Overview
What this challenge is about.
Pick one public AI incident (suggestions: a chatbot's harmful response that went viral, a facial-recognition false-arrest case, a financial-model bias scandal). Produce a 6-page structured case study covering: timeline, contributing factors (technical + organizational + regulatory), counterfactual analysis (what evaluation, governance, or design choice would have caught it), and 3 transferable lessons. Lead a 45-min seminar discussion with prepared discussion questions.
The Brief
What you'll do, and what you'll demonstrate.
Produce a structured case study of a public AI incident that surfaces transferable lessons for a safety-focused lab.
Earning criteria — what you'll demonstrate
- Apply structured incident-analysis methodology to a real public case
- Reason about technical, organizational, and regulatory contributing factors
- Construct counterfactual analyses without 20/20 hindsight
- Facilitate a small-group seminar discussion
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.
AI Safety Researcher
Structured incident analysis is a core AI-safety-research skill — labs hire on the ability to produce these.
This challenge sharpens
- incident-analysis
- counterfactual-reasoning
- responsible-ai
AI Product Manager
Translating public incidents into transferable product-process lessons is the responsible-AI muscle senior AI PMs build over time.
This challenge sharpens
- incident-analysis
- responsible-ai
- case-study-research
Research Scientist
Primary-source-driven analysis with explicit counterfactual reasoning is the research-scientist's methodology applied to safety questions.
This challenge sharpens
- case-study-research
- counterfactual-reasoning
- ethics-analysis