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Full Description
The Anticipatory Design Playbook is a practical and thought-provoking guide to crafting anticipatory experiences in an age defined by artificial intelligence (AI). Grounded in years of PhD research and real-world design leadership, Joana Cerejo offers a comprehensive framework for designing AI-driven systems that align with user intent, respond to evolving behaviors, and remain transparent, adaptive, and human-centered.
Unlike most resources focused solely on the technical side of AI, this book bridges design, behavioral science, and machine learning to equip designers, product leaders, and technologists with the tools to shape intelligent systems (before those systems negatively shape us). From foundational concepts in AI, machine learning, and data science to behavioral theory, ethical design, and foresight methods, Cerejo introduces a new design language for systems that think ahead.
Readers will learn to identify key AI patterns, interpret mental models, and strike a balance between autonomy and automation across predictive, conversational, and agentic systems. The book introduces a structured process—anticipate, imagine, shape—that translates complex concepts into actionable UX strategies. Whether you're designing AI assistants, hyperpersonalized services, or adaptive platforms, this playbook offers practical methods for designing systems that anticipate needs, reduce friction, and support long-term behavior change.
More than a framework, The Anticipatory Design Playbook urges us to reclaim our role in shaping the future of intelligent systems. It is a call to leave behind the illusion of certainty that forecasting provides. It invites us to design with foresight—to create systems that are not just efficient, but context-aware, participatory, and resilient to change.
Contents
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
