Human-Centered AI (HCI & UX)
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Course Modules:
Module 1: Introduction to Human-Centered AI
What is human-centered AI?
The role of HCI and UX in AI systems
Principles of usable, responsible, and explainable AI
Module 2: Understanding User Needs & Mental Models
Conducting user research in AI projects
Designing with empathy and behavioral context
User personas for AI-driven interactions
Module 3: Human-AI Interaction Patterns
Direct interaction vs. ambient intelligence
Human-in-the-loop (HITL) and human-on-the-loop (HOTL)
Interaction flows for voice, chat, and visual AI
Module 4: Designing UX for Intelligent Interfaces
UX patterns for uncertainty, delay, and learning curves
Progressive disclosure of AI functionality
Visualizing AI feedback and confidence levels
Module 5: Explainable AI (XAI) & Transparency
What makes AI explainable to end users?
Tools for interpretability: SHAP, LIME, feature visualizations
Designing model outputs users can understand
Module 6: Ethics, Fairness & Trust in AI Design
Avoiding dark patterns in AI interfaces
Managing consent, privacy, and data transparency
Building user trust through design and communication
Module 7: Evaluation Metrics for HCI & AI UX
Measuring usability, satisfaction, and user trust
Heuristics for intelligent systems
A/B testing and user feedback loops
Module 8: Prototyping Human-Centered AI Products
Tools: Figma, Framer, ProtoPie for AI interfaces
Designing ethical user flows
Prototyping predictive, generative, and adaptive systems
Module 9: Iterative Design & Continuous Improvement
Collecting user feedback for AI improvement
Inclusive design for diverse users and abilities
Keeping humans at the center of algorithm updates
Module 10: Final Capstone Project
Design and prototype a human-centered AI experience:
Examples: Transparent recommender system, ethical chatbot, AI health assistant
Submit design files, user research report, and walkthrough demo
Peer and instructor review
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