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An Introduction to Ethics in Robotics and AI / / by Christoph Bartneck, Christoph Lütge, Alan Wagner, Sean Welsh
| An Introduction to Ethics in Robotics and AI / / by Christoph Bartneck, Christoph Lütge, Alan Wagner, Sean Welsh |
| Autore | Bartneck Christoph <1973-> |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Springer Nature, 2021 |
| Descrizione fisica | 1 online resource (XI, 117 p. 18 illus. in color.) |
| Disciplina |
601
174.90063 |
| Collana | SpringerBriefs in Ethics |
| Soggetto topico |
Engineering ethics
Robotics Psychology, Applied Engineering Ethics Applied Psychology |
| Soggetto non controllato |
Engineering Ethics
Robotics Applied Psychology Moral Philosophy and Applied Ethics Behavioral Sciences and Psychology AI and ethics ethics and robotics descriptive ethics relationship between ethics and law machine ethics machine meta-ethics machine normative ethics types of AI systems strong and weak AI challenges of AI Open Access Ethics & moral philosophy Technology: general issues Artificial intelligence Psychology |
| ISBN | 3-030-51110-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- List of Figures -- 1 About the Book -- 1.1 Authors -- 1.2 Structure of the Book -- 2 What Is AI? -- 2.1 Introduction to AI -- 2.1.1 The Turing Test -- 2.1.2 Strong and Weak AI -- 2.1.3 Types of AI Systems -- 2.2 What Is Machine Learning? -- 2.3 What Is a Robot? -- 2.3.1 Sense-Plan-Act -- 2.3.2 System Integration. Necessary but Difficult -- 2.4 What Is Hard for AI -- 2.5 Science and Fiction of AI -- 3 What Is Ethics? -- 3.1 Descriptive Ethics -- 3.2 Normative Ethics -- 3.2.1 Deontological Ethics -- 3.2.2 Consequentialist Ethics -- 3.2.3 Virtue Ethics -- 3.3 Meta-ethics -- 3.4 Applied Ethics -- 3.5 Relationship Between Ethics and Law -- 3.6 Machine Ethics -- 3.6.1 Machine Ethics Examples -- 3.6.2 Moral Diversity and Testing -- 4 Trust and Fairness in AI Systems -- 4.1 User Acceptance and Trust -- 4.2 Functional Elements of Trust -- 4.3 Ethical Principles for Trustworthy and Fair AI -- 4.3.1 Non-maleficence -- 4.3.2 Beneficence -- 4.3.3 Autonomy -- 4.3.4 Justice -- 4.3.5 Explicability -- 4.4 Conclusion -- 5 Responsibility and Liability in the Case of AI Systems -- 5.1 Example 1: Crash of an Autonomous Vehicle -- 5.2 Example 2: Mistargeting by an Autonomous Weapon -- 5.2.1 Attribution of Responsibility and Liability -- 5.2.2 Moral Responsibility Versus Liability -- 5.3 Strict Liability -- 5.4 Complex Liability: The Problem of Many Hands -- 5.5 Consequences of Liability: Sanctions -- 6 Risks in the Business of AI -- 6.1 General Business Risks -- 6.1.1 Functional Risk -- 6.1.2 Systemic Risk -- 6.1.3 Risk of Fraud -- 6.1.4 Safety Risk -- 6.2 Ethical Risks of AI -- 6.2.1 Reputational Risk -- 6.2.2 Legal Risk -- 6.2.3 Environmental Risk -- 6.2.4 Social Risk -- 6.3 Managing Risk of AI -- 6.4 Business Ethics for AI Companies -- 6.5 Risks of AI to Workers -- 7 Psychological Aspects of AI -- 7.1 Problems of Anthropomorphisation.
7.1.1 Misplaced Feelings Towards AI -- 7.1.2 Misplaced Trust in AI -- 7.2 Persuasive AI -- 7.3 Unidirectional Emotional Bonding with AI -- 8 Privacy Issues of AI -- 8.1 What Is Privacy? -- 8.2 Why AI Needs Data -- 8.3 Private Data Collection and Its Dangers -- 8.3.1 Persistence Surveillance -- 8.3.2 Usage of Private Data for Non-intended Purposes -- 8.3.3 Auto Insurance Discrimination -- 8.3.4 The Chinese Social Credit System -- 8.4 Future Perspectives -- 9 Application Areas of AI -- 9.1 Ethical Issues Related to AI Enhancement -- 9.1.1 Restoration Versus Enhancement -- 9.1.2 Enhancement for the Purpose of Competition -- 9.2 Ethical Issues Related to Robots and Healthcare -- 9.3 Robots and Telemedicine -- 9.3.1 Older Adults and Social Isolation -- 9.3.2 Nudging -- 9.3.3 Psychological Care -- 9.3.4 Exoskeletons -- 9.3.5 Quality of Care -- 9.4 Education -- 9.4.1 AI in Educational Administrative Support -- 9.4.2 Teaching -- 9.4.3 Forecasting Students' Performance -- 9.5 Sex Robots -- 10 Autonomous Vehicles -- 10.1 Levels of Autonomous Driving -- 10.2 Current Situation -- 10.3 Ethical Benefits of AVs -- 10.4 Accidents with AVs -- 10.5 Ethical Guidelines for AVs -- 10.6 Ethical Questions in AVs -- 10.6.1 Accountability and Liability -- 10.6.2 Situations of Unavoidable Accidents -- 10.6.3 Privacy Issues -- 10.6.4 Security -- 10.6.5 Appropriate Design of Human-Machine Interface -- 10.6.6 Machine Learning -- 10.6.7 Manually Overruling the System? -- 10.6.8 Possible Ethical Questions in Future Scenarios -- 11 Military Uses of AI -- 11.1 Definitions -- 11.2 The Use of Autonomous Weapons Systems -- 11.2.1 Discrimination -- 11.2.2 Proportionality -- 11.2.3 Responsibility -- 11.3 Regulations Governing an AWS -- 11.4 Ethical Arguments for and Against AI for Military Purposes -- 11.4.1 Arguments in Favour -- 11.4.2 Arguments Against -- 11.5 Conclusion. 12 Ethics in AI and Robotics: A Strategic Challenge -- 12.1 The Role of Ethics -- 12.2 International Cooperation -- Appendix References -- -- Index. |
| Record Nr. | UNINA-9910416118603321 |
Bartneck Christoph <1973->
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| Springer Nature, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Robust Intelligence and Trust in Autonomous Systems / / edited by Ranjeev Mittu, Donald Sofge, Alan Wagner, W.F. Lawless
| Robust Intelligence and Trust in Autonomous Systems / / edited by Ranjeev Mittu, Donald Sofge, Alan Wagner, W.F. Lawless |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | New York, NY : , : Springer US : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (277 p.) |
| Disciplina | 004 |
| Soggetto topico |
Artificial intelligence
Robotics Automation Computational intelligence Artificial Intelligence Robotics and Automation Computational Intelligence |
| ISBN | 1-4899-7668-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Towards modeling the behavior of autonomous systems and humans for trusted operations -- Learning trustworthy behaviors using an inverse trust metric -- The “Trust V”—Building and measuring trust in autonomous systems -- Big Data analytic paradigms—From principle component analysis to deep learning -- Artificial brain systems based on neural network discrete chaotic dynamics. Toward the development of conscious and rational robots -- Modeling and control of trust in human-robot collaborative manufacturing -- Investigating human-robot trust in emergency scenarios: methodological lessons learned -- Designing for robust and effective teamwork in human-agent teams -- Measuring Trust in Human Robot Interactions: Development of the “Trust Perception Scale-HRI” -- Methods for developing trust models for intelligent systems -- The intersection of robust intelligence and trust: Hybrid teams, firms & systems. |
| Record Nr. | UNINA-9910254994403321 |
| New York, NY : , : Springer US : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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