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The Algorithmic Child Consumer

Persuasion, Datafication, and Privacy

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

Tech, War and the Fight for Humanity

Thundercloud

Discover how to adapt, adopt, and thrive in an AI-anxious era, written by the man with the compass for our maze Expecting the apocalypse around the corner? This book is your playbook to surviving the rise of machine learning. 71% of workers are anxious about AI. The good news: the machines still need you, and you can make them work for you. Don't Panic cuts through the noise, showing you exactly how this technology works and where it fails, and why your human judgment is more valuable than ever. Instead of focusing on technical skills or abstract predictions, author Nate B. Jones ("AI Nate") begins with the emotional reality behind AI anxiety, drawing on his 20-years experience in the tech industry. He's garnered trust from more than 1 million people to help them stay relevant in a rapidly changing technological landscape. AI might have a planet-sized brain, but just like Marvin the Android from The Hitchhiker’s Guide to the Galaxy, it’s permanently stuck at factory settings. It can’t learn, it can’t adapt, and it can’t gain wisdom. This book reveals why AI's permanent blind spots make human judgment more valuable today than ever before.&nbsp; Worry less, and start owning your future.

Discover how to adapt, adopt, and thrive in an AI-anxious era, written by the man with the compass for our maze Expecting the apocalypse around the corner? This book is your playbook to surviving the rise of machine learning. 71% of workers are anxious about AI. The good news: the machines still need you, and you can make them work for you. Don't Panic cuts through the noise, showing you exactly how this technology works and where it fails, and why your human judgment is more valuable than ever. Instead of focusing on technical skills or abstract predictions, author Nate B. Jones ("AI Nate") begins with the emotional reality behind AI anxiety, drawing on his 20-years experience in the tech industry. He's garnered trust from more than 1 million people to help them stay relevant in a rapidly changing technological landscape. AI might have a planet-sized brain, but just like Marvin the Android from The Hitchhiker’s Guide to the Galaxy, it’s permanently stuck at factory settings. It can’t learn, it can’t adapt, and it can’t gain wisdom. This book reveals why AI's permanent blind spots make human judgment more valuable today than ever before.&nbsp; Worry less, and start owning your future.

AI Optimism for the Mildly Alarmed

Don't Panic

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 and Risk Management in Finance

Useful & Usable

Algorithmic Management: Artificial Intelligence and the Transformation of Organizations is the first comprehensive textbook designed to prepare management students to engage critically and responsibly with artificial intelligence in organizations. Bringing together classical management theory, contemporary AI applications, and systematic power analysis, the book equips future managers to both harness AI's potential and confront its risks.Structured in three parts, the book begins with foundational frameworks-socio-technical systems theory, technology and society perspectives, and core management theories reinterpreted for the AI era. It then examines applications across all major management functions-Marketing, HR, Finance, Operations, Supply Chain, and Strategy-using over 30 real-world case studies drawn from different industries, parts of the world, and types of organizations from multinational corporations to nonprofits and social ventures. The final section addresses organizational design, leadership, governance, and the future of algorithmic organizations. Throughout, pedagogical features-learning objectives, vignettes, discussion questions, toolkits, and ethical dilemmas-make the book classroom-ready and adaptable across MBA, undergraduate, and executive education settings. The text advances an approach of pragmatic criticality: AI is neither celebrated uncritically nor rejected outright but treated as a socio-technical phenomenon requiring managerial judgment, ethical reflection, and contextual awareness.By bridging management theory, functional practice, and critical perspectives, this book fills a critical market gap and is positioned to become the definitive teaching resource on AI and management for business education worldwide.

Artificial Intelligence and the Transformation of Organizations

Algorithmic Management

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 behaviorFeaturing 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

Innovations in Intelligent Internet of Everything IoE

Biomedical Applications of AI and IoMT in Smart Healthcare

Turn AI investment into scalable business impact by enabling your workforce to build the solutions they actually need. From AI Users to Solution Builders is a strategic guide for senior AI, technology, and transformation leaders who want to move beyond underperforming, centralized AI initiatives, and unlock real enterprise value. As organizations struggle to translate AI into measurable results, this book shows how shifting from top-down deployment to workforce-led solution building creates faster adoption, stronger ROI, and sustained innovation. Written by experienced AI leader Wei Manfredi, this book combines strategic insight with practical execution. It draws clear parallels between failed digital transformation efforts and current AI adoption challenges, while demonstrating how natural language interfaces are reshaping access to AI. By enabling non-technical professionals to design their own tools, organizations can embed AI directly into workflows, decision-making, and daily operations. You'll learn how to: - Shift from centralized AI models to workforce-driven innovation - Enable employees to build AI solutions for real workflows - Design scalable infrastructure for AI solution development - Apply change management to overcome resistance and drive adoption &gt;Featuring real-world examples from organizations including Lululemon, Google, Oracle, and JPMorgan Chase, this book provides a proven framework for embedding AI into everyday collaboration, accelerating innovation, and future-proofing your organization's competitive advantage. Themes include: AI strategy, AI adoption, workforce transformation, AI governance, enterprise AI, change management

Scaling AI Across Your Organization

From AI Users to Solution Builders

Emerging Trends in Science, Innovation and Business

"Federated Learning Applications in Healthcare: Empowering Wellness" is an ambitious and timely endeavor aimed at providing a comprehensive exploration of the intersection between federated learning and healthcare.Federated learning, a decentralized machine learning approach that enables model training across multiple devices or institutions without centralized data sharing, holds immense promise for revolutionizing healthcare by facilitating collaboration, preserving patient privacy, and improving healthcare outcomes. This book aims to unravel the complexities of federated learning and demonstrate its transformative potential in various healthcare applications. Through a combination of theoretical insights, practical guidelines, case studies, and real-world examples, the book aims to empower readers to harness the potential of federated learning to address pressing healthcare challenges effectively.Whether readers are healthcare professionals seeking to leverage data-driven approaches to improve patient care, researchers exploring innovative solutions at the intersection of machine learning and healthcare, policymakers grappling with regulatory and ethical considerations, or technologists developing cutting-edge healthcare solutions, this book serves as a valuable resource for understanding, implementing, and advancing federated learning in healthcare.

Empowering Wellness

Federated Learning Applications in Healthcare

The book explores how emerging digital technologies can address the interconnected challenges of food security, climate change, and sustainability. It delves into AI-driven predictive models for crop yield estimation, IoT-enabled soil and water monitoring, and renewable energy-powered smart irrigation systems. The book highlights practical applications of big data, precision farming, and cloud platforms to enhance productivity, reduce ecological footprints, and improve resilience to climate change. With global case studies and interdisciplinary insights, it serves as a resource for researchers, students, farmers, agribusiness leaders, and policymakers, offering actionable strategies for transforming agriculture into a climate-resilient and resource-efficient sector.

AI, Technology, and Sustainability

Smart Solutions for a Changing Climate

AI and quantum computing are two disruptive forces about to push financial services and the banking industry over the edge, demanding an unprecedented transformation. They are not fleeting trends but fundamental disruptors that will reshape the core of banking and finance. Authored by a senior Swiss banking technology executive, this practical guide helps board members and senior leaders turn disruption into a disciplined strategic agenda. It offers a rare insider perspective and a roadmap for navigating these seismic shifts. Bridging the gap between technological innovation and practical application, this book equips leaders with the tools to address the challenges and opportunities posed by AI and quantum computing. It features a thorough review of the latest business opportunities and threats associated with these technologies, alongside foresight-based strategic decision frameworks to guide prioritisation. Real-world case studies and an online companion with 125 AI use cases tailored for banks provide actionable insights. It also introduces an original AI Adoption Maturity Model and a Hybrid Enterprise Reference Architecture to ensure safe integration of internal systems with external frontier models. Finally, it provides two detailed multi-year roadmaps, offering a clear path to harness AI's potential and to prepare for a post-quantum future through crypto agility.Rather than offering abstract predictions or generic solutions, this book presents financial-services leaders with the frameworks, choices, and implementation path they need to act with confidence at a moment when waiting is no longer an option.

Evolutions at the Bleeding Edge

How AI and Quantum Computing Will Make or Break the Bank

The Algorithmic Child Consumer

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