AI Applications in Advanced Contexts

This unit focuses on applying AI to complex domains—space exploration, medical systems, and sensor-driven automation—emphasizing hardware constraints, sensor integration, telepresence, generative AI, security, and commercialization. Students synthesize prior foundational skills to design, test, and critique practical AI solutions and to prepare for further study or industry capstone projects.

Learning Objectives

• Analyze trade-offs and limitations in data acquisition, sensors, and hardware for AI systems by identifying at least three constraints and proposing measurable mitigation strategies from provided case studies
• Apply system-integration principles to design an AI-enabled solution that combines sensors, telepresence, automation, and robotics for a specified space or medical scenario, producing a block diagram and an implementation plan that meets given performance and safety constraints
• Demonstrate methods to detect, explain, and mitigate AI-based errors, uncertainties, and data security vulnerabilities by developing and testing a mitigation plan that includes at least three technical or procedural controls
• Evaluate the ethical, commercial, and workforce impacts of deploying generative AI and automation in medical and space industries and produce a stakeholder-focused recommendation brief addressing regulatory, privacy, and professional-disruption concerns