The Anticipatory Design Playbook is a practical guide to crafting anticipatory experiences in an age defined by artificial intelligence. Grounded in years of PhD research and real-world design leadership, Joana Cerejo offers a comprehensive framework for designing AI-driven systems.
The Anticipatory Design Playbook is a practical guide to crafting anticipatory experiences in an age defined by artificial intelligence. Grounded in years of PhD research and real-world design leadership, Joana Cerejo offers a comprehensive framework for designing AI-driven systems.
Joana Cerejo, PhD in Digital Media from the University of Porto, with over a decade of experience, is a UX lead and researcher specializing in human-centered AI and anticipatory systems. She was nominated for the 2021 Women in AI Awards by VentureBeat. With a background spanning UX research and strategy, behavioral science, and data-driven design, she helps organizations craft intelligent experiences that prioritize transparency, adaptability, and user autonomy. Since 2012, she has taught at universities and technical schools, mentoring new designers and sharing her knowledge.
Inhaltsangabe
PART I Setting the Stage: Understanding Artificial Intelligence, Data Science, Machine Learning, and Deep Learning: The Layers for Anticipatory Systems Chapter 1: Foundational Concepts of Artificial Intelligence and Machine Learning Chapter 2: Key AI Capabilities and Real-World Use Cases Chapter 3: Seven Fundamental AI Patterns Chapter 4: ML for Designers: Learning Phases, Key Concepts, and Models PART II Designing Relief: Addressing the Cognitive Burden of Technology Through Anticipatory Systems Chapter 5: The Paradox of Choice in the Digital Era Chapter 6: Origins of Anticipatory Design Chapter 7: The Fragile Promise of Anticipatory Experiences Chapter 8: Trust Calibration: Balancing Autonomy and Automation Chapter 9: The Science of Behavior Change PART III Anticipatory Design in Action: Approaches, Frameworks, and Practical Examples Chapter 10: From Theory to Method: Interpreting Anticipatory Design Chapter 11: Anticipatory Design: Designing for What Comes Next Chapter 12: Making Sense of AI: Users' Mental Models and Trust Gaps Chapter 13: Designing Anticipatory Systems: A Layered and Temporal Approach Chapter 14: Designing With Foresight: Future Studies in Anticipatory Design Part IV Designing Anticipatory Systems Chapter 15: How Foresight Integrates With Traditional UX Workflows? Chapter 16: Designing Anticipatory Experiences Chapter 17: Design Heuristics for Anticipatory Systems: Turning Principles into Practice
PART I Setting the Stage: Understanding Artificial Intelligence, Data Science, Machine Learning, and Deep Learning: The Layers for Anticipatory Systems Chapter 1: Foundational Concepts of Artificial Intelligence and Machine Learning Chapter 2: Key AI Capabilities and Real-World Use Cases Chapter 3: Seven Fundamental AI Patterns Chapter 4: ML for Designers: Learning Phases, Key Concepts, and Models PART II Designing Relief: Addressing the Cognitive Burden of Technology Through Anticipatory Systems Chapter 5: The Paradox of Choice in the Digital Era Chapter 6: Origins of Anticipatory Design Chapter 7: The Fragile Promise of Anticipatory Experiences Chapter 8: Trust Calibration: Balancing Autonomy and Automation Chapter 9: The Science of Behavior Change PART III Anticipatory Design in Action: Approaches, Frameworks, and Practical Examples Chapter 10: From Theory to Method: Interpreting Anticipatory Design Chapter 11: Anticipatory Design: Designing for What Comes Next Chapter 12: Making Sense of AI: Users' Mental Models and Trust Gaps Chapter 13: Designing Anticipatory Systems: A Layered and Temporal Approach Chapter 14: Designing With Foresight: Future Studies in Anticipatory Design Part IV Designing Anticipatory Systems Chapter 15: How Foresight Integrates With Traditional UX Workflows? Chapter 16: Designing Anticipatory Experiences Chapter 17: Design Heuristics for Anticipatory Systems: Turning Principles into Practice
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