Deploying Responsible Customer AI

This capstone unit prepares students to deploy, govern, and monitor customer-facing AI systems with attention to ethics, privacy, bias mitigation, explainability, security, and organizational culture. Using real-world case studies and IRL scenarios, students integrate technical, legal, and business considerations to produce accountable, transparent, and trust-preserving deployments.

Learning Objectives

• Analyze technical, ethical, privacy, and security risks in a customer-facing AI solution and produce a deployment plan that includes monitoring, accountability, and incident response measures
• Apply privacy-by-design and bias-mitigation techniques (e.g., consent frameworks, de-identification, audits, model explainability methods) to modify a customer AI workflow and document measurable protections
• Demonstrate the ability to communicate trade-offs among profits, brand, and trust by creating an executive governance proposal that persuades stakeholders and secures approval for a deployed AI product
• Evaluate human–machine collaboration models and recommend policies and metrics that promote transparency, continuous improvement, and a data-driven culture post-deployment