Foundations of AI-Driven Spatial Computing

This unit introduces the historical, technological, and business contexts for AI-driven spatial computing, tracing media and UX revolutions from photography and cinema through VR/AR to today. Students will explore core technologies, real-world use cases and beneficiaries, and assess leadership, strategic planning, and risk considerations to prepare for applied work in subsequent units.

Learning Objectives

• Analyze the historical progression of visual and interactive media (photography, film, television, VR/AR) and synthesize how these transitions set the stage for modern spatial computing by creating a timeline and brief analysis
• Demonstrate understanding of spatial computing by identifying and describing major components and related technologies (AI, computer vision, sensors, AR/VR, cloud/edge compute) and explaining how they interrelate
• Evaluate real-world use cases and stakeholders by assessing at least three industry examples to determine primary beneficiaries, business value propositions, and measurable outcomes
• Apply risk assessment and strategic planning principles to develop an executive-level recommendation that addresses leadership imperatives, ethical/privacy concerns, and initial integration steps for an organization considering spatial computing adoption