{"product_id":"responsible-ai-principles-and-practices-hardback-9781394355440","title":"Responsible AI; Principles and Practices (Hardback) 9781394355440","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eResponsible AI\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003ePrinciples and Practices\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eManish Kumar (Edited by), M Kumar (Author), Nitigya Sambyal (Edited by), Leena P. Singh (Edited by), V. Ramasamy (Edited by), S. Balamurugan (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394355440, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 25 March 2026\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e448 pages\u003cbr\u003e22.9 x 15.2 x 2.7 cm, 0.812 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eBridge the gap between groundbreaking AI innovation and ethical responsibility with this comprehensive guide to the expert-led frameworks needed to navigate the complex legal, social, and moral landscapes of our digital future.\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eArtificial Intelligence (AI) has emerged as a transformative force with the ability to bring new innovations to reshape economies, industries, and our daily lives. From advanced medical diagnostics to autonomous vehicles, AI systems are driving incomparable innovations in every sector. These advancements promise unmatched benefits and provide the potential to solve some of humanity’s most pressing challenges. However, there are many potential challenges and significant risks that come alongside the benefits provided by AI. \u003c\/p\u003e\n\u003cp\u003eThis book offers a multidisciplinary viewpoint on how to develop and use AI systems responsibly by offering a deep dive into the ethical, legal, and societal ramifications of artificial intelligence. It explores important subjects such as algorithmic fairness, transparency, accountability, and governance through contributions from notable academics, engineers, and policy specialists. It highlights how crucial it is to match AI development with democratic norms and human values, offering both theoretical frameworks and workable implementation solutions for a range of industries. This comprehensive guide is an essential resource for scholars, professionals, and legislators dedicated to making sure that AI technology is created and applied in ways that are moral, inclusive, and advantageous to society. \u003c\/p\u003e\n\u003cp\u003eThe reader will find the volume: \u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eProvides a multidisciplinary exploration of the ethical, legal, and social dimensions of AI;\u003c\/li\u003e \u003cli\u003eBridges the gap between AI theory and real-world applications through practical frameworks;\u003c\/li\u003e \u003cli\u003eCovers key topics such as fairness, transparency, accountability, and governance;\u003c\/li\u003e \u003cli\u003eServes as a valuable resource for researchers, practitioners, and policymakers aiming to build trustworthy AI systems.\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003cb\u003eAudience\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eAI practitioners, data scientists, developers, business leaders, and executives actively engaged in the development and implementation of AI systems.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003eSeries Preface xxi\u003cbr\u003ePreface xxiii\u003cbr\u003eAcknowledgement xxvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 AI for Social Good 1\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eR. Srivats, Kalyanasundaram V., Abhiram Sharma, Deepika Roselind J. and Logeswari G.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction to AI for Social Good 2\u003cbr\u003e1.2 AI in Healthcare 6\u003cbr\u003e1.3 AI in Education 10\u003cbr\u003e1.4 AI for Disaster Management and Response 14\u003cbr\u003e1.5 AI in Culture 17\u003cbr\u003e1.6 Conclusion and Future Work 24\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Balancing Innovation and Patient Safety: Ethical AI Deployment in Healthcare 29\u003c\/b\u003e\u003cbr\u003e\u003ci\u003ePrajakta R. Patil, Sachin S. Mali, Riya R. Patil and Dhanashree R. Davare\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 29\u003cbr\u003e2.2 The Promise of AI in Healthcare 34\u003cbr\u003e2.3 Ethical Challenges in AI 36\u003cbr\u003e2.4 Responsible AI Development and Deployment 39\u003cbr\u003e2.5 Case Studies: Real-World Examples of Ethical AI in Healthcare 46\u003cbr\u003e2.6 Strategies for Ensuring Ethical and Responsible Use of AI 52\u003cbr\u003e2.7 The Future of Ethical AI in Healthcare 56\u003cbr\u003e2.8 Conclusion 58\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Responsible AI in Practice: Case Studies from Industry and Government 69\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eNabanita Roy, Sangita Roy and Shalini Kumari\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 69\u003cbr\u003e3.2 Framework for Analyzing Responsible AI Implementation 71\u003cbr\u003e3.3 Literature Review 72\u003cbr\u003e3.4 Case Studies 72\u003cbr\u003e3.5 Cross-Sector Analysis: Patterns in Responsible AI Implementation 74\u003cbr\u003e3.6 Emerging Regulatory Landscape 75\u003cbr\u003e3.7 Recommendations for Organizations 75\u003cbr\u003e3.8 Discussion 78\u003cbr\u003e3.9 Conclusion 79\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 An Efficient System for Skin Disease Detection and Localization Using Faster Region Based Convolutional Neural Networks with Inception Architecture 81\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eNitin Singh, Ankita Nanda, Keshav Garg, Varun Gupta, Nitigya Sambyal and Deepika Vikas Agrawal\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 82\u003cbr\u003e4.2 Related Work 84\u003cbr\u003e4.3 Proposed System 86\u003cbr\u003e4.4 Results 96\u003cbr\u003e4.5 Conclusion 100\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Detection of Machining Error Using Intelligent Hybrid Machine Learning Technique 105\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eRitu Maity\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 106\u003cbr\u003e5.2 Literature Review 106\u003cbr\u003e5.3 Models Used 108\u003cbr\u003e5.4 Methodology 109\u003cbr\u003e5.5 Results and Discussion 113\u003cbr\u003e5.6 Conclusion 116\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Ground Water Level Classification Using Machine Learning 119\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eCharu Chaudhary, Khushi Passi, Taruna Saini, Ritika Dhaneshwar and Varun Gupta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 120\u003cbr\u003e6.2 Related Work 121\u003cbr\u003e6.3 Data Description and Data Processing 124\u003cbr\u003e6.4 Results and Discussion 130\u003cbr\u003e6.5 Conclusion 139\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Sustainability in AI Development 143\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eRiya R. Patil, Sandip A. Bandgar, Sachin S. Mali, Prajakta R. Patil and Dhanashree R. Davare\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 144\u003cbr\u003e7.2 Environmental Sustainability in AI 148\u003cbr\u003e7.3 Social Sustainability in AI 152\u003cbr\u003e7.4 Economic Sustainability in AI 157\u003cbr\u003e7.5 Governance and Policy for Sustainable AI 159\u003cbr\u003e7.6 Challenges and Future Directions 164\u003cbr\u003e7.7 Conclusion and Call to Action 167\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Integrating AutoML and Explainability: A Unified Approach for Decision-Making in Engineering and Social Sciences 175\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eAyush Dalmia and Chandramohan Dhasarathan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 176\u003cbr\u003e8.2 Literature Study 178\u003cbr\u003e8.3 Proposed Model 183\u003cbr\u003e8.4 Evaluation of the Proposed System (Comparative Analysis\/Justification with Acceptable Measures\/Metrics) 186\u003cbr\u003e8.5 Observations 195\u003cbr\u003e8.6 Conclusion 196\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Trust Dynamics and Ethical Transparency in AI-Powered Mobile Apps: A Data‑Driven Exploration of User Perceptions 199\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eRachita Sambyal\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 200\u003cbr\u003e9.2 Review of Literature 201\u003cbr\u003e9.3 Research Methodology 204\u003cbr\u003e9.4 Results and Discussion 204\u003cbr\u003e9.5 Results and Recommendations 212\u003cbr\u003e9.6 Limitations and Future Scope 212\u003cbr\u003e9.7 Conclusion 212\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 AI-Powered Advancements in Autonomous Vehicle Technologies 221\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSachi Choudhary and Prashant Shukla\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 222\u003cbr\u003e10.2 Core AI Technologies for AVs 224\u003cbr\u003e10.3 Machine Learning and Deep Learning Techniques for AVs 226\u003cbr\u003e10.4 Computer Vision and Image Processing in AVs 228\u003cbr\u003e10.5 Sensor Fusion and Environmental Perception in AVs 231\u003cbr\u003e10.6 Object Detection and Classification in Autonomous Vehicles (AVs) 233\u003cbr\u003e10.7 Decision-Making and Path Planning in AVs 235\u003cbr\u003e10.8 AI's Role in Route Optimization, Path Planning, and Obstacle Avoidance 239\u003cbr\u003e10.9 Challenges of AI in Autonomous Vehicles 240\u003cbr\u003e10.10 Conclusion 241\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Data Security and Privacy Frameworks for AI Technologies 247\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSangita Roy and Nabanita Roy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 248\u003cbr\u003e11.2 Foundations of Data Security and Privacy in AI 249\u003cbr\u003e11.3 Challenges in AI-Specific Privacy and Security 251\u003cbr\u003e11.4 Privacy-Preserving AI Technologies 251\u003cbr\u003e11.5 Regulatory and Legal Frameworks 255\u003cbr\u003e11.6 Organizational Privacy and Security Frameworks 258\u003cbr\u003e11.7 Case Studies 259\u003cbr\u003e11.8 Designing Privacy-Centric AI Systems 261\u003cbr\u003e11.9 Future Directions 264\u003cbr\u003e11.10 Conclusion 266\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 AI in Autonomous Systems 269\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eKalyanasundaram V., G. Prethija, Keerthi A.J., Yuvan Shankar Baabu and R. Srivats\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction to AI in Autonomous Systems 270\u003cbr\u003e12.2 AI Technologies in Autonomous Systems 274\u003cbr\u003e12.3 Autonomous Vehicles and Real-Time Decision Making 279\u003cbr\u003e12.4 AI Innovations in Space and Healthcare Systems 284\u003cbr\u003e12.5 Safety, Ethical Considerations, and Challenges 288\u003cbr\u003e12.6 Future Directions and Conclusion 291\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Responsible Use of AI in Healthcare: Addressing Bias, Transparency, and Patient Trust 297\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eShubham Gupta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 298\u003cbr\u003e13.2 Ethical Challenges in AI-Driven Healthcare 300\u003cbr\u003e13.3 Transparency in AI Systems 306\u003cbr\u003e13.4 Building and Maintaining Patient Trust 311\u003cbr\u003e13.5 Governance and Regulatory Oversight 314\u003cbr\u003e13.6 The Future of Ethical AI in Healthcare 318\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Advancing Healthcare with AI: Balancing Efficiency, Security, and Compliance 323\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSivakumar Ramakrishnan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 324\u003cbr\u003e14.2 Literature Review 329\u003cbr\u003e14.3 Identified Gaps in Literature and Future Directions 332\u003cbr\u003e14.4 Methodology 333\u003cbr\u003e14.5 Result and Discussion 345\u003cbr\u003e14.6 Case Studies and Real-World Examples 351\u003cbr\u003e14.7 Ethical Considerations in AI-Based Healthcare Fraud Detection 353\u003cbr\u003e14.8 Blockchain and Federated Learning: Securing AI-Based Healthcare Transactions Blockchain in Healthcare Transactions 357\u003cbr\u003e14.9 AI's Limitations and the Evolution of Fraud Strategies 357\u003cbr\u003e14.10 Conclusion 359\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 AI Beyond the Veil: Techniques for Privacy Preservation 363\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eD. Kalpanadevi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 364\u003cbr\u003e15.2 Scope of Research 364\u003cbr\u003e15.3 Background 365\u003cbr\u003e15.4 Techniques for Privacy Preservation 365\u003cbr\u003e15.5 Implementation and Discussion 373\u003cbr\u003e15.6 Current Challenges 375\u003cbr\u003e15.7 Industry Adoption 376\u003cbr\u003e15.8 Future Directions 377\u003cbr\u003e15.9 Conclusion 377\u003cbr\u003eReferences 378\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 VetAce – A Deep Learning Inspired Framework for Classification and Prediction of Pet Diseases 379\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eMunish Saini, Vaibhav Arora and Harpreet Singh\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 380\u003cbr\u003e16.2 Related Work 381\u003cbr\u003e16.3 Analysis Methodology 383\u003cbr\u003e16.4 Results and Analysis 391\u003cbr\u003e16.5 Discussion 395\u003cbr\u003e16.6 Conclusion 396\u003c\/p\u003e \u003cp\u003eBibliography 397\u003cbr\u003eIndex 401\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Scrivener","offers":[{"title":"Brand New","offer_id":52433823990040,"sku":"9781394355440","price":156.36,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394355440.jpg?v=1784854215","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/responsible-ai-principles-and-practices-hardback-9781394355440","provider":"Freshly Printed Books","version":"1.0","type":"link"}