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Ethical Decision-Making Using Artificial Intelligence
Sapna Juneja (Edited by), Juneja (Author), Rajesh Kumar Dhanaraj (Edited by), Abhinav Juneja (Edited by), Malathy Sathyamoorthy (Edited by), Asadullah Shaikh (Edited by)
9781394275281, Wiley
Hardback, published 22 July 2025
432 pages
28 x 19 x 2.5 cm, 0.666 kg
Ethical Decision-Making Using Artificial Intelligence: Challenges, Solutions, and Applications gives invaluable insights into the ethical complexities of artificial intelligence, empowering the navigation of critical decisions that shape our future in an era where AI’s influence on society is rapidly expanding. The significant impact of artificial intelligence on society cannot be overstated in a time of lightning-fast technical development and growing integration of AI into our daily lives. A new frontier of human potential has emerged with the development and application of AI technologies, pushing the limits of what is possible in the areas of innovation and efficiency. AI systems are increasingly trusted with complicated decisions that affect our security, well-being, and the fundamental foundation of our societies as they develop in intelligence and autonomy. These choices have substantial repercussions for both individuals and communities in a wide range of fields, including healthcare, finance, criminal justice, and transportation. The necessity for moral direction and deliberate decision-making procedures is critical as AI systems develop and become more independent. Ethical Decision-Making Using Artificial Intelligence: Challenges, Solutions, and Applications examines the complex relationship between artificial intelligence and the moral principles that guide its application. This book addresses fundamental concerns surrounding AI ethics, namely what moral standards ought to direct the creation and use of AI systems. In order to promote responsible AI development that is consistent with human values and goals, this book’s goal is to equip readers with the knowledge and skills they need to traverse the ethical landscape of AI decision-making.
Preface xxi 1 Standards, Policies, Ethical Guidelines and Governance in Artificial Intelligence: Insights on the Financial Sector 1 1.1 Introduction 2 1.2 Chatbots in the Financial Industry 3 1.3 Background of the Study 5 1.4 Literature Review 6 1.5 Understanding Bias in Customer Service Chatbots 8 1.6 Impact of Bias in Financial Chatbot Interactions 10 1.7 Strategies for Mitigating Bias in Financial Customer Service Chatbots 11 1.8 Ethical Considerations and Transparency in Financial Chatbot Firms 13 1.9 Future Directions and Recommendations 15 1.10 Conclusion 16 2 Domain-Specific AI Algorithms and Models in Decision-Making: An Overview 27 2.1 Introduction 28 2.2 Understanding Domain-Specific Decision Making 36 2.3 Building Blocks of AI for Decision-Making 38 2.4 Domain-Specific AI: Revolutionizing Industries 39 2.5 Ethical and Societal Implications 51 2.6 Future Directions and Emerging Trends 51 2.7 Conclusion 52 3 Role of AI in Decision-Making – A Comprehensive Study 55 3.1 Introduction 56 3.2 Need of AI-Based Decision-Making System 58 3.3 Major Obstacle for AI-Based Decision-Making System 62 3.4 Applications of AI-Based Decision-Making System 65 3.5 Case Study: AIDMS for Age-Related Macular Degeneration (amd) 70 3.6 Conclusion and Future Directions 75 4 Ethical Challenges in AI Decision]Making: From the User’s Perspective 79 4.1 Introduction 80 4.2 Public Perception towards AI 85 4.3 Ethical Dilemmas of AI 87 4.4 Emerging Issues that are Prevailing in the Current World 90 4.5 Future Considerations 95 5 Ethical Decision-Making in Yoga Posture Detection through AI: Fostering Responsible Technology Integration 99 5.1 Introduction 100 5.2 Literature Review 111 5.3 Technologies Used 112 5.4 Dataset Used 115 5.5 Methodology 117 5.6 Conclusion 119 6 Ethical AI: A Design of an Integrated Framework towards Intelligent Decision-Making in Stock Control 125 6.1 Introduction 126 6.2 Benefits and Impact of AI on Inventory Control 128 6.3 Best Practices for Implementing AI for Stock Management in E-Commerce 131 6.4 Formulation of Proposed Model 138 6.5 Conclusion 148 7 Integrating Machine Learning and Data Ethics: Frameworks for Intelligent Ethical Decision-Making 153 7.1 Introduction 154 7.2 Concept of Machine Learning and Data Ethics 155 7.3 Importance of ML and AI in Design Making 157 7.4 Defining an Intelligent Decision-Making Support System 158 7.5 Transformation of the Decision-Making System to Intelligent Decision-Making Support 159 7.6 Architecture Framework 161 7.7 Conceptual Framework 162 7.8 Cloud-Based Scalability with Auto Scaling 170 7.9 Case Study of Complex Problem Using Framework 174 7.10 Algorithm and Coding Analysis 174 7.11 Results and Impact Analysis 178 7.12 Conclusion 178 8 Importance of Human Loop in AI-Based Decision-Making: Strengthening the Ethical Perspective 183 8.1 Introduction 184 8.2 Human Interaction with AI Platform 186 8.3 Human and Machine Ethical Annotation 187 8.4 Exploring AI with Human-in-the-Loop Technique 191 8.5 Creating Ethical AI Using HTIL Technique 195 8.6 Conclusion 203 9 AI in Finance and Business: Novel Method for Human Resource Recommendation Using Improved Gradient Boosting Tree Model 207 9.1 Introduction 208 9.2 Literature Review 210 9.3 The Proposed Model 217 9.4 Evaluation of the Impact of the Technology 218 9.5 Conclusion 222 10 Comprehensive View from Ethics to AI Ethics: With Multifaceted Dimensions 227 10.1 Introduction 228 10.2 AI (Artificial Intelligence) 230 10.3 Concept of Ethics 234 10.4 AI Ethics 239 10.5 AI Ethics in Business 245 10.6 AI Ethics in Medicine 250 10.7 AI Ethics in Education 254 10.8 Conclusion 255 11 Case Study on Soil Identification for Insecticides and Fertilizer Recommendation Using IoT and Deep Learning: An Ethical Approach in Smart Agriculture 4.0 259 11.1 Introduction 260 11.2 Literature Survey 264 11.3 Problem Formulation 268 11.4 Proposed Work 269 11.5 Result and Discussion 271 11.6 Conclusion 276 12 Case Study on Ethical AI-Based Decision-Making in E-Commerce Industrial Sector: Insights on McDonald’s and Deliveroo 283 12.1 Introduction 284 12.2 Foundations of AutoML 284 12.3 Benefits and Challenges 286 12.4 Industrial Applications of AutoML: McDonald’s 289 12.5 Industrial Applications of AutoML: Deliveroo 295 12.6 Ethical Considerations 303 12.7 Future Trends 306 12.8 Conclusion 309 13 AI Insights: Navigating Education News Ethically Through Aggregation and Sentiment Analysis 313 13.1 Introduction 314 13.2 Literature Review 323 13.3 Methodology 328 13.4 Results Discussion 334 13.5 Conclusion and Future Work 339 14 Case Study on AI-Based Ethical Decision-Making for Smart Transportation 343 14.1 Introduction 344 14.2 Artificial Intelligence 345 14.3 Role of Artificial Intelligence in Transportation 347 14.4 Literature Review 348 14.5 Challenges 351 14.6 AI Ethics 351 14.7 Data Confidentiality and Security 360 14.8 Vision from Data: Smart Decision-Making in Transportation 361 14.9 Conclusions 363 14.10 Future Directions 363 15 Case Study on AI-Based Decision-Making in E-Commerce: Exploring Location-Based Insights for Analysis of Geospatial Data 367 15.1 Introduction 368 15.2 Objective 372 15.3 Background Knowledge 372 15.4 Related Work 374 15.5 Data Analysis of Geolocation Data 378 15.6 Proposed Methodology 380 15.7 Results 384 15.8 Conclusion 387 15.9 Future 387 Acknowledgment 388 References 388 Index 393
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Subject Areas: Computer science [UY]
