This capstone unit synthesizes technical, operational, and social considerations for deploying AI systems in real-world contexts. Students examine a healthcare case study, assess resource and data constraints, and explore workforce roles and societal change to prepare actionable deployment plans and ethical risk communications.
Learning Objectives
- Analyze the breast cancer case study and other examples to identify deployment constraints, stakeholder needs, and ethical risks
- Evaluate the technical and environmental factors (cost, connectivity, infrastructure) that affect AI system viability and recommend appropriate deployment strategies
- Apply data-quality, annotation, and bias-mitigation practices to refine project scoping and modeling decisions for responsible AI solutions
- Demonstrate understanding of emerging AI roles and societal impacts by producing a stakeholder communication plan and an ethical risk assessment for a proposed AI deployment
Curriculum
- 1 Section
- 15 Lessons
- 30 hours
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- Unit 4 — AI Deployment and Societal Impact15
- 1.1Case Study: Breast Cancer Example20 mins
- 1.2Project Scoping20 mins
- 1.3The Reality of Running AI: Cost, Connectivity, and Context20 mins
- 1.4Understanding the Role of Environmental Context in AI Deployment20 mins
- 1.5Technology Resources20 mins
- 1.6Data: Quantity and Quality, Annotations, Biases20 mins
- 1.7Modeling20 mins
- 1.8Final Thoughts20 mins
- 1.9References20 mins
- 1.10New Technologies20 mins
- 1.11AI Teams in the Near Future20 mins
- 1.12AI-Specific Jobs20 mins
- 1.13Societal Change20 mins
- 1.14Final Thoughts20 mins
- 1.15References20 mins
Instructor
Free
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