Download Free The Cambridge Handbook Of Private Law And Artificial Intelligence Book in PDF and EPUB Free Download. You can read online The Cambridge Handbook Of Private Law And Artificial Intelligence and write the review.

AI appears to disrupt key private law doctrines, and threatens to undermine some of the principal rights protected by private law. The social changes prompted by AI may also generate significant new challenges for private law. It is thus likely that AI will lead to new developments in private law. This Cambridge Handbook is the first dedicated treatment of the interface between AI and private law, and the challenges that AI poses for private law. This Handbook brings together a global team of private law experts and computer scientists to deal with this problem, and to examine the interface between private law and AI, which includes issues such as whether existing private law can address the challenges of AI and whether and how private law needs to be reformed to reduce the risks of AI while retaining its benefits.
Industrial consolidation, digital platforms, and changing political views have spurred debate about the interplay between public and private power in the United States and have created a bipartisan appetite for potential antitrust reform that would mark the most profound shift in US competition policy in the past half-century. While neo-Brandeisians call for a reawakening of antitrust in the form of a return to structuralism and a concomitant rejection of economic analysis founded on competitive effects, proponents of the status quo look on this state of affairs with alarm. Scrutinizing the latest evidence, Alan J. Devlin finds a middle ground. US antitrust laws warrant revision, he argues, but with far more nuance than current debates suggest. He offers a new vision of antitrust reform, achieved by refining our enforcement policies and jettisoning an unwarranted obsession with minimizing errors of economic analysis.
The technology and application of artificial intelligence (AI) throughout society continues to grow at unprecedented rates, which raises numerous legal questions that to date have been largely unexamined. Although AI now plays a role in almost all areas of society, the need for a better understanding of its impact, from legal and ethical perspectives, is pressing, and regulatory proposals are urgently needed. This book responds to these needs, identifying the issues raised by AI and providing practical recommendations for regulatory, technical, and theoretical frameworks aimed at making AI compatible with existing legal rules, principles, and democratic values. An international roster of authors including professors of specialized areas of law, technologists, and practitioners bring their expertise to the interdisciplinary nature of AI.
Algorithms are a fundamental building block of artificial intelligence - and, increasingly, society - but our legal institutions have largely failed to recognize or respond to this reality. The Cambridge Handbook of the Law of Algorithms, which features contributions from US, EU, and Asian legal scholars, discusses the specific challenges algorithms pose not only to current law, but also - as algorithms replace people as decision makers - to the foundations of society itself. The work includes wide coverage of the law as it relates to algorithms, with chapters analyzing how human biases have crept into algorithmic decision-making about who receives housing or credit, the length of sentences for defendants convicted of crimes, and many other decisions that impact constitutionally protected groups. Other issues covered in the work include the impact of algorithms on the law of free speech, intellectual property, and commercial and human rights law.
Businesses are rushing to collect personal data to fuel surging demand. Data enthusiasts claim personal information that's obtained from the commercial internet, including mobile platforms, social networks, cloud computing, and connected devices, will unlock path-breaking innovation, including advanced data security. By contrast, regulators and activists contend that corporate data practices too often disempower consumers by creating privacy harms and related problems. As the Internet of Things matures and facial recognition, predictive analytics, big data, and wearable tracking grow in power, scale, and scope, a controversial ecosystem will exacerbate the acrimony over commercial data capture and analysis. The only productive way forward is to get a grip on the key problems right now and change the conversation. That's exactly what Jules Polonetsky, Omer Tene, and Evan Selinger do. They bring together diverse views from leading academics, business leaders, and policymakers to discuss the opportunities and challenges of the new data economy.
Argues that treating people and artificial intelligence differently under the law results in unexpected and harmful outcomes for social welfare.
Exploring issues from big-data to robotics, this volume is the first to comprehensively examine the regulatory implications of AI technology.
Syntax – the study of sentence structure – has been at the centre of generative linguistics from its inception and has developed rapidly and in various directions. The Cambridge Handbook of Generative Syntax provides a historical context for what is happening in the field of generative syntax today, a survey of the various generative approaches to syntactic structure available in the literature and an overview of the state of the art in the principal modules of the theory and the interfaces with semantics, phonology, information structure and sentence processing, as well as linguistic variation and language acquisition. This indispensable resource for advanced students, professional linguists (generative and non-generative alike) and scholars in related fields of inquiry presents a comprehensive survey of the field of generative syntactic research in all its variety, written by leading experts and providing a proper sense of the range of syntactic theories calling themselves generative.
Artificial intelligence (AI) is becoming increasingly more prevalent in our daily social and professional lives. Although AI systems and robots bring many benefits, they present several challenges as well. The autonomous and opaque nature of AI systems implies that their commercialisation will affect the legal and regulatory framework.0In this comprehensive book, scholars critically examine how AI systems may impact Belgian law. It contains contributions on consumer protection, contract law, liability, data protection, procedural law, insurance, health, intellectual property, arbitration, lethal autonomous weapons, tax law, employment law, ethics,?While specific topics of Belgian private and public law are thoroughly addressed, the book also provides a general overview of a number of regulatory and ethical AI evolutions and tendencies in the European Union. Therefore, it is a must-read for legal scholars, practitioners and government officials as well as for anyone with an interest in law and AI.
This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term "A.I." is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether "human" or "A.I."