Module 4: Transparency, explainability, and accountability

Theme

Transparency, explainability, and accountability

Essential Question

Who needs to understand what, and when?

Module Components

• Book prose: conceptual framing, domain scenario, methods, and failure modes

• Assignment: evidence-backed production of a specific artifact

• Slides: presentation sequence for seminar or lecture delivery

• Narration: spoken version of the slide flow

• Rubric: criteria for evaluating the module artifact

• Notebook: executable lab aligned with the module theme using synthetic governance case facts including affected groups, data rights, transparency controls, and harm scenarios

Module Artifact

responsible AI review memo with risk register, policy analysis, and redress plan focused on transparency, explainability, and accountability: Map accountability across users, vendors, and operators.

Professional Setting

Students work as if advising an AI governance board reviewing a proposed high-impact AI deployment. Their work must be intelligible to governance chair, legal counsel, affected-user advocate, product owner, and compliance officer.

Use This Module in Order

1. Read the learning chapter.

2. Review the slide deck with the matching narration.

3. In Populi, open the private student-repository link for this course and enter modules/module-4.

4. Clone the repository once or open its Codespace/Colab copy; run lab.ipynb and complete exercise.ipynb there.

5. Self-check with the rubric, commit and push the work, then submit exactly what Populi requests.