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AI Impacts on Branded Entertainment and
Advertising

AI Impacts on Branded Entertainment and Advertising

Artificial Intelligence and Blockchain in International Arbitration offers an exhaustive analysis of technology-assisted arbitration across the entire arbitral lifecycle by examining how blockchain and artificial intelligence are used in drafting and concluding arbitral agreements, in the constitution of the tribunal, in the overall procedural management of the case, on evidence and disclosure, on virtual hearings, and even on arbitral award drafting. It delves deeper into the limitations of automation, the non-delegable roles of arbitrators, and the compatibility of digital procedures with core arbitration principles such party autonomy, due process, equality of arms, secrecy, and impartiality. Additionally, it examines how new technologies interact with private international law, with the consent of the parties, the relevant legislation and how these technologies can be incorporated into arbitration without going against public policy, without violation due process rights and, in that way ensuring enforcement under the New York Convention.This book, by examining how blockchain and artificial intelligence are changing arbitral practice, provides a fresh and topical viewpoint on current debates in international arbitration and explores how these technological advancements are reshaping arbitration foundations while posing ethical challenges about the future of arbitration.

Artificial Intelligence and Blockchain in International Arbitration

Leveraging Data Science and Machine Learning

Predictive Intelligence for Transforming Healthcare Insurance

The next choice we make is the last chance we have. Ten thousand years ago, wild cats wandered into a human grain store. Over generations, gorged with a plentiful supply of prey, they traded their raw instincts for a life of dependency as our household pets. Today, domestic cats are more comfortable than ever but they can no longer hunt effectively. Their brains are 16% smaller than their distant ancestors. They are domesticated. AI is turning the modern world into a cognitive grain store. And we are the cats. In this groundbreaking and vital book, leading AI researcher and campaigner James F. Ryan charts our relationship with transformative technologies - from writing to AI - and explains why this time it's different. Large language models like ChatGPT are not just tools, but are remaking our brains and eroding our ability to think. From the workplace and our relationships to our schools and universities, we face an urgent battle to safeguard human thought. The Domestication sets out the evidence, the imposing challenge we face, and how we respond.

A Story of AI and the Human Mind

The Domestication

Decision-Making in the Age of Artificial Intelligence

Do We Still Need to Decide?

Why the career ladder you were climbing has come apart, and what to do about it.Your job title may still be intact. The meetings continue; the monthly presentation still needs producing. But AI is already taking on the reporting, coordination, research and analysis work that once justified whole teams. The change seldom arrives with a dramatic announcement. It's more insidious than that: the hire is paused, the contractor is not renewed, the promotion evaporates.Written by someone building the tools behind this shift, The Next Rung looks at the knowledge-work middle: project leads, analysts, account managers, operations teams and managers whose jobs depend on orchestration. It traces the pressure from boardroom economics to kitchen-table arithmetic, and asks what happens when professional incomes and mortgages are exposed at the same time.Inside, you'll find: <ul> <li> The roles AI is quietly hollowing out </li> <li> Why the 'junior grind' is disappearing </li> <li> The 80/20 Collapse in professional work </li> <li> A practical audit of your exposure and runway </li> <li> The human capabilities that still matter </li> <li> Routes towards trades, portfolio work and community enterprise </li> <li> What AI's gains mean for housing, welfare and inequality. </li> </ul>This is a clear-eyed notebook from inside the transition, focused on judgement, resilience and building work with more human value. It will let you know where you stand, strengthen your options, and help you make your next move before the ladder disappears beneath you.

Why AI is breaking the career ladder, and how to find your next step

The Next Rung

Build a resilient, high-performing organization by integrating agentic AI into strategy, operations, and decision-making. Building an Agentic Organization is a strategic guide for senior technology, AI and business leaders responsible for delivering value from agentic AI while managing its risks. As organizations move toward human and AI collaboration at scale, leaders must balance innovation with governance, adoption, and long-term economic impact. Written by experienced AI executive Geoffrey Schaefer, this book provides a comprehensive framework for designing an agentic organization by examining strategy, governance, and economics. It explores how to define the purpose of agentic AI, align it with business objectives, and create the structures needed to support safe, scalable adoption. Addressing both opportunity and risk, it equips leaders to navigate workforce concerns, reputational exposure, and the evolving role of AI agents in enterprise environments. You'll learn how to: - Define a clear strategy for integrating agentic AI - Establish governance frameworks to manage risk and accountability - Drive workforce adoption and address resistance to AI collaboration - Assess economic value and impact of agentic AI systems - Manage reputational and operational risks from AI agent behavior Featuring real-world examples from Leidos, JPMorgan Chase, SY Partners, and OMA, this book provides a practical roadmap for embedding agentic AI into the fabric of your organization while protecting value, trust, and long-term performance. Themes include: agentic AI, AI strategy, AI governance, AI transformation, enterprise AI, risk management

The Strategy, Governance, and Economics of Agentic AI

Building an Agentic Organization

Taylor and Francis Proceedings in Computer Science and Engineering

Reimagining Tomorrow: AI and Sustainable Imperative presents a curated collection of high-quality research contributions that explore the transformative role of Artificial Intelligence in addressing pressing sustainability challenges across a variety of sectors.This book highlights how advanced AI techniques-ranging from machine learning and deep learning to intelligent optimization-are being leveraged to enhance efficiency, reduce environmental impact, and support data-driven decision-making. The volume emphasises the growing importance of integrating technological innovation with sustainability goals to create resilient and future-ready systems. The primary focus of this book is on human-centred Artificial Intelligence, with particular attention given to its ethical, societal, and governance dimensions. It examines critical issues such as transparency, fairness, accountability, and privacy, while also showcasing AI-driven solutions for sustainable development in key domains, including healthcare, education, smart infrastructure, and Industry 5.0. The contributions further address interdisciplinary approaches, combining AI with emerging paradigms such as edge computing, IoT, and green technologies to enable scalable and responsible innovation.The book provides valuable insights for researchers, academicians, industry practitioners, policymakers, and students by offering a comprehensive perspective on both theoretical advancements and practical implementations of AI for sustainability and serves as a reference for understanding current trends, identifying research gaps, and exploring future directions in the design of intelligent, ethical, and sustainable systems.

AI and Sustainable Imperative

Reimagining Tomorrow

Wiley Finance

The handbook to unleash the power of AI in Finance with guidance to pragmatically managing AI Risk Are you ready to harness the transformative potential of artificial intelligence and machine learning in finance while effectively managing the associated risks? "AI and Risk Management in Finance: A Practitioner's Handbook" by Sri Krishnamurthy, CFA, is your indispensable guide. Tailored for financial professionals, this comprehensive handbook delivers practical insights, case studies, and frameworks to navigate the complex landscape of AI and ML in the financial sector. This pragmatic handbook, developed primarily for professionals involved in designing, developing, and deploying AI models in the financial industry explores cutting-edge technologies, regulatory landscapes, and pragmatic frameworks. From generative AI to robust risk management strategies, this handbook equips you with the tools you need to validate models, ensure compliance, and operationalize AI risk management effectively. Leveraging lessons from QuantUniversity's AI and Machine Learning Risk Management program offered in 18 countries, this book focuses on enabling practitioners apply the state-of-the-art AI and machine learning techniques factoring unique risks specific to the financial services domain. Whether you're a seasoned professional or a newcomer, this book offers invaluable insights for harnessing the power of AI responsibly in the financial industry. Highlights of the Book: <ul> <li>Machine Learning and AI in Financial Services: Dive into the fundamentals of ML and AI, exploring various applications within the financial industry through real-world case studies.</li> <li>Generative AI and LLMs in Finance: Understand the emerging landscape, key players, and advanced concepts like prompt engineering and fine-tuning with practical examples.</li> <li>Risk Management for AI/ML Applications: Learn about current and emerging regulatory landscapes, AI risk management frameworks, and legislative efforts shaping the field.</li> <li>Data Governance Issues: Address critical aspects of data quality, privacy, security, and governance, with actionable frameworks and illustrative case studies.</li> <li>Model and System Governance: Gain insights into validating machine learning models, quantifying model risk, and ensuring robust system governance with MLOps and model monitoring.</li> <li>Key Risk Assessment Facets: Focus on documentation, explainability, fairness, security, and reliability with detailed case studies.</li> <li>Verification and Validation: Distinguish between verification and validation and learn frameworks for effective AI application validation.</li> <li>Algorithmic Auditing: Conduct comprehensive algorithmic audits with detailed processes and real-world examples.</li> <li>Operationalizing AI Risk Management: Discover ten essential strategies for implementing AI risk management practices effectively in your organization.</li> </ul> Prepare for the future of finance with expert advice and actionable strategies. Don't miss out on this comprehensive guide-your roadmap to navigating AI and risk management in the financial sector.

A Practitioner's Guide to Machine Learning, Generative AI, Agentic Systems, and Responsible Deployment

AI Impacts on Branded Entertainment and Advertising

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