Ethics and Digital Transition

Marie-Hélène Abel is Professor and Head of the Computer Science department at the University of Technology of Compiègne, France. She was President of the IEEE-SMC French chapter from 2014 to 2021.Nada Matta is Professor of Knowledge Engineering and Management at the Université de Technologie de Troyes, France. She was Co-Chair of the IEEE-SMC French chapter from 2022 to 2024.Hedi Karray is Programme Manager for Artificial Intelligence at the European Innovation Council, and a former professor at the University of Technology Tarbes Occitanie Pyrénées, France. He was Co-Chair of the IEEE-SMC French chapter from 2022 to 2024.Inès Saad is Professor of Information Systems at Amiens Business School and a researcher at the UPJV's MIS laboratory, France. She is also the Chair of the ICIKS conference and the IEEE-SMC French chapter.

• Foreword xiJean-Gabriel GANASCIAIntroduction xvNada MATTA, Marie-Hélène ABEL, Hedi KARRAY and Inès SAADChapter 1 Digital Ethics: Empowering Agents and Taking Care of Systems 1Bruno BACHIMONT1.1 Introduction 11.2 Technology and ethical neutrality 31.3 What are the ethics of technology? 51.3.1 Contemporary ethics 51.3.2 The ethics of moral agents 71.4 Calculation, algorithm 101.5 The ethical challenges of digital technology 141.5.1 Complexity and technology: temporal alienation 141.5.2 Data, algorithms: alienation of property 161.5.3 Moral agents and their acolytes 181.5.4 Ethical situations 191.5.5 Empowering agents 201.5.6 Taking care of patients 221.5.7 Taking care of witnesses 231.6 Conclusion 241.7 References 25Chapter 2 Bias, Discrimination and Decision-Making: Fate or Responsibility? 29Florence SÈDES2.1 Why this question? 292.2 Bias, history and typology 312.3 Types of bias 352.4 Bias and fairness – a measure of ethics? 372.4.1 A mixed picture 372.4.2 How can we define algorithmic fairness? 402.4.3 And in practice... how can these biases be corrected? 422.4.4 Fairness and interpretability: finding the right balance? 442.5 "We are open, the door is just very heavy" 442.6 Biases: fatality or responsibility? Fatality and responsibility&... 462.6.1 Synthetic data for a qualified bias correction approach 472.7 Debiasing machines 482.8 References 49Chapter 3 Digital Technology and Artificial Intelligence: How Can We Facilitate the Ethical Control of their Use? 51Alain MILLE3.1 Introduction 513.2 Expected properties of an ethics-oriented DTD-AI 543.2.1 Property I: construction and memorization of knowledge of situated action for the technician (Simondon) as tertiary retentions (Stiegler) 593.2.2 Property II: supporting the process of discussing and regulating activity 613.3 Illustrations of DTDs integrating activity reflexivity for individual and collective documentation purposes 653.3.1 Support from M-Traces for a corporate community of practice 663.3.2 Support for human learning activity 683.3.3 Example of an activity involving a ChatGPT-type DTD-AI 693.4 Conclusion 713.5 References 76Chapter 4 Ethical Autonomous Agents: Literature Review and Illustration for Markov Decision Processes 81Grégory BONNET, Nadjet BOURDACHE, Abdel-Illah MOUADDIB and Mihail STOJANOVSKI4.1 Introduction 814.2 Issues specific to the integration of ethics 834.2.1 A high-level approach to ethics 834.2.2 Programming ethical autonomous agents 854.3 Ethical autonomous agents: state of the art 874.3.1 Qualitative implicit architectures 874.3.2 Qualitative cognitive architectures 884.3.3 Quantitative cognitive architectures 934.3.4 Learning an ethical model 954.3.5 Intermediate conclusion 974.4 Ethical Markov decision processes 984.4.1 Markov processes and ethical contexts 994.4.2 Modeling ethics 1024.4.3 Solving E-MDPs 1054.5 Establishing ethical principles in E-MDPs 1074.5.1 Theory of divine command 1074.5.2 Prima facie duties 1094.5.3 Virtue ethics 1104.6 Conclusion 1144.7 References 115Chapter 5 Ethics and Ecology in Production Systems 121Emmanuel CAILLAUD and Lou GRIMAL5.1 Introduction 1215.2 Ecological context 1225.3 Integrating ethical issues into an industry in ecological transition 1265.3.1 Attempts to meet standards 1285.3.2 From environmental ethics to ecological ethics 1325.3.3 Ecological ethics and technology 1335.4 Proposed areas of work 1345.4.1 Competence of production system players 1345.4.2 Purpose of the production system 1355.4.3 Returning to planetary limits with available technical systems 1365.5 Conclusion 1375.6 Acknowledgments 1385.7 References 138Chapter 6 Operational Ethics in Industrial Systems of the Future: Methodological Elements 141Damien TRENTESAUX, Lamia BERRAH and Karine SAMUEL6.1 Introduction 1416.2 Ethics: definition, typologies and paradigms 1446.3 Performance management for 4.0 industrial systems and its ethical risks 1476.3.1 Overview 1476.3.2 State of the art on ethics in industrial systems of the future 1496.4 Toward the operational integration of ethics in the 4.0 industrial systems 1536.4.1 Scope 1546.4.2 Methodological elements 1546.5 Industrial testimony 1596.6 Conclusion 1646.7 Acknowledgements 1656.8 References 165Chapter 7 AI for Industry: Transforming the Daily Lives of Maintenance Operators 171Anne DOURGNON, Eunika MERCIER LAURENT and Alain ANTOINE7.1 Genesis of this innovation 1717.2 Background of this innovation 1737.2.1 A low-key innovation 1737.3 The naysayers 1747.4 Dealing with hazards 1767.5 A decisive demonstration 1777.6 The keys to success 1787.7 Overcoming obstacles 1797.8 Outlook 1807.9 Acknowledgments 1817.10 References 181Conclusion 183Hedi KARRAYC.1 From ethics to responsibility 183C.2 Principles and challenges behind responsible AI 184C.3 Responsible AI: a threat or an opportunity? 186C.4 Responsible AI challenges 187C.5 An ecosystem for responsible AI 189C.5.1 Actions for responsible AI 190C.5.2 Policy measures: initiatives and regulations 191C.5.3 Technical progress 191C.5.4 Public awareness and education 192C.6 References 192List of Authors 195Index 197