895 |
Genre | Railroad law |
ISBN |
The Federal Reserve Act (approved December 23, 1913) as Amended
Title | The Federal Reserve Act (approved December 23, 1913) as Amended PDF eBook |
Author | United States |
Publisher | |
Pages | 114 |
Release | 1920 |
Genre | Banking law |
ISBN |
Public Documents of Massachusetts
Title | Public Documents of Massachusetts PDF eBook |
Author | Massachusetts |
Publisher | |
Pages | 1150 |
Release | 1898 |
Genre | |
ISBN |
Acts and Resolutions of the General Assembly
Title | Acts and Resolutions of the General Assembly PDF eBook |
Author | |
Publisher | |
Pages | 686 |
Release | 1831 |
Genre | Law |
ISBN |
The Laws of the State of Vermont
Title | The Laws of the State of Vermont PDF eBook |
Author | Vermont |
Publisher | |
Pages | 526 |
Release | 1808 |
Genre | Law |
ISBN |
A Selection of Cases on the Law of Private Corporations
Title | A Selection of Cases on the Law of Private Corporations PDF eBook |
Author | Leslie Jay Tompkins |
Publisher | |
Pages | 1172 |
Release | 1908 |
Genre | Corporation law |
ISBN |
Regulating Artificial Intelligence
Title | Regulating Artificial Intelligence PDF eBook |
Author | Thomas Wischmeyer |
Publisher | Springer Nature |
Pages | 391 |
Release | 2019-11-29 |
Genre | Law |
ISBN | 3030323617 |
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.