Ethics of artificial intelligence

In: The international library of ethics, law and technology volume 41

Abstract

Intro -- Acknowledgments -- Contents -- Chapter 1: Introduction -- References -- Part I: Can an AI System Be Ethical? -- Chapter 2: Bias and Discrimination in Machine Decision-Making Systems -- 2.1 Introduction -- 2.2 Why Machine Failure Is More Serious -- 2.3 How Machine Learning Works -- 2.4 What Is Meant by Machine Discrimination -- 2.4.1 Fairness Through Unawareness -- 2.4.2 Individual Fairness -- 2.4.3 Counterfactual Fairness -- 2.4.4 Group Fairness -- 2.4.5 Impossibility of Fairness -- 2.5 What We Are Talking About: Example of Machine Discrimination -- 2.6 Why Machine Learning Can Discriminate -- 2.7 How Machine Discrimination Can Be Overcome -- 2.7.1 Pre-processing for Fairness -- 2.7.2 In-training for Fairness -- 2.7.3 Post-processing for Fairness -- 2.8 Conclusion -- References -- Chapter 3: Opacity, Machine Learning and Explainable AI -- 3.1 Introduction -- 3.2 Fundamentals of Trustworthy and Explainable Artificial Intelligence -- 3.3 Dimensions and Strategies for Promoting Explainablity and Interpretability -- 3.3.1 Dimensions of Explainability and Interpretability -- 3.3.2 Interpretability Strategies -- 3.4 Digging Deeper on Counterfactual Explanations -- 3.4.1 Basics of Counterfactual Explanations -- 3.4.2 Overview on Techniques for Counterfactual Explanations -- 3.5 Future Challenges for Achieving Explainable Artificial Intelligence -- 3.5.1 Multimodal Data Fusion for Improved Explainability -- 3.5.2 Reliable and Auditable Machine Learning Systems -- 3.5.3 GPAI Algorithms to Learn to Explain -- 3.6 Concluding Remarks -- References -- Chapter 4: The Moral Status of AI Entities -- 4.1 Introduction -- 4.2 Can Machines Be Moral Agents? -- 4.3 Do We Need a Mind to Attribute Moral Agency? -- 4.4 The Challenge of Responsibility -- 4.5 Artificial Moral Patients and Rights -- 4.6 Relationalist Proposals -- 4.7 Conclusion -- References.