Trustworthy Artificial Intelligence Implementation: Introduction to the TAII Framework

Description

Rapidly developing Artificial Intelligence (AI) systems hold tremendous potential to change various domains and exert considerable influence on societies and organizations alike. More than merely a technical discipline, AI requires interaction between various professions. Based on the results of fundamental literature and empirical research, this book addresses the management’s awareness of the ethical and moral aspects of AI. It seeks to fill a literature gap and offer the management guidance on tackling Trustworthy AI Implementation (TAII) while also considering ethical dependencies within the company. The TAII Framework introduced here pursues a holistic approach to identifying systemic ethical relationships within the company ecosystem and considers corporate values, business models, and common goods aspects like the Sustainable Development Goals and the Universal Declaration of Human Rights. Further, it provides guidance on the implementation of AI ethics in organisations without requiring a deeper background in philosophy and considers the social impacts outside of the software and data engineering setting. Depending on the respective legal context or area of application, the TAII Framework can be adapted and used with a range of regulations and ethical principles. This book can serve as a case study or self-review for c-level managers and students who are interested in this field. It also offers valuable guidelines and perspectives for policymakers looking to pursue an ethical approach to AI.   Prelude Acknowledgement Contents About the Author Abbreviations List of Figures List of Tables 1: Introduction 1.1 The Challenge 1.2 Course of Action References 2: Artificial Intelligence 2.1 Terms and Definitions 2.2 Understanding of the Technology 2.3 Current and Near Future State 2.4 Challenges 2.5 Opportunities and Risks 2.6 Goals 2.7 Human Life and Behavior 2.8 Chapter Summary References 3: Ethics and Moral 3.1 How to Train Ethics? 3.2 Influence on Product Development 3.3 Ethical and Moral Challenges 3.4 Guidelines and Principles 3.5 Summary References 4: Business and Management Perspective 4.1 Current State of AI Implementations 4.2 Business Strategy 4.3 Management Decisions 4.4 Summary References 5: Empirical Study 5.1 Research Methodology 5.2 Definition of the Material References 6: Findings 6.1 Definitions 6.1.1 Moral 6.1.2 Ethics 6.1.3 Artificial Intelligence 6.2 Prioritization 6.3 Stakeholders 6.4 Guidelines and Principles 6.4.1 Advantages of Ethical AI Guidelines 6.4.2 Doubts About Ethical AI Guidelines 6.4.3 Guideline Proposals 6.4.4 Ethical AI Guideline Creators 6.4.5 Advantages of AI System Certification 6.4.6 Doubts About AI System Certification 6.5 Social Responsibility 6.5.1 Ethical Aspects of AI Systems 6.5.2 Environmental Impact 6.5.3 Social Impact 6.5.4 Societal Impact 6.5.5 Legal System Adaption 6.6 Responsibility of AI Systems 6.6.1 Transparency 6.6.2 Robustness 6.6.3 Bias 6.6.4 Privacy and Security 6.6.5 Accountability 6.7 Management Reflection 6.8 Findings and Recommendations Reference 7: TAII Framework 7.1 Introduction 7.2 Trustworthy AI 7.3 Overview of the TAII Framework 7.4 Business Model AI 7.5 Implementation Challenges of TAI 7.6 TAII Framework Canvas 7.7 Conclusion References