Search results for "Generative AI and Legal Profession"
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R 397.00
AI in Legal Tech
Explore the potential and risks of generative AI in the legal industry In AI in Legal Tech: How Generative AI Is Transforming Legal Technology and the Practice of Law, legal-tech pioneer and eDiscovery guru Catherine Casey—aka, TechnoCat—delivers a startlingly insightful and up-to-date discussion of the risks and opportunities presented by generative AI in the legal sector. The author walks you through generative AI's impact on the practice of law, legal ethics, and legal careers, offering guidance and clarity on a rapidly evolving technology. Balancing engaging narrative with expert analysis, AI in Legal Tech is written specifically for non-technical legal professionals and students doing their best to navigate the intersection of technology and law. You'll find: Explanations of how AI is shaping new legal careers and what you can do to find success in your ownA “Legal Tech Survival Kit,” complete with a comprehensive Legal AI glossary and must-try tools for tech-savvy lawyersInsights from the “front lines” of legal AI and the people designing the technologies shaping tomorrow's legal industry Perfect for practicing lawyers, law students, and law practice managers, AI in Legal Tech will also prove invaluable to legal technologists, paralegals, and anyone else interested in the application of the latest tech to the legal field.
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Artificial Intelligence and the Legal Profession
How are new technologies changing the practice of law?With examples and explanations drawn from the UK, US, Canada, Australia and other common law countries, as well as from China and Europe, this book considers the opportunities and implications for lawyers as artificial intelligence systems become commonplace in legal service delivery. It examines what lawyers do in the practice of law and where AI will impact this work. It also explains the important continuing role of the lawyer in an AI world.This book is divided into three parts:Part A provides an accessible explanation of AI, including diagrams, and contrasts this with the role and work of lawyers.Part B focuses on six different aspects of legal work (litigation, transactional, dispute resolution, regulation and compliance, criminal law and legal advice and strategy) where AI is making a considerable impact and looks at how this is occurring.Part C discusses how lawyers and law firms can best utilise the promise of AI, while also acknowledging its limitations. It also discusses ethical and regulatory issues, including the lawyer’s role in upholding the rule of law.
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Copyright Law and Generative AI
Is it lawful for generative AI to draw on protected works without permission? The question sits at the heart of today’s most urgent debates on AI, and the answer is anything but simple. This book takes a comparative and interdisciplinary approach to unpack how copyright exceptions apply—or fail to apply—in the age of generative AI. It examines how major jurisdictions, including the United States, China, the European Union, Japan, the United Kingdom, and Singapore, are confronting these challenges.The book begins by explaining the basic principles of copyright law and why they matter for both AI training and AI-generated content. It then surveys the key copyright exceptions and licensing routes currently available, highlighting how legal uncertainty has complicated efforts to regulate the way generative AI systems access and use protected material. To make sense of this uncertainty, the book looks beyond the law and examines the broader forces shaping the debate: emerging norms around AI ethics and copyright, the evolving business models built on generative AI, concerns about the market impact of AI-generated products, and the technical realities of generative models, from the black-box problem to the structure of latent space. These dynamics show why existing copyright exceptions, designed for an earlier technological era, often struggle to keep pace with generative AI. The book concludes with a framework for rethinking copyright exceptions that integrates legal, economic, normative, and technological considerations.By bringing together insights across jurisdictions and disciplines, this book offers a clear and timely account of how legal systems are trying to adapt copyright rules to the rise of generative AI without stifling innovation. It will appeal to scholars of intellectual property and artificial intelligence, as well as policymakers, regulators, and AI developers navigating this fast-changing landscape.
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Law, Reinvented
Law, Reinvented: Leading AI Transformation in Legal Practice is a practical guide for legal professionals at every stage of their AI transformation, whether they are leading it inside their firm or organization, working through it day to day as practitioners, or stepping into the profession as it changes. Written by three experts in the field based in London and New York who work in this space every day, it draws on their experience with law firms and in-house teams to address both the strategic and the operational realities of AI in legal practice.The book offers a clear framework for thinking about AI in legal practice, supported throughout by experience drawn from the authors’ work on both sides of the Atlantic. Topics covered include pricing around outcomes rather than time; building credible AI-enabled services; training users and driving adoption; managing risk and governance; and the emerging competitive landscape in which clients, firms, and technology providers increasingly overlap.Whether the reader is in leadership, in practice, or new to the profession, the book is direct, practical, and grounded in real experience. It addresses the operational, ethical, and cultural questions that firms, legal departments, and their clients are working through today, and the ones they will confront next.
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Generative AI’s “Creative” Process in the Era of Privatisation of Knowledge
This book investigates how generative AI in the creative sector should be regulated in ways that are both effective and normatively desirable in the current era of datafication and knowledge capitalism. In particular, the book analyses the challenges posed by generative AI at both the input and output phases of the so-called “algorithmic creative process” while, on the one hand, examining how the EU legislator seeks to address these challenges—primarily through the AI Act—and, on the other hand, arguing that the analysis should extend beyond digital law to encompass renewed reflection on intellectual property law itself. In this respect, the book emphasises the need to reaffirm the social function that copyright law is meant to pursue, which is essential both to the effective governance of this phenomenon and to mitigating the risks arising from an uncritical acceptance of the ongoing privatisation of knowledge within the current socio-economic context.
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Artificial Intelligence and Legal Analytics
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.
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Regulation of Artificial General Intelligence
This book proposes a comprehensive legal framework for regulating Artificial General Intelligence (AGI), integrating insights from law, economics, and process management.Adopting a structured, future-focused, and risk-based approach to address the unique challenges of AGI regulation, this book validates the “singularity scenario” as a legitimate field of scientific inquiry. It critically examines the limitations of the EU Artificial Intelligence Act in governing AGI, and introduces a foundational four-level analytical model rooted in transaction cost theory. Through a detailed exploration of the what, who, and how of regulation, the book maps the risks associated with AGI, discusses the potential role of electronic legal personhood, and develops a practical legal framework aimed at ensuring AGI’s trustworthiness and alignment with human values. Ultimately, it argues for proactive, rather than reactive regulatory strategies in anticipation of the technological singularity.The book will be of interest to researchers in the field of the law of emerging technologies, artificial intelligence and regulation.
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AI Approaches to the Complexity of Legal Systems
This book constitutes revised selected papers from the two International Workshops on Artificial Intelligence Approaches to the Complexity of Legal Systems, AICOL IV and AICOL V, held in 2013. The first took place as part of the 26th IVR Congress in Belo Horizonte, Brazil, during July 21-27, 2013; the second was held in Bologna as a joint special workshop of JURIX 2013 on December 11, 2013. The 19 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They are organized in topical sections named: social intelligence and legal conceptual models; legal theory, normative systems and software agents; semantic Web technologies, legal ontologies and argumentation; and crowdsourcing and online dispute resolution (ODR).
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Understanding the Ethics of Generative AI
The book discusses the ethical complexities that software developers face as they build AI systems capable of autonomous creation. It explores the ethical decisions developers must make when building generative AI systems, from mitigating bias in training data to protecting user privacy and navigating regulatory compliance. Through real-world case studies and actionable frameworks, it equips technical professionals with both the understanding and tools to build AI systems that are fair, transparent, and worthy of public trust.Identifies and corrects algorithmic bias in training datasets, ensuring AI systems produce equitable outputs that don't systematize discriminationDesigns privacy-first AI architectures and implements transparency practices that comply with data protection regulations while building user trustNavigates evolving legal and regulatory landscapes (GDPR, AI Act, sector-specific rules), helping teams stay ahead of compliance requirementsApplies ethical frameworks to real-world decisions: what to do when fairness and accuracy conflict, how to audit AI systems for hidden harms, when to say no to a projectProvides a governance model for embedding ethics into development workflows, not as an afterthought but as core design practice
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Generative AI
Generative AI (GenAI) is the hottest new area of AI, accelerating innovations affecting all industries and showcasing AI’s ability to present human-like language capabilities with large language models (LLMs). This book builds a solid foundation for the technology underlying GenAI Models, LLM, and foundation and reasoning models for the No-Code audience by explaining the models' workings in simple English. It then takes the reader on a journey to find out where there are gaps to innovate. Each chapter outlines the state of research in each topic and invites learners to build on this research to think about ethical implications and balance it with innovation to benefit everyone. The author covers the technological, product, and societal impact of Generative AI to give a comprehensive guide for this important technology. This book will help the data scientist, product manager, and business leader alike because it covers the API economy and critical industries impacted and offers a framework to think about automation and jobs impacted and what competencies are needed to excel in GenAI and offers an in-depth guide to build GenAI products and applications.
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AI Approaches to the Complexity of Legal Systems - Models and Ethical Challenges for Legal Systems, Legal Language and Legal Ontologies, Argumentation and Software Agents
The inspiring idea of this workshop series, Artificial Intelligence Approaches to the Complexity of Legal Systems (AICOL), is to develop models of legal knowledge concerning organization, structure, and content in order to promote mutual understanding and communication between different systems and cultures. Complexity and complex systems describe recent developments in AI and law, legal theory, argumentation, the Semantic Web, and multi-agent systems. Multisystem and multilingual ontologies provide an important opportunity to integrate different trends of research in AI and law, including comparative legal studies. Complexity theory, graph theory, game theory, and any other contributions from the mathematical disciplines can help both to formalize the dynamics of legal systems and to capture relations among norms. Cognitive science can help the modeling of legal ontology by taking into account not only the formal features of law but also social behaviour, psychology, and cultural factors. This book is thus meant to support scholars in different areas of science in sharing knowledge and methodological approaches. This volume collects the contributions to the workshop's third edition, which took place as part of the 25th IVR congress of Philosophy of Law and Social Philosophy, held in Frankfurt, Germany, in August 2011. This volume comprises six main parts devoted to the each of the six topics addressed in the workshop, namely: models for the legal system ethics and the regulation of ICT, legal knowledge management, legal information for open access, software agent systems in the legal domain, as well as legal language and legal ontology.
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Generative Artificial Intelligence and Explainable Artificial Intelligence for Real-world Applications
This book integrates the concepts of explainable artificial intelligence, and generative explainable artificial intelligence, showcasing how explainability can be incorporated into generative models. It highlights the importance of making generative models transparent, offering strategies to achieve this through interpretability techniques.Focuses on the principles and methodologies of explainable artificial intelligence, providing readers with a thorough understanding of how artificial intelligence models can be made transparent and interpretable.Explores explainable artificial intelligence techniques, including feature importance, SHAP values, LIME, and counterfactual explanations.Offers an in-depth examination of generative artificial intelligence, covering cutting-edge advancements in generative models like GANs, VAEs, and transformer-based architectures.Bridges the gap between theoretical concepts and their practical applications, making advanced artificial intelligence technologies accessible to the readers.Includes numerous case studies and real-world examples that demonstrate the successful application of generative artificial intelligence, and explainable artificial intelligence.The text is primarily written for graduate students and academic researchers in electrical engineering, electronics, and communication engineering, computer science and engineering, biomedical engineering, and information technology.
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Threats of Algorithms and AI to Civil Rights, Legal Remedies, and American Jurisprudence
The Threats of Algorithms and A.I. to Civil Rights, Legal Remedies, and American Jurisprudence addresses the many threats to American jurisprudence caused by the growing use of algorithms and artificial intelligence (A.I.). Although algorithms prove valuable to society, that value may also lead to the destruction of the foundations of American jurisprudence by threatening constitutional rights of individuals, creating new liabilities for business managers and board members, disrupting commerce, interfering with long-standing legal remedies, and causing chaos in courtrooms trying to adjudge lawsuits. Alfred R. Cowger, Jr. explains these threats and provides potential solutions for both the general public and legal practitioners. Scholars of legal studies, media studies, and political science will find this book particularly useful.
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Generative AI
This book will show how generative technology works and the drivers. It will also look at the applications – showing what various startupsand large companies are doing in the space. There will also be a look at the challenges and risk factors.During the past decade, companies have spent billions on AI. But the focus has been on applying the technology to predictions – which is known as analytical AI. It can mean that you receive TikTok videos that you cannot resist. Or analytical AI can fend against spam or fraud or forecast when a package will be delivered. While such things are beneficial, there is much more to AI. The next megatrend will be leveraging the technology to be creative. For example, you could take a book and an AI model will turn it into a movie – at very little cost. This is all part of generative AI. It’s still in the nascent stages but it is progressing quickly. Generative AI can already create engaging blog posts, social media messages, beautiful artwork and compelling videos.The potential for this technology is enormous. It will be useful for many categories like sales, marketing, legal, product design, code generation, and even pharmaceutical creation.What You Will LearnThe importance of understanding generative AIThe fundamentals of the technology, like the foundation and diffusion modelsHow generative AI apps workHow generative AI will impact various categories like the law, marketing/sales, gaming, product development, and code generation.The risks, downsides and challenges.Who This Book is ForProfessionals that do not have a technical background. Rather, the audience will be mostly those in Corporate America (such as managers) as well as people in tech startups, who will need an understanding of generative AI to evaluate the solutions.
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Generative AI and Creativity
Generative AI and Creativity: From Theory to Practice is an immersive exploration into the revolutionary domain of generative artificial intelligence. It takes a step-by-step journey starting with the fundamentals of generative AI and progressing to advanced applications. The book unravels the complexities of generative models, delving into key techniques such as generative adversarial networks (GANs) and variational autoencoders (VAE)s, providing a solid foundation for readers to understand the underlying principles.FEATURES• Explores the collaboration between humans and AI in creative processes• Examines generative art movements, graphic design applications, and artist-AI collaborations• Defines creativity in AI, by showcasing case studies and discussing ethical considerationsMoving beyond creative content generation in art and music to practical implementations in industries like healthcare and finance, the book showcases the versatility and transformative potential of generative AI across diverse domains. Readers will gain practical skills through coding examples, case studies, and collaborative projects, empowering them to integrate generative AI into their own work.The book is enriched with stories of innovation, featuring pioneers who have leveraged generative AI to push the boundaries of creativity. Ethical considerations and the societal impact of generative AI are also explored to foster a holistic understanding of the technology.
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Legal Services and Digital Infrastructures
This book seeks to provide and promote a better understanding and a more responsive and inclusive governance of the automation and digital devices in public institutions, particularly the law and justice sector. Concerns related to AI design and use have been exacerbated recently with the recognition of the discriminatory potential that can be embedded into AI applications in public service institutions. This book examines issues relating to the assigning of responsibility in a public service produced and delivered on the basis of an automated mechanism. It encourages critical thinking about the legal services and the justice institutions as they are transformed by AI and automation. It raises awareness as to the prospect of transformation we face in terms of responsibility and of agency and the need to design a citizen-centered and human rights compliant system of technology assessment and AI monitoring and evaluation. The book calls for a comprehensive strategy to enable professional practitioners and decision makers to engage in the design of AI driven legal and justice services. The work draws on on-going research and consulting activities carried out by the author across different countries and different systems in the legal and justice sector. The book offers a critical approach to encourage a new mindset among legal professionals and the justice institutions thus empowering and training them to develop the necessary responsiveness and accountability in the justice sector and legal systems. It will also be of interest to researchers and academics working in the area of AI, Public Law, Human Rights and Criminal Justice.
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Generative AI and Creativity
Generative AI and Creativity: From Theory to Practice is an immersive exploration into the revolutionary domain of generative artificial intelligence. It takes a step-by-step journey starting with the fundamentals of generative AI and progressing to advanced applications. The book unravels the complexities of generative models, delving into key techniques such as generative adversarial networks (GANs) and variational autoencoders (VAE)s, providing a solid foundation for readers to understand the underlying principles.FEATURES• Explores the collaboration between humans and AI in creative processes• Examines generative art movements, graphic design applications, and artist-AI collaborations• Defines creativity in AI, by showcasing case studies and discussing ethical considerationsMoving beyond creative content generation in art and music to practical implementations in industries like healthcare and finance, the book showcases the versatility and transformative potential of generative AI across diverse domains. Readers will gain practical skills through coding examples, case studies, and collaborative projects, empowering them to integrate generative AI into their own work.The book is enriched with stories of innovation, featuring pioneers who have leveraged generative AI to push the boundaries of creativity. Ethical considerations and the societal impact of generative AI are also explored to foster a holistic understanding of the technology.
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Applied Generative AI for Beginners
This book provides a deep dive into the world of generative AI, covering everything from the basics of neural networks to the intricacies of large language models like ChatGPT and Google Bard. It serves as a one-stop resource for anyone interested in understanding and applying this transformative technology and is particularly aimed at those just getting started with generative AI.Applied Generative AI for Beginners is structured around detailed chapters that will guide you from foundational knowledge to practical implementation. It starts with an introduction to generative AI and its current landscape, followed by an exploration of how the evolution of neural networks led to the development of large language models. The book then delves into specific architectures like ChatGPT and Google Bard, offering hands-on demonstrations for implementation using tools like Sklearn. You’ll also gain insight into the strategic aspects of implementing generative AI in an enterprise setting, with the authors covering crucial topics such as LLMOps, technology stack selection, and in-context learning. The latter part of the book explores generative AI for images and provides industry-specific use cases, making it a comprehensive guide for practical application in various domains.Whether you're a data scientist looking to implement advanced models, a business leader aiming to leverage AI for enterprise growth, or an academic interested in cutting-edge advancements, this book offers a concise yet thorough guide to mastering generative AI, balancing theoretical knowledge with practical insights.What You Will LearnGain a solid understanding of generative AI, starting from the basics of neural networks and progressing to complex architectures like ChatGPT and Google BardImplement large language models using Sklearn, complete with code examples and best practices for real-world applicationLearn how to integrate LLM’s in enterprises, including aspects like LLMOps and technology stack selectionUnderstand how generative AI can be applied across various industries, from healthcare and marketing to legal compliance through detailed use cases and actionable insightsWho This Book Is ForData scientists, AI practitioners, Researchers and software engineers interested in generative AI and LLMs.
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