A Blueprint For The Regulation Of Artificial Intelligence Technologies

The technology of Artificial Intelligence is here, and moving fast, without ethical standards in place. A Blueprint for the Regulation of Artificial Intelligence Technologies leans on classical western philosophy for its ethical grounding. Values such as conscience, rights, equity, and discrimination, establish a basis for regulatory standards. Multiple international agencies with governing interests are compared. The development of ethical standards is suggested through two new non-governmental organizations (NGOs). The first is to develop standards that evolve from practice, while the second acts as an ombudsman to settle abuse. Both NGOs are envisioned to cooperate with regulators. More than seeking a perfect solution, the book aims to balance the tension between conflicting interests, with the goal to keep this dangerously wonderful technology under global human control. For that to materialize, the technology needs to have a seat on the table of global ethics. The final chapter lists fourteen thinking points to achieve an ethics balance for new technologies.

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.

What Is Artificial Intelligence Regulation The establishment of public sector policies and rules for developing and regulating artificial intelligence (AI) is what constitutes the regulation of artificial intelligence (AI); as a result, AI regulation is related to the more general regulation of algorithms. The legal and policy landscape for artificial intelligence is a developing topic in jurisdictions all over the world, notably in the European Union and in supranational groups like the IEEE and the OECD, amongst others. In an effort to keep society in control of artificial intelligence technology, a wave of AI ethical guidelines has been issued from the year 2016. Regulation is seen as important in order to both foster artificial intelligence and manage the risks connected with it. In addition to government regulation, AI-deploying enterprises need to play a central role in developing and deploying trustworthy AI in accordance with the principles of trustworthy AI, and they also need to take responsibility for minimizing the associated risks. Regulation of artificial intelligence using systems such as review boards is one example of a social means approach to solving the problem of AI control. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Regulation of artificial intelligence Chapter 2: Artificial intelligence Chapter 3: Ethics of artificial intelligence Chapter 4: Machine ethics Chapter 5: Regulation of algorithms Chapter 6: Artificial Intelligence Act Chapter 7: Automated decision-making Chapter 8: AI safety Chapter 9: Government by algorithm Chapter 10: Artificial intelligence arms race (II) Answering the public top questions about artificial intelligence regulation. (III) Real world examples for the usage of artificial intelligence regulation in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of artificial intelligence regulation' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of artificial intelligence regulation.

Exploring potential scenarios of artificial intelligence regulation which prevent automated reality harming individual human rights or social values, this book reviews current debates surrounding AI regulation in the context of the emerging risks and accountabilities. Considering varying regulatory methodologies, it focuses mostly on EU’s regulation in light of the comprehensive policy making process taking place at the supranational level. Taking an ethics and humancentric approach towards artificial intelligence as the bedrock of future laws in this field, it analyses the relations between fundamental rights impacted by the development of artificial intelligence and ethical standards governing it. It contains a detailed and critical analysis of the EU’s Ethic Guidelines for Trustworthy AI, pointing at its practical applicability by the interested parties. Attempting to identify the most transparent and efficient regulatory tools that can assure social trust towards AI technologies, the book provides an overview of horizontal and sectoral regulatory approaches, as well as legally binding measures stemming from industries’ self-regulations and internal policies.

This timely book provides an extensive overview and analysis of the law and regulation as it applies to the technology and uses of Artificial Intelligence (AI). It examines the human and ethical concerns associated with the technology, the history of AI and AI in commercial contexts.

This provocative and timely book identifies and disrupts the conventional regulation and governance discourses concerning AI and big data. It suggests that, instead of being used as tools for exclusionist commercial markets, AI and big data can be employed in governing digital transformation for social good.

Can the law keep up with AI? This book examines liability and regulation for artificial intelligence causing serious physical harm, both now and in the future. While AI moves quickly, regulation follows more slowly - an increasing problem for an evolutionary, fast-paced emerging technology. AI has the potential to save lives, but in doing so will have the potential to take them as well. How do we future-proof law and regulation to incentivise life-saving innovation as safely as possible? This book details how to regulate AI in high-risk civil applications (for example automated vehicles and medicine), addressing both liability and regulatory structure. It highlights crucial liability themes for technology governance; provides tools to bridge the gap between regulators and technologists; examines jurisdictional approaches to AI regulation in the EU, UK, USA, and Singapore; and ultimately suggests a jurisdiction-agnostic blueprint for regulation.