Werthner, Hannes.
Introduction to Digital Humanism : A Textbook. - 1st ed. - 1 online resource (631 pages)
Intro -- Preface -- Contents -- Part I: Background -- Humanism and Enlightenment -- 1 Introduction -- 2 Digitalization: Age of the Enlightenment 2.0 or the Counter-Enlightenment? -- 3 What Does Humanism Mean and Where Does the Term Come From? -- 4 Education as a Humanistic Ideal Has Two Components: One Theoretical and One Practical -- 5 Why Is the Enlightenment so Important for Humanism? -- 6 Conclusions -- References -- Philosophical Foundations of Digital Humanism -- 1 Introduction -- 2 The Humanist Practice of Attributing Responsibility and the Conceptual Connection Between Responsibility, Freedom, and Reason -- 3 Conclusions -- 3.1 Theoretical Implications of Digital Humanism -- 3.1.1 Rejection of Mechanistic Paradigm: Humans Are Not Machines -- 3.1.2 Rejection of the Animistic Paradigm: Machines Are Not (Like) Humans -- 3.2 Practical Implications of Digital Humanism -- References -- Evolution of Computing -- 1 Introduction -- 2 Prehistory -- 3 Computers as Calculators -- 4 Computers and Communications -- 5 Computing as a Science -- 6 Hardware ``Laws�� -- 7 Personal Computers -- 8 Natural Interfaces -- 9 The Internet -- 10 Mobile Computing -- 11 Machine Learning -- 12 Big Data and Cloud Computing -- 13 Security and Privacy -- 14 Conclusions -- References -- The Digital Revolution in a Historical Perspective -- 1 Introduction -- 2 Renaissance, Reformation, Printing, and Ships, 1440-1648 -- 3 The French Revolution, Steam Power, and the Industrial Revolution, 1769-1945 -- 4 The Collapse of Communism and Information Technology, 1973-2023 -- 5 Conclusions -- References -- The Social Responsibilities of Scientists and Technologists in the Digital Age -- 1 Introduction -- 2 On the Social Responsibilities of Scientists in the Atomic Age -- 3 Fast Forward to the Digital Age. 3.1 General Elements of the Social Responsibility of Scientists and Technologists -- 3.2 Societal Impacts of Digital Technologies and the Sustainable Development Goals -- 4 Governance, Public Values, and Fairness in Digital Ecosystems -- 5 Conclusions -- References -- Digital Transformation Through the Lens of Intersectional Gender Research Challenges and Needs for Action -- 1 Introduction -- 2 Intersectional Gender Research, Feminist Theory, and Digital Technology -- 2.1 Intersectional Gender Research -- 2.2 Feminist Theory and Epistemologies -- 2.3 How Gender and Technology Interact -- 3 Conclusions -- References -- No Digital Citizens Without Digital Humanism -- 1 Introduction -- 2 The Challenge: Cognitive Machines -- 3 The Social Impact of Digital Technology -- 4 An Example: The European Approach to Digital Education -- 5 Priorities in Education -- 6 Conclusions -- References -- Digital Transformation, Digital Humanism: What Needs to Be Done -- 1 Introduction -- 2 Some Notes on Informatics -- 3 The Web, Its Impact, and Transformation -- 4 ``The System Is Failing�� -- 5 Digital Humanism and the Vienna Manifesto -- 6 The Digital Humanism Initiative -- 7 Research and Innovation Roadmap -- 8 Conclusions -- References -- Part II: Digital Humanism: A System�s View -- A Short Introduction to Artificial Intelligence: Methods, Success Stories, and Current Limitations -- 1 Introduction -- 2 Methods of AI -- 2.1 Symbolic AI -- 2.2 Machine Learning -- 2.3 Combination of Methods -- 3 Reflections -- 3.1 AI4Good -- 3.2 Is ChatGPT a Tipping Point? -- 3.3 Pressing Issues -- 4 Conclusions -- References -- Trustworthy Artificial Intelligence: Comprehensible, Transparent and Correctable -- 1 Introduction -- 2 Problems with Data-Intensive Machine Learning: Unfairness, Biases and Missing Robustness. 3 Explainable Artificial Intelligence: Comprehensibility of Machine-Learned Models -- 4 Third-Wave AI Methods: Hybrid, Comprehensible and Correctable -- 5 Conclusions -- References -- Are We in Control? -- 1 Introduction -- 2 Fear -- 3 Pushback -- 4 Information Flood -- 5 Digital Creationism -- 6 Coevolution -- 7 Regulation -- 8 Feedback -- 9 Actions -- 10 Conclusions -- References -- AI @ Work: Human Empowerment or Disempowerment? -- 1 Introduction -- 2 Algorithmic Decision Systems -- 3 How ADS Impact Decision Outcomes -- 4 How ADSs Change Work -- 4.1 Assignment of Tasks to Roles -- 4.2 Self-Assessment, Self-Efficacy, and Human Competences -- 4.3 Human Oversight and Accountability -- 5 Conclusions -- References -- The Re-enchanted Universe of AI: The Place for Human Agency -- 1 Introduction -- 2 Questioning Our Assumptions: What ChatGPT Is and What It Does -- 3 Technologies as Agents of Change: The Externalization of Knowledge Operations -- 4 They Are Like Us: The Re-enchanted Universe of AI -- 5 Redefining Human Agency -- 6 Conclusions -- References -- Aesthetic Aspects of Digital Humanism: An Aesthetic-Philosophical Analysis of Whether AI Can Create Art -- 1 Introduction -- 2 Aesthetics Is the Study of the Subject of Art, and Kant Is One of Its Most Influential Representatives -- 3 According to the KAA, There Is No Art Without (Artistic) Freedom -- 4 What Is the State of the Art in Art-Making AI? -- 5 Can AI Create Art from an Aesthetic-Philosophical Standpoint? -- 6 Conclusions -- References -- Approaches to Ethical AI -- 1 Introduction -- 2 Ethical AI -- 2.1 Can AI Be Ethical? -- 3 Approaches to Ethical AI -- 3.1 Ethical AI Frameworks -- 3.2 Philosophical Principlism -- 3.3 Challenges and Limitations of Ethical Frameworks -- 4 From Principles to Practice -- 4.1 Further Research Directions -- 5 Conclusions -- References. Artificial Intelligence and Large-Scale Threats to Humanity -- 1 Introduction -- 2 AI and the Climate Crisis -- 3 AI and Nuclear Deterrence -- 4 Militarization of AI and Nuclear Defense Modernization -- 5 Responsibilities of AI Stakeholders and Large-Scale Threats to Humanity -- 6 Conclusions -- References -- Promises and Perils in Moralizing Technologies -- 1 Introduction -- 2 Conceptual Framework -- 3 Moralizing Technologies -- 4 Exploring the Promises and Perils of Moralizing Technologies -- 5 Conclusions -- References -- The Road Less Taken: Pathways to Ethical and Responsible Technologies -- 1 Introduction -- 2 Human-Adjacent Computing -- 3 Human-Aware Computing -- 4 Human-Centered Computing -- 4.1 Thinking About Technology and People -- 4.2 Development Objectives -- 4.3 Participants -- 4.4 Ethical and Responsible Computing and the Socio-technical System -- 4.5 From Technology Development to Sociotechnical System Orchestration -- 5 Conclusions -- References -- Bridging the Digital Divide -- 1 Introduction -- 2 Short History of the Efforts to Bridge the Digital Divide -- 3 The Digital Divide Through a Decolonial Lens -- 4 Requirements for a Human-Centered Approach -- 5 Combining Action Research, Design Science, and Ethics Perspective -- 6 Tiballi: A Case Study of AI and Data Science for Farmers in Ghana -- 7 Discussion on Critical and Societal Issues -- 8 Conclusions -- References -- Responsible Software Engineering: Requirements and Goals -- 1 Introduction -- 2 Requirements Engineering (RE) -- 2.1 Introduction to RE -- 2.2 Requirements and Goals -- 2.3 The Need for Human-Centered Values -- 3 Values We Live By: Eliciting, Articulating, and Organizing Goals -- 3.1 Values and RE Activities -- 3.2 Values and Goals -- 4 Toward Responsible Software Engineering: DigHum Goals in the Life Cycle -- 4.1 Requirements and Other Activities. 4.2 Software Processes -- 4.3 Validation and Verification -- 4.4 The Running System -- 5 Conclusions -- References -- Governance for Digital Humanism: The Role of Regulation, Standardization, and Certification -- 1 Introduction -- 2 Background to AI Principles, Regulation, and Standards -- 2.1 The Principles -- 2.2 The Role of Regulation -- 2.3 The Standards -- 2.4 The Role of Standards and Certification -- 2.5 What Is AI (and Data) Governance and Why Is It Necessary? -- 2.6 Key Areas for Any Responsible AI Governance Operating Model -- 2.7 Accountability -- 2.8 Algorithmic Bias -- 2.9 Transparency -- 2.10 Ethical Privacy -- 3 Application of the Principles and the Governance Operational Model -- 4 Use Case: Wiener Stadtwerke (The IEEE CertifAIEd Framework for AI Ethics Applied to the City of Vienna, 2021) -- 5 Assessment of Wiener Stadtwerke�s Email Classification System -- 6 Conclusions -- References -- Value-Sensitive Software Design: Ethical Deliberation in Agile Development Processes -- 1 Introduction -- 2 Codes of Conduct and Software Development -- 3 Ethical Deliberation -- 4 Individual Responsibility of the Software Engineer -- 5 Agile Software Development -- 6 Ethical Deliberation in Agile Processes -- 7 Example -- 7.1 Ethical Deliberation: Disclosive Contemplation -- 7.2 Ethical Deliberation: Weighing Contemplation and Sprint Planning -- 7.3 Ethical Deliberation: Applicative Contemplation to the Increment -- 7.4 Ethical Deliberation: Sprint Review and Sprint Retrospective -- 8 Conclusions -- References -- Humans in the Loop: People at the Heart of Systems Development -- 1 Introduction -- 2 People as Creators of Software Systems -- 2.1 Specialists such as Software Engineers -- 2.2 Non-specialists such as Domain Experts -- 3 People as Users of Software Systems -- 3.1 Taking Account of Users and What They Do. 3.2 Software Use Influences Future Development.
9783031453045
Electronic books.
QA76.9.C66
801/.95
Introduction to Digital Humanism : A Textbook. - 1st ed. - 1 online resource (631 pages)
Intro -- Preface -- Contents -- Part I: Background -- Humanism and Enlightenment -- 1 Introduction -- 2 Digitalization: Age of the Enlightenment 2.0 or the Counter-Enlightenment? -- 3 What Does Humanism Mean and Where Does the Term Come From? -- 4 Education as a Humanistic Ideal Has Two Components: One Theoretical and One Practical -- 5 Why Is the Enlightenment so Important for Humanism? -- 6 Conclusions -- References -- Philosophical Foundations of Digital Humanism -- 1 Introduction -- 2 The Humanist Practice of Attributing Responsibility and the Conceptual Connection Between Responsibility, Freedom, and Reason -- 3 Conclusions -- 3.1 Theoretical Implications of Digital Humanism -- 3.1.1 Rejection of Mechanistic Paradigm: Humans Are Not Machines -- 3.1.2 Rejection of the Animistic Paradigm: Machines Are Not (Like) Humans -- 3.2 Practical Implications of Digital Humanism -- References -- Evolution of Computing -- 1 Introduction -- 2 Prehistory -- 3 Computers as Calculators -- 4 Computers and Communications -- 5 Computing as a Science -- 6 Hardware ``Laws�� -- 7 Personal Computers -- 8 Natural Interfaces -- 9 The Internet -- 10 Mobile Computing -- 11 Machine Learning -- 12 Big Data and Cloud Computing -- 13 Security and Privacy -- 14 Conclusions -- References -- The Digital Revolution in a Historical Perspective -- 1 Introduction -- 2 Renaissance, Reformation, Printing, and Ships, 1440-1648 -- 3 The French Revolution, Steam Power, and the Industrial Revolution, 1769-1945 -- 4 The Collapse of Communism and Information Technology, 1973-2023 -- 5 Conclusions -- References -- The Social Responsibilities of Scientists and Technologists in the Digital Age -- 1 Introduction -- 2 On the Social Responsibilities of Scientists in the Atomic Age -- 3 Fast Forward to the Digital Age. 3.1 General Elements of the Social Responsibility of Scientists and Technologists -- 3.2 Societal Impacts of Digital Technologies and the Sustainable Development Goals -- 4 Governance, Public Values, and Fairness in Digital Ecosystems -- 5 Conclusions -- References -- Digital Transformation Through the Lens of Intersectional Gender Research Challenges and Needs for Action -- 1 Introduction -- 2 Intersectional Gender Research, Feminist Theory, and Digital Technology -- 2.1 Intersectional Gender Research -- 2.2 Feminist Theory and Epistemologies -- 2.3 How Gender and Technology Interact -- 3 Conclusions -- References -- No Digital Citizens Without Digital Humanism -- 1 Introduction -- 2 The Challenge: Cognitive Machines -- 3 The Social Impact of Digital Technology -- 4 An Example: The European Approach to Digital Education -- 5 Priorities in Education -- 6 Conclusions -- References -- Digital Transformation, Digital Humanism: What Needs to Be Done -- 1 Introduction -- 2 Some Notes on Informatics -- 3 The Web, Its Impact, and Transformation -- 4 ``The System Is Failing�� -- 5 Digital Humanism and the Vienna Manifesto -- 6 The Digital Humanism Initiative -- 7 Research and Innovation Roadmap -- 8 Conclusions -- References -- Part II: Digital Humanism: A System�s View -- A Short Introduction to Artificial Intelligence: Methods, Success Stories, and Current Limitations -- 1 Introduction -- 2 Methods of AI -- 2.1 Symbolic AI -- 2.2 Machine Learning -- 2.3 Combination of Methods -- 3 Reflections -- 3.1 AI4Good -- 3.2 Is ChatGPT a Tipping Point? -- 3.3 Pressing Issues -- 4 Conclusions -- References -- Trustworthy Artificial Intelligence: Comprehensible, Transparent and Correctable -- 1 Introduction -- 2 Problems with Data-Intensive Machine Learning: Unfairness, Biases and Missing Robustness. 3 Explainable Artificial Intelligence: Comprehensibility of Machine-Learned Models -- 4 Third-Wave AI Methods: Hybrid, Comprehensible and Correctable -- 5 Conclusions -- References -- Are We in Control? -- 1 Introduction -- 2 Fear -- 3 Pushback -- 4 Information Flood -- 5 Digital Creationism -- 6 Coevolution -- 7 Regulation -- 8 Feedback -- 9 Actions -- 10 Conclusions -- References -- AI @ Work: Human Empowerment or Disempowerment? -- 1 Introduction -- 2 Algorithmic Decision Systems -- 3 How ADS Impact Decision Outcomes -- 4 How ADSs Change Work -- 4.1 Assignment of Tasks to Roles -- 4.2 Self-Assessment, Self-Efficacy, and Human Competences -- 4.3 Human Oversight and Accountability -- 5 Conclusions -- References -- The Re-enchanted Universe of AI: The Place for Human Agency -- 1 Introduction -- 2 Questioning Our Assumptions: What ChatGPT Is and What It Does -- 3 Technologies as Agents of Change: The Externalization of Knowledge Operations -- 4 They Are Like Us: The Re-enchanted Universe of AI -- 5 Redefining Human Agency -- 6 Conclusions -- References -- Aesthetic Aspects of Digital Humanism: An Aesthetic-Philosophical Analysis of Whether AI Can Create Art -- 1 Introduction -- 2 Aesthetics Is the Study of the Subject of Art, and Kant Is One of Its Most Influential Representatives -- 3 According to the KAA, There Is No Art Without (Artistic) Freedom -- 4 What Is the State of the Art in Art-Making AI? -- 5 Can AI Create Art from an Aesthetic-Philosophical Standpoint? -- 6 Conclusions -- References -- Approaches to Ethical AI -- 1 Introduction -- 2 Ethical AI -- 2.1 Can AI Be Ethical? -- 3 Approaches to Ethical AI -- 3.1 Ethical AI Frameworks -- 3.2 Philosophical Principlism -- 3.3 Challenges and Limitations of Ethical Frameworks -- 4 From Principles to Practice -- 4.1 Further Research Directions -- 5 Conclusions -- References. Artificial Intelligence and Large-Scale Threats to Humanity -- 1 Introduction -- 2 AI and the Climate Crisis -- 3 AI and Nuclear Deterrence -- 4 Militarization of AI and Nuclear Defense Modernization -- 5 Responsibilities of AI Stakeholders and Large-Scale Threats to Humanity -- 6 Conclusions -- References -- Promises and Perils in Moralizing Technologies -- 1 Introduction -- 2 Conceptual Framework -- 3 Moralizing Technologies -- 4 Exploring the Promises and Perils of Moralizing Technologies -- 5 Conclusions -- References -- The Road Less Taken: Pathways to Ethical and Responsible Technologies -- 1 Introduction -- 2 Human-Adjacent Computing -- 3 Human-Aware Computing -- 4 Human-Centered Computing -- 4.1 Thinking About Technology and People -- 4.2 Development Objectives -- 4.3 Participants -- 4.4 Ethical and Responsible Computing and the Socio-technical System -- 4.5 From Technology Development to Sociotechnical System Orchestration -- 5 Conclusions -- References -- Bridging the Digital Divide -- 1 Introduction -- 2 Short History of the Efforts to Bridge the Digital Divide -- 3 The Digital Divide Through a Decolonial Lens -- 4 Requirements for a Human-Centered Approach -- 5 Combining Action Research, Design Science, and Ethics Perspective -- 6 Tiballi: A Case Study of AI and Data Science for Farmers in Ghana -- 7 Discussion on Critical and Societal Issues -- 8 Conclusions -- References -- Responsible Software Engineering: Requirements and Goals -- 1 Introduction -- 2 Requirements Engineering (RE) -- 2.1 Introduction to RE -- 2.2 Requirements and Goals -- 2.3 The Need for Human-Centered Values -- 3 Values We Live By: Eliciting, Articulating, and Organizing Goals -- 3.1 Values and RE Activities -- 3.2 Values and Goals -- 4 Toward Responsible Software Engineering: DigHum Goals in the Life Cycle -- 4.1 Requirements and Other Activities. 4.2 Software Processes -- 4.3 Validation and Verification -- 4.4 The Running System -- 5 Conclusions -- References -- Governance for Digital Humanism: The Role of Regulation, Standardization, and Certification -- 1 Introduction -- 2 Background to AI Principles, Regulation, and Standards -- 2.1 The Principles -- 2.2 The Role of Regulation -- 2.3 The Standards -- 2.4 The Role of Standards and Certification -- 2.5 What Is AI (and Data) Governance and Why Is It Necessary? -- 2.6 Key Areas for Any Responsible AI Governance Operating Model -- 2.7 Accountability -- 2.8 Algorithmic Bias -- 2.9 Transparency -- 2.10 Ethical Privacy -- 3 Application of the Principles and the Governance Operational Model -- 4 Use Case: Wiener Stadtwerke (The IEEE CertifAIEd Framework for AI Ethics Applied to the City of Vienna, 2021) -- 5 Assessment of Wiener Stadtwerke�s Email Classification System -- 6 Conclusions -- References -- Value-Sensitive Software Design: Ethical Deliberation in Agile Development Processes -- 1 Introduction -- 2 Codes of Conduct and Software Development -- 3 Ethical Deliberation -- 4 Individual Responsibility of the Software Engineer -- 5 Agile Software Development -- 6 Ethical Deliberation in Agile Processes -- 7 Example -- 7.1 Ethical Deliberation: Disclosive Contemplation -- 7.2 Ethical Deliberation: Weighing Contemplation and Sprint Planning -- 7.3 Ethical Deliberation: Applicative Contemplation to the Increment -- 7.4 Ethical Deliberation: Sprint Review and Sprint Retrospective -- 8 Conclusions -- References -- Humans in the Loop: People at the Heart of Systems Development -- 1 Introduction -- 2 People as Creators of Software Systems -- 2.1 Specialists such as Software Engineers -- 2.2 Non-specialists such as Domain Experts -- 3 People as Users of Software Systems -- 3.1 Taking Account of Users and What They Do. 3.2 Software Use Influences Future Development.
9783031453045
Electronic books.
QA76.9.C66
801/.95