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Leading artificial intelligence (AI) developers and researchers, as well as government officials and policymakers, are investigating the harms that advanced AI systems might cause. In this report, the authors describe the basic features of U.S. tort law and analyze their significance for the liability of AI developers whose models inflict, or are used to inflict, large-scale harm. Highly capable AI systems are a growing presence in widely used consumer products, industrial and military enterprise, and critical societal infrastructure. Such systems may soon become a significant presence in tort cases as well--especially if their ability to engage in autonomous or semi-autonomous behavior, or their potential for harmful misuse, grows over the coming years. The authors find that AI developers face considerable liability exposure under U.S. tort law for harms caused by their models, particularly if those models are developed or released without utilizing rigorous safety procedures and industry-leading safety practices. At the same time, however, developers can mitigate their exposure by taking rigorous precautions and heightened care in developing, storing, and releasing advanced AI systems. By taking due care, developers can reduce the risk that their activities will cause harm to other people and reduce the risk that they will be held liable if their activities do cause such harm. The report is intended to be useful to AI developers, policymakers, and other nonlegal audiences who wish to understand the liability exposure that AI development may entail and how this exposure might be mitigated.
Initiated by the European Commission, the first study published in this volume analyses the largely unresolved question as to how damage caused by artificial intelligence (AI) systems is allocated by the rules of tortious liability currently in force in the Member States of the European Union and in the United States, to examine whether - and if so, to what extent - national tort law regimes differ in that respect, and to identify possible gaps in the protection of injured parties. The second study offers guiding principles for safety and liability with regard to software, testing how the existing acquis needs to be adjusted in order to adequately cope with the risks posed by software and AI. The annex contains the final report of the New Technologies Formation of the Expert Group on Liability and New Technologies, assessing the extent to which existing liability schemes are adapted to the emerging market realities following the development of new digital technologies.
Artificial Intelligence (AI) based entities are already causing damages and fatalities in today's commercial world. As a result, the dispute about tort liability of AI-based machines, algorithms, agents and robots is exponentially advancing in the scholarly world and outside of it. When it comes to AI accidents, different scholars and key figures in the AI industry advocate for different liability regimes. This ever-growing disagreement is condemning this new emergent technology, soon to be found in almost every home and street in the US and around the world, into a realm of regulatory uncertainty. This obstructs our ability to fully enjoy the many benefits AI has to offer us as consumers and as a society.This Article advocates for the adoption and application of a strict liability regime on current and future AI accidents. It does so by delving into and exploring the realm of legal analogies in the AI context and promoting the agency analogy, and subsequently, the respondeat superior doctrine. This Article explains and justifies why the agency analogy is the best-suited one in contrast to other analogies which have been suggested in the context of AI liability (e.g., products, animals, electronic persons and even slaves). As a result, the intuitive application of the respondeat superior doctrine provides the AI industry with a much-needed underlying liability regime which will enable it to continue to evolve in the years to come, and its victim to receive remedy once accidents occur.
Argues that treating people and artificial intelligence differently under the law results in unexpected and harmful outcomes for social welfare.
When data from all aspects of our lives can be relevant to our health - from our habits at the grocery store and our Google searches to our FitBit data and our medical records - can we really differentiate between big data and health big data? Will health big data be used for good, such as to improve drug safety, or ill, as in insurance discrimination? Will it disrupt health care (and the health care system) as we know it? Will it be possible to protect our health privacy? What barriers will there be to collecting and utilizing health big data? What role should law play, and what ethical concerns may arise? This timely, groundbreaking volume explores these questions and more from a variety of perspectives, examining how law promotes or discourages the use of big data in the health care sphere, and also what we can learn from other sectors.
Asbestos litigation is the longest-running mass tort litigation in U.S. history. Through 2002, approximately 730,000 individuals have brought claims against some 8,400 business entities, and defendants and insurers have spent a total of $70 billion on litigation. Building on previous RAND briefings, the authors report on what happened to those who have claimed injury from asbestos, what happened to the defendants in those cases, and how lawyers and judges have managed the cases.
This report evaluates and models proposals for an insurance-based program to provide businesses with resources to maintain payroll and benefits and cover ongoing operating expenses during a pandemic.
Exploring issues from big-data to robotics, this volume is the first to comprehensively examine the regulatory implications of AI technology.
This Research Handbook considers many aspects of corporate liability, beginning with a fundamental explanation of what the company is, through depictions of corporate liability in theory, to the key areas of liability in practice. Interdisciplinary in nature, the contributions cover corporate and participant liability under statutory law, tort and criminal law, and corporate fiduciary and securities law. Specific perspectives include those on vicarious liability in tort and its application to corporations, and accountability for AI labour.