AI Integration for Spatial Experiences

This unit explores how AI (including ML/DL, CV, and GenAI) is integrated into spatial computing to create immersive, measurable, and maintainable experiences. Students will examine implementation strategies, sensory and UX design, monitoring and optimization, and the ethical and regulatory considerations necessary to deploy responsible spatial AI systems, building on prior foundations and preparing for a culminating project.

Learning Objectives

• Analyze how AI modalities (ML/DL, computer vision, and generative models) function as a virtualization layer within spatial computing and compare transformative applications across industries.
• Apply implementation and sensory-design strategies to produce a high-level integration plan or prototype specification that addresses UX/CX/EX goals, connectivity, and collaboration requirements for a spatial computing scenario.
• Evaluate ethical, compliance, and regulatory risks associated with spatial AI deployments and propose concrete mitigation, governance, and accountability measures.
• Demonstrate methods for monitoring and optimizing spatial AI systems by defining success metrics, testing protocols, and iterative improvement workflows that support maintenance and scalability.