Data-Driven DEI and AI Ethics

This unit explores how businesses measure, evaluate, and run diversity, equity, inclusion (DEI) and employee well-being initiatives using program evaluation principles, clear metrics, and case-study analysis. It also examines the opportunities and risks introduced by AI — including bias and deepfakes — and prepares learners to design mitigation and governance strategies before implementing DEI programs in subsequent units.

Learning Objectives

• Analyze DEI and employee well-being data to distinguish correlation from causation and to formulate focused business questions that guide proactive data collection
• Apply program evaluation fundamentals to design measurable DEI and well-being initiatives, including selecting appropriate metrics, KPIs, and data collection methods
• Evaluate real-world case studies and the role of employee resource groups (ERGs) to recommend program improvements that align DEI and well-being efforts with business goals
• Analyze the potential benefits, biases, and misuse risks of AI (including deepfakes) for DEI and employee well-being, and develop practical mitigation, governance, and ethical oversight strategies