Overview
What this challenge is about.
Compute viewpoint-diversity metrics from recommendation logs, identify filter bubble risks, and propose three changes. Get a verifiable certificate.
The Brief
What you'll do, and what you'll demonstrate.
Quantify recommender-driven viewpoint narrowing on a civic platform and recommend three product changes with expected impact.
Earning criteria — what you'll demonstrate
- Design diversity metrics for recommender outputs
- Run a cohort-based exposure audit on impression logs
- Translate audit findings into concrete product-design changes
- Communicate audit results to non-technical board members
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
Career paths this builds toward
Canonical rolesAI Safety Researcher
Designing and running a recommender-bias audit with a board-ready output is the entry point for AI safety researchers on trust-and-safety teams.
This challenge sharpens
- audit-methodology
- diversity-metrics
- recommender-evaluation
Data Scientist
Cohort-based exposure analysis with stakeholder storytelling is the data-scientist craft applied to a high-stakes policy question.
This challenge sharpens
- recommender-evaluation
- data-storytelling
- social-media-analytics
AI Product Manager
Turning audit findings into three product changes with expected impact is core AI PM work on consumer platforms under regulatory pressure.
This challenge sharpens
- recommender-evaluation
- diversity-metrics
- data-storytelling