AI Deployment and Societal Impacts

This capstone unit focuses on translating AI prototypes into real-world, socially beneficial systems by addressing project scoping, operational realities, data and modeling quality, and workforce implications. Students will synthesize case studies, resource constraints, team structures, and societal impacts to produce actionable deployment plans and risk-mitigation strategies.

Learning Objectives

• Analyze a case study (e.g., breast cancer) to identify how environmental context, connectivity, cost, and stakeholder needs influence AI effectiveness and ethical outcomes
• Apply project-scoping methods to produce a deployment plan that estimates technical resources, data requirements, annotation needs, budgetary constraints, and timelines
• Evaluate datasets and models for quantity, quality, annotation completeness, and bias, and recommend concrete mitigation strategies to improve fairness and reliability
• Demonstrate understanding of AI workforce and governance by outlining team roles, emerging AI-specific jobs, and societal implications to support responsible adoption