Law and Technology

"Turn yourself into a Data Head. You'll become a more valuable employee and make your organization more successful." Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI Advantage You've heard the hype around data--now get the facts. In Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning, award-winning data scientists Alex Gutman and Jordan Goldmeier pull back the curtain on data science and give you the language and tools necessary to talk and think critically about it. You'll learn how to: Think statistically and understand the role variation plays in your life and decision making Speak intelligently and ask the right questions about the statistics and results you encounter in the workplace Understand what's really going on with machine learning, text analytics, deep learning, and artificial intelligence Avoid common pitfalls when working with and interpreting data Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you'll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently readable book. Anyone can become a Data Head--an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

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Litigating Artificial Intelligence is the first resource of its kind in Canada to comprehensively review the diverse ways AI can interact with the litigation process, both in the courtroom and in legal practice. Presenting a realistic, even-handed treatment of the latest developments in AI and law, the General Editor team and expert contributors address four primary ways litigators can expect AI to influence their work: 1) challenging AI-informed decision-making 2) navigating evidence law questions arising from AI 3) bringing or defending lawsuits involving AI-based products and 4) using AI tools to enhance aspects of legal practice.

Data analytics may seem daunting, but if you're an experienced Excel user, you have a unique head start. With this hands-on guide, intermediate Excel users will gain a solid understanding of analytics and the data stack. By the time you complete this book, you'll be able to conduct exploratory data analysis and hypothesis testing using a programming language. Exploring and testing relationships are core to analytics. By using the tools and frameworks in this book, you'll be well positioned to continue learning more advanced data analysis techniques. Author George Mount, founder and CEO of Stringfest Analytics, demonstrates key statistical concepts with spreadsheets, then pivots your existing knowledge about data manipulation into R and Python programming. This practical book guides you through: Foundations of analytics in Excel: Use Excel to test relationships between variables and build compelling demonstrations of important concepts in statistics and analytics From Excel to R: Cleanly transfer what you've learned about working with data from Excel to R From Excel to Python: Learn how to pivot your Excel data chops into Python and conduct a complete data analysis

By taking a close look at both the risks and potential inherent in AI technologies, Artificial Intelligence and the Law in Canada provides valuable insight into the current state of AI in Canada as well as how the technology interacts with traditional areas of law, including intellectual property, contracts, torts, data protection, competition, administrative and health. This book illustrates the range of legal and public policy challenges related to AI that Canada faces.

Algorithms permeate our lives in numerous ways, performing tasks that until recently could only be carried out by humans. Artificial Intelligence (AI) technologies, based on machine learning algorithms and big-data-powered systems, can perform sophisticated tasks such as driving cars, analyzing medical data, and evaluating and executing complex financial transactions - often without active human control or supervision. Algorithms also play an important role in determining retail pricing, online advertising, loan qualification, and airport security. In this work, Martin Ebers and Susana Navas bring together a group of scholars and practitioners from across Europe and the US to analyze how this shift from human actors to computers presents both practical and conceptual challenges for legal and regulatory systems. This book should be read by anyone interested in the intersection between computer science and law, how the law can better regulate algorithmic design, and the legal ramifications for citizens whose behavior is increasingly dictated by algorithms.

The field of artificial intelligence (AI) and the law is on the cusp of a revolution that began with text analytic programs like IBM's Watson and Debater and the open-source information management architectures on which they are based. Today, new legal applications are beginning to appear and this book - designed to explain computational processes to non-programmers - describes how they will change the practice of law, specifically by connecting computational models of legal reasoning directly with legal text, generating arguments for and against particular outcomes, predicting outcomes and explaining these predictions with reasons that legal professionals will be able to evaluate for themselves. These legal applications will support conceptual legal information retrieval and allow cognitive computing, enabling a collaboration between humans and computers in which each does what it can do best. Anyone interested in how AI is changing the practice of law should read this illuminating work.

The field of artificial intelligence has made tremendous advances in the last few decades, but as smart as AI is now, it is getting exponentially smarter and becoming more autonomous in its actions. This raises a host of challenges to current legal doctrine, including whether the output of AI entities should count as 'speech', the extent to which AI should be regulated under antitrust and criminal law statutes, and whether AI should be considered an independent agent and responsible for its actions under the law of tort or agency. Containing chapters written by leading U.S., EU, and International law scholars, the Research Handbook presents current law, statutes, and regulations on the role of law in an age of increasingly smart AI, addressing issues of law that are critical to the evolution of AI and its role in society. To provide a broad coverage of the topic, the Research Handbook draws upon free speech doctrine, criminal law, issues of data protection and privacy, legal rights for increasingly smart AI systems, and a discussion of jurisdiction for AI entities that will not be "content" to stay within the geographical boundaries of any nation state or be tied to a particular physical location. Using numerous examples and case studies, the chapter authors discuss the political and jurisdictional decisions that will have to be made as AI proliferates into society and transforms our government and social institutions. The Research Handbook will also introduce designers of artificially intelligent systems to the legal issues that apply to the make-up and use of AI from the technologies, algorithms, and analytical techniques. This essential guide to the U.S., EU, and other International law, regulations, and statutes which apply to the emerging field of "law and AI"will be a valuable reference for scholars and students interested in information and intellectual property law, privacy, and data protection as well as to legal theorists and social scientists who write about the future direction and implications of AI. The Handbook will also serve as an important reference for legal practitioners in different jurisdictions who may litigate disputes involving AI, and to computer scientists and engineers actively involved in the design and use of the next generation of AI systems.

In an era of corporate surveillance, artificial intelligence, deep fakes, genetic modification, automation, and more, law often seems to take a back seat to rampant technological change. To listen to Silicon Valley barons, there's nothing any of us can do about it. In this riveting work, Joshua A. T. Fairfield calls their bluff. He provides a fresh look at law, at what it actually is, how it works, and how we can create the kind of laws that help humans thrive in the face of technological change. He shows that law can keep up with technology because law is a kind of technology - a social technology built by humans out of cooperative fictions like firms, nations, and money. However, to secure the benefits of changing technology for all of us, we need a new kind of law, one that reflects our evolving understanding of how humans use language to cooperate.

This book offers a toolkit for harnessing AI in the practice of law and for optimizing AI by society as a whole. This is ... [a] study of how AI will dramatically affect the law, both as a profession and a regulatory domain, as well as society at large