Ai-Powered Interaction Design Patterns

Case studies, challenges and best practices

What you'll learn

Describe key AI-powered interaction patterns like adaptive interaction, feedback loops, and human-in-the-loop systems.

Identify examples and applications of AI-powered design patterns.

Use design patterns to create personalized, engaging, and trustworthy AI solutions.

Describe challenges and best practices of designing and implementing various AI-powered design patterns.

Requirements

Previous experience in product development, UX (User Experience) design, HCI (Human-Computer Interaction), or data-driven projects can enhance your engagement in this course. However, if you do not have this experience, curiosity about how AI shapes modern products and a willingness to explore ethical and technical challenges are sufficient.

Description

AI is transforming user experiences by making digital interactions smarter, adaptive, and more intuitive. This course explores AI-powered design patterns—structured approaches that leverage AI to create engaging, efficient, and human-centered digital experiences.By understanding and applying these patterns, learners will be able to:Describe key AI-powered interaction patterns like adaptive interaction, feedback loops, and human-in-the-loop systems.Identify examples and applications of AI-powered design patterns.Use design patterns to create personalized, engaging, and trustworthy AI solutions.Describe challenges and best practices of designing and implementing various AI-powered design patterns.What You Will Learn:AI-Driven Adaptive Patterns – How AI adjusts experiences dynamically based on user behavior.Conversational AI Patterns – Designing intuitive AI-powered chatbots and voice assistants.Natural User Interaction - How AI help design interactions based on human behaviors. Human-AI Collaboration – How users and AI co-create, guide, or enhance digital interactions.Gamification & Engagement – AI-powered rewards, challenges, and social interaction strategies.Feedback & Learning Loops – Using AI to refine and optimize interactions through continuous feedback.Who Should Take This Course?Designers (UX/UI, Interaction) – Enhance digital products with AI-driven interactions.Developers – Implement AI-powered patterns in software and applications.Product Managers – Understand AI’s impact on user engagement and strategy.Researchers & Educators – Explore cutting-edge AI interaction design methodologies.By the end of this course, you’ll have a deep understanding of AI-powered interaction design patterns and be able to apply them in real-world applications across various industries.

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Target Audience

Lecture 3 Disclosures

Section 2: Design Patterns

Lecture 4 Learning Objectives

Lecture 5 Introduction to Design Patterns

Lecture 6 History of Design Patterns

Lecture 7 AI-Powered Design Patterns

Section 3: Adaptive Patterns

Lecture 8 Learning Objectives and Introduction

Lecture 9 Dynamic Personalization

Lecture 10 Predictive Assistance

Lecture 11 Context-Aware Interfaces

Lecture 12 Conclusion

Section 4: Conversational Patterns

Lecture 13 Learning Objectives

Lecture 14 Introduction

Lecture 15 Single-Turn Conversational Patterns

Lecture 16 Multi-Turn Conversational Patterns

Lecture 17 Variations in Conversational Patterns

Lecture 18 Conclusion

Section 5: Feedback and Learning Patterns

Lecture 19 Learning Objectives

Lecture 20 Introduction

Lecture 21 Continuous Feedback Loops

Lecture 22 Adaptive Learning Patterns

Lecture 23 Corrective Feedback and Error Recovery Pattern

Lecture 24 Anomaly Detection Feedback Pattern

Lecture 25 Conclusion

Section 6: Natural Interaction Patterns

Lecture 26 Learning Objectives

Lecture 27 Introduction

Lecture 28 Voice Interaction

Lecture 29 Gesture Recognition

Lecture 30 Emotion Recognition

Lecture 31 Touch and Haptic Feedback

Lecture 32 Eye-Tracking & Gaze Prediction

Lecture 33 Conclusion

Section 7: Human-AI Collaboration Patterns

Lecture 34 Learning Objectives

Lecture 35 Introduction

Lecture 36 Human-Guided AI

Lecture 37 Human-AI Collaboration Loop

Lecture 38 Human-AI Co-creation

Lecture 39 AI Guides Human

Lecture 40 AI Takes Initiative, Human Approves

Lecture 41 Conclusion

Section 8: Gamification and Engagement Patterns

Lecture 42 Learning Objectives

Lecture 43 Introduction

Lecture 44 AI-Enhanced Challenges

Lecture 45 Dynamic Rewards

Lecture 46 Habit Formation and Streak Mechanisms

Lecture 47 Social and Competitive Engagement

Section 9: Conclusion

Lecture 48 Conclusion

designers (UI/UX, product, interaction), developers, product managers, researchers and educators.