Autonomous transformation creating a more human future in the era of artificial intelligence

From technologist and strategist Brian Evergreen, a bold new agenda for the role of organizational leaders in creating a more human future with technology Social good initiatives are incompatible with the current network of systems that make up and support the private and public sectors. Millions of...

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Detalles Bibliográficos
Otros Autores: Evergreen, Brian, author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Hoboken, New Jersey : John Wiley & Sons, Inc [2023]
Edición:First edition
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009757915606719
Tabla de Contenidos:
  • Intro
  • Title Page
  • Copyright Page
  • Contents
  • Introduction: We Can Create a More Human Future
  • What Is a More Human Future?
  • How Do We Create This More Human Future?
  • What Is Profitable Good?
  • 1. Talent Preferences
  • 2. Market Preference (e.g., doing good has become an economic force)
  • 3. Strategic Partner Preference
  • Greed, Profit, and Altruism
  • What About Social Purpose Corporations?
  • Profitable Good in the Real World
  • Notes
  • Part One The Fundamentals
  • Chapter 1 Reformation, Transformation, and Creation: Defining Autonomous Transformation
  • Weaving Our Way to the Moon
  • Job Protectionism, Job Fatalism, and Job Pragmatism
  • Preservation of Human Work for Human Experiences
  • Creating a More Human Future Through Creation, Reformation, and Transformation
  • Survivalism and Digital Darwinism
  • Notes
  • Chapter 2 What Does It Mean to Be Human in the Era of Artificial Intelligence?
  • The Pain of Uncertainty
  • Capability
  • Consciousness
  • Notes
  • Part Two The Art of the Impossible
  • Chapter 3 Our Inheritance
  • Our Inheritance from the Industrial Revolution
  • Taylorism, or Scientific Management
  • Data Science Taylorism*
  • Notes
  • Chapter 4 Maintenance Mode
  • Centuries-Old Systems
  • Maintenance Mode as a Means of Sustaining Scaffolded Systems
  • Maintenance Mode and Advanced Technologies
  • Is Technology the Problem or the Solution?
  • The Coexistence of Maintenance and Creation
  • A Note for Individual Contributors
  • Note
  • Part Three Envision Your Future
  • Chapter 5 Requiem for the Industrial Revolution: Rehumanizing Work
  • Note
  • Chapter 6 The Problem with Solving Problems: Introducing Future Solving
  • Problem Solving versus Future Solving
  • The Use Case Problem
  • The Second Use Case Problem: Use Case Battleship
  • Doing the Wrong Thing Right
  • Notes.
  • Chapter 7 Developing the Skill of Envisioning
  • Functional Reimagining
  • Multiverse Reimagining
  • Part Four Discover and Rediscover
  • Chapter 8 Systemic Design and the Lost Art of Synthesis
  • The Interconnectedness of Parts within a System
  • Dimensions of Systems
  • The Lost Art of Synthesis
  • Notes
  • Chapter 9 The Organization as a Chessboard: Seeing the Pieces
  • How to Determine Whether You Are Focused on a Subset of the Whole System
  • A Note for Individual Contributors
  • Notes
  • Chapter 10 The Organization as a System
  • Intraorganizational Systems
  • Interorganizational Systems
  • Industry-Specific Organizational Systems
  • Chapter 11 Broken Systems
  • The Hedberg Strategy
  • A Broken System
  • One Reimagining of Internal Technology Organizations
  • A Second Reimagining of Internal Technology Organizations
  • Part Five Clear the Digital Fog
  • Chapter 12 Chaos, Noise, and Epistemology in the Digital Age
  • Chaos, Noise, and the Three Logical Fallacies
  • Epistemology in the Digital Age
  • Notes
  • Chapter 13 Silicon Valley, Wall Street, and the Factory Floor
  • The Divide Within
  • The Divide Across
  • The View from One Side of the Field
  • The View from the Other Side of the Field
  • The Divide Without
  • Note
  • 14 The Multiplication of Expertise: A Leadership Imperative
  • Three Altitudes of Inputs and Outputs
  • Example A
  • Example B
  • Notes
  • Part Six Design for Inevitability
  • Chapter 15 From Data-Driven to Reason-Driven
  • Aristotle's Conundrum
  • Organizational Empiricism
  • Organizational Reasoning (from Data-Driven to Reason-Driven)
  • Notes
  • Chapter 16 The Reformational Economics of Linear and Exponential Value
  • Linear versus Exponential Value in the Case of Capability
  • Notes
  • Chapter 17 The Reformational Economics of Omission and Commission
  • Outcome Bias in the Face of Failure.
  • Chapter 18 The Ecosystem: Surprising and Remarkable Partnerships
  • Designing for Inevitability: An Ecosystemic Discipline
  • Building an Ecosystem
  • Maintaining versus Sustaining an Ecosystem
  • Surprising and Remarkable Partnerships within an Organization
  • Part Seven Create a More Human Future
  • Chapter 19 Beyond Pilot Purgatory
  • Pilots within Social Systems
  • Riskless Experimentation
  • Piloting the Path to Promotion
  • Human-Centered Transformation
  • Note
  • Chapter 20 Storytelling: Leading Social Systems
  • Storytelling as a Strategic Organizational Imperative
  • Closing the Story Circle
  • Storytelling as an Agent for Change
  • Chapter 21 A More Human Organization
  • Notes
  • Part Eight Autonomous Transformation Technologies
  • Chapter 22 Autonomous Transformation Technologies: A Leader's Guide
  • Autonomous Transformation Example 1: Product Development
  • Autonomous Transformation Example 2: Global Logistics
  • Autonomous Transformation Example 3: Health Care
  • A Note on Blockchain
  • Notes
  • Chapter 23 A Deeper Dive into Artificial Intelligence
  • The Components of Artificial Intelligence
  • Analytics
  • Descriptive Analytics: What does my data tell me has happened/is happening?
  • Diagnostic Analytics: Why does my data say that it happened/is happening?
  • Predictive Analytics: What does my data tell me is likely to happen in the future?
  • Prescriptive Analytics: What do my data and business logic tell me I should do next?
  • Statistics
  • Data Science
  • Decision Science
  • Machine Learning
  • Generative Artificial Intelligence (Generative AI)
  • Reinforcement Learning
  • Autonomous Artificial Intelligence
  • Machine Teaching: A New Paradigm
  • Automation versus Artificial Intelligence
  • Automation versus Autonomy
  • How to Tell When Someone Is Lying about Artificial Intelligence
  • Quiz
  • Notes
  • Conclusion.
  • What Should You Read Next?
  • Acknowledgments
  • Index
  • EULA.