Search results for "Generative AI Governance"
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AI-Governance im Aufsichtsrat
AI-Governance gehört als Pflichtthema auf jede Board-Agenda. Wer sie aktiv gestaltet, schafft einen echten Governance-Vorteil. Dieses Buch dient dabei als wertvoller Begleiter und Leitfaden. Es verbindet rechtliche Grundlagen wie Sorgfaltspflichten, Haftung und EU AI Act mit praxiserprobten Governance-Bausteinen von der KI-Risikoappetit-Erklärung über Ausschussstrukturen bis zum 100-Tage-Plan für das Board. Es richtet sich an Aufsichtsräte und Beiräte in börsennotierten wie auch in mittelständischen, häufig familiengeführten Unternehmen. Mit branchenspezifischen Cases, einer verständlichen Erklärung der technischen Standards und einem fundierten Ausblick auf agentische KI.
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Generative AI for Leaders Playbook
Lead the AI revolution with confidence. Learn how to craft strategy, build AI teams, and drive innovation responsibly with this practical leadership playbook for the Generative AI era.Free with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesBuild AI fluency and lead digital transformation with confidenceDesign enterprise-wide AI strategy, teams, and governance modelsUnlock growth with responsible and scalable Generative AI adoptionBook DescriptionGenerative AI has shifted from a technical breakthrough to a leadership imperative. This essential guide helps executives, directors, and tech leads navigate the transformation, bridging AI’s technical realities with enterprise applications and providing the frameworks and vocabulary needed to make informed decisions.Written for strategic leaders and decision-makers, this practical playbook demystifies key concepts, including generative AI, large language models (LLMs), and emerging agentic AI systems. It shows you how to develop AI strategies aligned with business goals, build AI-first organizations, and establish governance frameworks for responsible, compliant adoption. Real-world examples show how leading companies use AI to drive innovation, efficiency, and growth.Beyond strategy, you’ll learn how to build and scale AI teams, evaluate technology vendors, and integrate AI across business functions. You’ll also explore global policy trends, ethical implications, and the governance frameworks emerging across jurisdictions.This playbook provides a roadmap for turning AI disruption into sustainable competitive advantage, equipping executives with the strategic understanding and practical guidance needed to lead, implement, and scale AI responsibly.*Email sign-up and proof of purchase requiredWhat you will learnUnderstand generative and agentic AI capabilities and business valueBuild organizational AI literacy and cultural readinessCraft an enterprise AI strategy aligned with business goalsDesign and scale high-performing AI teams and structuresEvaluate AI platforms and vendors for transparency and reliabilityEmbed responsible AI governance and compliance frameworksWho this book is forThis book is for AI professionals, AI business leaders, founders, and senior managers who need to navigate the strategic, operational, and ethical challenges of AI adoption. It’s also invaluable for consultants, policy leaders, and transformation specialists advising enterprises on AI readiness. No coding knowledge is required—only a vision to lead AI-powered change across industries.
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Generative AI in Higher Education: Ethical Governance, Skills, and Employability
Building upon the foundational principles established in the first volume, this second volume of Generative AI in Higher Education advances the debate on AI beyond theoretical frameworks toward concrete institutional practice. Where the first volume developed guiding principles for higher education institutions to use GenAI effectively and ethically in teaching and learning, this volume introduces original, research-informed frameworks that redefine employability as an ethical, adaptive, and human-centred practice. It presents distinctive models including Skills Dynamics, the Justice–Responsibility Framework for Human Flourishing, and the AI Dialogic Partner frameworks that move decisively from principles to practice.The book integrates ethical governance, curriculum design, and skills formation through actionable models such as the Double ERL Framework (Ethical Regulation Literacy and Ethical Reflexive Learning), the ERL Justice Framework, and the Institutional AI Stewardship Lab (IASL) model. Uniquely combining philosophical depth with policy relevance, it bridges global and local perspectives—drawing on UNESCO, OECD, and regional policy frameworks—to address the ethical, social, and regulatory dimensions of AI in higher education. The volume includes comprehensive international policy analysis, diverse global case studies, and practical tools that transform conceptual exploration into implementable guidance.Generative AI in Higher Education: Ethical Governance, Skills, and Employability serves as essential reading for university leaders, policymakers, educators, and employers seeking to align AI innovation with justice, inclusion, and sustainability. Its practical frameworks and transparency principles empower institutions to position education not merely as a response to technological change but as a transformative force for human flourishing, providing both scholarly contribution and actionable roadmap for embedding ethical AI in higher education practice.
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AI Governance Playbook
Organizations are rushing to capitalize on the artificial intelligence (AI) trend, however, often the proper controls and planning are not in place, resulting in significant risks. Key to successful generative AI deployments are clear guardrails and guidelines for training the AI model, along with proper controls and metrics to track progress and cite issues.AI governance is an offshoot of IG, and includes a comprehensive framework of principles, policies, regulations, and operational practices that steer the entire lifecycle of AI technologies, from development to deployment to usage. This multifaceted approach addresses a wide array of vital factors, such as ethics, accountability, transparency, fairness, privacy, and security. The significance of AI governance lies in its capacity to guarantee the responsible and value-aligned evolution and application of AI technologies, serving the betterment of society as a whole. In the absence of robust governance, AI has the potential to amplify preexisting disparities, compromise individual rights, and introduce risks that may impact both individuals and the broader community.Without proper AI governance controls and “guardrails” AI program deployments can suffer from:Bias and Discrimination: Without proper governance, AI systems can perpetuate and even amplify biases present in training data, leading to discriminatory outcomes. This can have serious ethical and legal implications and harm marginalized communities.Privacy Violations: AI systems might inadvertently infringe on individuals' privacy by collecting, processing, or sharing personal data without consent or inappropriately.Security Risks: Ungoverned AI deployments can become targets for cyberattacks. If AI systems are not adequately secured, they can be exploited, leading to data breaches, unauthorized access, or other security breaches.Reputation Damage: Poorly managed AI deployments can result in algorithmic errors or unintended consequences, which can tarnish a company's reputation and trustworthiness, and reduce its brand equity value.Regulatory Compliance Issues: Failing to adhere to data protection and AI-related regulations can lead to legal issues, fines, and penalties, which can be costly for businesses.Loss of Accountability: Unclear responsibility for AI system outcomes can lead to a lack of accountability, making it challenging to rectify issues and assign responsibility when things go wrong.Ineffective or Inefficient Operations: Ungoverned AI might not operate optimally, leading to inefficiencies or errors in business processes.Missed Opportunities: Without proper governance, organizations might underutilize AI's potential, missing out on opportunities for automation, data-driven insights, and improved decision-making.Ethical Concerns: AI deployment without ethical guidelines can raise moral questions about the technology's use in various applications, such as surveillance, autonomous weapons, or job displacement.Lack of Transparen
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Global Governance of the Transition to Artificial General Intelligence
While today’s Artificial Narrow Intelligence (ANI) tools have limited purposes like diagnosing illness or driving a car, if managed well, Artificial General Intelligence (AGI), could usher in great advances in human condition encompassing the fields of medicine, education, longevity, turning around global warming, scientific advancements, and creating a more peaceful world. However, if left unbridled, AGI also has the potential to end human civilization. This book discusses the current status, and provides recommendations for the future, regarding regulations concerning the creation, licensing, use, implementation and governance of AGI. Based on an international assessment of the issues and potential governance approaches for the transition from ANI of today to future forms of AGI by The Millennium Project, a global participatory think tank, the book explores how to manage this global transition. Section 1 shares the views of 55 AGI experts and thought leaders from the US, China, UK, Canada, EU, and Russia, including Elon Musk, Sam Altman and Bill Gates, on 22 critical questions. In Section 2, The Millennium Project futurist team analyzes these views to create a list of potential regulations and global governance systems or models for the safe emergence of AGI, rated and commented on by an international panel of futurists, diplomats, international lawyers, philosophers, scientists and other experts from 47 countries. This book broadens and deepens the current conversations about future AI, educating the public as well as those who make decisions and advise others about potential artificial intelligence regulations.
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Governing Pandora
A road map for developing responsible and innovative governance systems based on generative AI and other exponential technologiesAs exponential technology rapidly advances, leaders in every sector are faced with the challenge of harnessing its potential power while developing precautionary safeguards against its risks. From generative artificial intelligence to the future of quantum computing, these innovations are transforming the world at an unprecedented rate, leaving decision-makers unsure of how to maintain control and ensure responsible development.Governing Pandora focuses on multiple exponential technologies in order to demonstrate how leaders can develop responsible and innovative governance systems. This book equips leaders with frameworks and tools—including a detailed five-element "exponential governance mind-set"—to develop a more holistic tech governance approach for current and future waves of exponential tech. Andrea Bonime-Blanc encourages the development of a culture of collaboration across borders, sectors, and disciplines as technology takes on a bigger role in our ecosystem. She explains the context, risks, and opportunities of the ongoing exponential technology revolution so that leaders can futureproof themselves, their organizations, and key stakeholders with strategies and tactics to act responsibly, ethically, and successfully.This book speaks directly to executives, board members, policymakers, and organizational leaders who are tasked with charting a course through the advancement of modern technologies. Governing Pandora bridges the gap between exploring pure technology and managing and governing applied technology. Readers will learn not only how to develop a governance mind-set for exponential technology but also how to build organizational resilience.
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AI-Ready Data Blueprints
Companies innovating with generative AI understand that having the right data foundation is critical for success and profitability. To best position themselves for long-term success, organizations must prioritize investments in data and AI governance. AI-Ready Data Blueprints is your map to connecting data strategy, GenAI, and ethical practices to build and scale truly effective solutions. Taking a comprehensive, cloud-agnostic approach focused on real-world business challenges, seasoned data and AI experts Navnit Shukla, Kien Pham, Srikanth Sopirala, and Harsha Tadiparthi share actionable insights to guide you in designing and implementing effective data-centric GenAI systems. Whether you're new to GenAI or are already focusing on optimizing it for accuracy, speed, or both, the principles shared in this book will empower you to excel in all your AI endeavors. Identify the key elements of a solid data foundation for generative AIApply data governance and orchestration techniques to ensure high data quality, access control, and proper data lineage for reliable AI systemsOptimize GenAI applications through prompt engineering, fine-tuning, and retrieval-augmented generationImplement security, compliance, and governance measures, including responsible AI practices, transparency, and more
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GENERATIVE AI AS THE SECOND MIND: REWRITING THE RULES OF BUSINESS AND ORGANIZATION
This book focuses on redefining organizational strategy and management in the era of Generative AI (GenAI). It challenges the foundational assumptions of the Industrial Revolution, arguing that GenAI dissolves the boundaries between labor, materials, and production by introducing a "Second Mind" — a non human entity with human level capabilities and infinite memory. Positioned as workforce, tool, and raw material simultaneously, this paradigm compels leaders to rethink management principles that have guided enterprises for two centuries.The text provides both corporate and academic communities with a rigorous cognitive framework and a strategic roadmap for navigating the transition from legacy hierarchies to symbiotic intelligence. It distinguishes the logic of Classical AI from Generative AI, mapping how each reshapes organizational structures, employee roles, and decision making authority. Central to this framework is the concept of Symbiotic Agency Modes (SAM) — a hierarchy of Coordination, Cooperation, and Collaboration — which specifies how human and digital minds operate as a coupled system.Moving beyond vague "human in the loop" notions, the book introduces actionable governance mechanisms and tailored performance indicators, such as learning rate and reversibility, to evaluate hybrid workforces. By offering a systematic roadmap for implementation, it ensures measurable ROI and sustainable competitive advantage.Serving as an "Origin of Species" for 21st century organizational evolution, this book equips leaders, strategists, and institutions to harness symbiotic intelligence and lead the next era of business transformation.
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Generative AI, Media, and Society
This groundbreaking book demystifies generative AI’s transformative impact on media, socio-cultural dynamics, ethics, and policy.Defining generative AI as an evolutionary leap in the development of artificial intelligence, the author examines intricate human-machine interactions and socio-technical dynamics, advocating robust, proactive AI governance to address emerging uncertainties. The book is clearly structured into six key chapters, each exploring distinct aspects of the relationship between artificial intelligence, media, and society. The chapter on "Transformation" examines how machine behavior is reshaping our datafied society, questioning whether data is the new oil, or digital manure. "Generative AI" investigates the models and future impacts of generative AI as a co-intelligence, revisiting the Turing Test and analyzing societal-business impacts. "AI Media" explores the convergence of media and AI, highlighting robot journalism, synthetic content, and the disinformation era and discussing the trend toward high-risk optimism. "Uncertainties" addresses inherent unpredictability vs. strategic foresight, focusing on challenged business models, sustainability concerns, and emotional intelligence factors. "Ethics" analyzes generative morality and dual-use technology, covering trusted AI principles—from misuse to integrative solutions. Finally, "Policy" discusses governance, labor market impacts, and the importance of human rights and power dynamics in generative AI. Each chapter also provides summaries of impact projects, reflective art, scholarly questions, and strategic takeaways—extended with a comprehensive glossary.This is an essential resource for scholars, students, policymakers, technologists, ethicists, and AI industry leaders seeking to rapidly understand and address the challenges and opportunities of generative AI and AI media in a cohesive framework.
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Foundational Principles of AI Governance and Policy
This edited volume provides a structured analysis of AI governance principles, challenges, and implementation strategies. Drawing on interdisciplinary perspectives and global case studies, the volume offers actionable insights for policymakers, industry leaders, and academics. The book is organized into four parts, each addressing critical dimensions of AI governance and policy. Part I lays the foundational understanding of AI from a policy and governance perspective. Part II examines the positive potential of AI, focusing on how standardization, talent cultivation, and global cooperation can enable AI to address pressing global challenges. Part III addresses the ethical, legal, and security challenges AI poses. It provides a critical analysis of the risks associated with AI deployment, including issues related to warfare, disinformation, and regulatory gaps. Part IV focuses on the necessity of international cooperation and the development of global governance frameworks for AI. This book serves as a foundational resource for stakeholders seeking to understand and navigate the complexities of AI governance.
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Cambridge Handbook of Generative AI and the Law
This handbook offers an important exploration of generative AI and its legal and regulatory implications from interdisciplinary perspectives. The volume is divided into four parts. Part I provides the necessary context and background to understand the topic, including its technical underpinnings and societal impacts. Part II probes the emerging regulatory and policy frameworks related to generative AI and AI more broadly across different jurisdictions. Part III analyses generative AI's impact on specific areas of law, from non-discrimination and data protection to intellectual property, corporate governance, criminal law and more. Part IV examines the various practical applications of generative AI in the legal sector and public administration. Overall, this volume provides a comprehensive resource for those seeking to understand and navigate the substantial and growing implications of generative AI for the law.
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Democracy, Leadership and Governance – Application of Artificial Intelligence
In today’s rapidly evolving political landscape, the intersection of democracy, leadership, and governance with artificial intelligence (AI) has become a focal point for academic inquiry and practical explorations. This book is a machine-generated literature overview that explores the opportunities, challenges, and impacts of integrating AI technologies in democratic processes, leadership dynamics, and sustainable governance. Through a collection of thought-provoking chapters, readers will gain insights into the transformative potential of AI that revisits the tenets of deliberative democracy, redefines leadership roles, and rejuvenates public service delivery. This volume offers a comprehensive exploration of the processes and practices of democratic decision-making, leadership development, and sustainable governance. It serves as a valuable resource to academics, policymakers, and practitioners navigating through the concepts, dimensions, and praxis of democracy, leadership, and governance. It is an important value addition to the body of knowledge and paves the way for informed decision-making and responsible application of digital technologies for good governance.
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Hybrid Intelligence
Uniquely aimed at teams that think together to solve problems and make decisions, this book explains how to enhance the collective intelligence of a team-size group and combine it with the artificial intelligence (AI) of generative AI to create a hybrid intelligence that is smarter than either one on its own.Boards, committees, and other team-size groups of 5-20 people are the primary problem-solving and decision-making units within organizations, and they form the bridges between organizations, industries, and nations that collaborate on projects. So how can leaders exponentially improve their teams’ capabilities? Assemble the right people, arm them with the right processes, and execute those processes on the right platforms—then add generative AI to enhance those practices. This book describes and synthesizes various ways of increasing a group’s collective intelligence through people, process, and platform practices, and goes on to explain how to augment the practices with generative AI, including how to ask it questions and what questions to ask to obtain superior answers. The resulting upsurge in team capability enables organizations to survive and thrive in a world that is growing progressively more competitive and complex.This book will become the definitive resource for leaders and managers of commercial, government, and nonprofit organizations who want to learn how to significantly improve their teams’ problem-solving and decision-making ability by increasing their collective intelligence and combining it with the artificial intelligence of generative AI.
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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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Cambridge Handbook of the Governance of Technology
In recent years, the use of AI has skyrocketed. The introduction of widely available generative AI, such as ChatGPT, has reinvigorated concerns for harm caused to users. Yet so far government bodies and scholarly literature have failed to determine a governance structure to minimize the risks associated with AI and big data. Despite the recent consensus among tech companies and governments that AI needs to be regulated, there has been no agreement regarding what a framework of functional AI governance should look like. This volume assesses the role of law in governing AI applications in society. While exploring the intersection of law and technology, it argues that getting the mix of AI governance structures correct-both inside and outside of the law-while balancing the importance of innovation with risks to human dignity and democratic values, is one of the most important legal-social determination of our times.
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AI in Popular Culture
This book examines the transformative impact of generative AI on cultural production, with a particular focus on how AI technologies like ChatGPT are reshaping the creation of popular culture.Through a comprehensive analysis of both Global North and South perspectives, the book offers critical insights into AI governance, ethical considerations, and the future of cultural production in an increasingly AI-integrated creative landscape. Tracing the evolution of AI in cultural industries, from its early representations in films to its current active role in content creation across various media, including film, television, music, and animation, the book explores how AI has shifted from being merely depicted in cultural works to becoming an integral tool in the creative process, from pre-production to post-production stages. It critically analyzes three core concepts—creativity, control, and credentials (3Cs)—in the context of AI-driven cultural production, putting focus on the examination of "precarious creativity," the tension between human creative expression and AI-generated content. The work addresses crucial concerns about labor rights, job security, and creative control in the cultural industries.This book will interest graduate students and researchers in media studies, cultural studies, anthropology, globalization studies, sociology, and science and technology studies (STS), as well as interested policymakers and practitioners interested in AI's impact on the creative industries.
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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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Practical Guide to Generative AI Using Amazon Bedrock
This comprehensive guide gives you the knowledge and skills you need to excel in Generative AI. From understanding the fundamentals to mastering techniques, this book offers a step-by-step approach to leverage Amazon Bedrock to build, deploy, and secure Generative AI applications. The book presents structured chapters and practical examples to delve into key concepts such as prompt engineering, retrieval-augmented generation, and model evaluation. You will gain profound insights into the Amazon Bedrock platform. The book covers setup, life cycle management, and integration with Amazon SageMaker. The book emphasizes real-world applications, and provides use cases and best practices across industries on topics such as text summarization, image generation, and conversational AI bots. The book tackles vital topics including data privacy, security, responsible AI practices, and guidance on navigating governance and monitoring challenges while ensuring adherence to ethical standards and regulations. The book provides the tools and knowledge needed to excel in the rapidly evolving field of Generative AI. Whether you're a data scientist, AI engineer, or business professional, this book will empower you to harness the full potential of Generative AI and drive innovation in your organization. What You Will Learn Understand the fundamentals of Generative AI and Amazon BedrockBuild Responsible Generative AI applications leveraging Amazon BedrockKnow techniques and best practicesSee real-world applicationsIntegrate and manage platformsHandle securty and governance issuesEvaluate and optimze modelsGain future-ready insightsUnderstand the project life cycle when building Generative AI Applications Who This Book Is For Data scientistys, AI/ML engineers and architects, software developers plus AI enthusiasts and studenta and educators, and leaders who want to evangelize within organizatios
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Agentic GraphRAG
What if your AI systems could retrieve information, reason over complex knowledge, plan actions, and continuously learn-all while maintaining enterprise-grade security and compliance? Agentic Graph RAG guides technical leaders, engineers, and architects through the next evolution of generative AI. Combining retrieval-augmented generation (RAG) with graph-based reasoning and agentic capabilities, this guide provides a practical blueprint for building scalable, auditable, and intelligent AI systems.Written by Anthony Alcaraz and Sam Julien, this book demystifies knowledge graphs, graph memory, neural-symbolic reasoning, and agent orchestration through real-world case studies, hands-on design patterns, and production-ready architectures. Readers will learn how to construct graph-native retrieval systems, integrate advanced reasoning into agent workflows, and address enterprise challenges around governance, scalability, and transparency.Design graph-augmented architectures that surpass traditional RAGImplement agents with dynamic memory, planning, and decision-making capabilitiesIntegrate knowledge graphs with large language models for robust, explainable AIDeploy scalable, governable multiagent systems ready for production environments
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