MODULE 1 · AGES 12–17 · ABOUT 3–3.5 HOURS WHEN COMPLETE
AI Literacy & Technical Fundamentals
Why does your feed show you that video? What does an AI actually learn from? When does a clever trick become manipulation? This module answers those questions by making you do the thing — rank a feed, set the weights, build the ranker.
By the end of this module, you can:
- Explain in your own words that a feed is a ranking problem, not a search.
- Read a scoring formula and predict how changing a weight changes what shows up first.
- Explain the difference between on-device and server models, and what context signals are.
- Spot a retention mechanic and name where it crosses from helpful to manipulative.
- Build and test a tiny ranker on real-ish data.
Lessons
Lesson 1: How Ranking Works — live now, about 40–45 minutes. Start Lesson 1 →
Lesson 2: On-Device vs Server Models — coming soon
Lesson 3: Context Signals & Privacy — coming soon
Lesson 4: Retention Mechanics & the Ethical Line — coming soon
Lesson 5: Build a Tiny Ranker — coming soon
Key terms
- Candidate
- One thing the feed is considering showing you.
- Ranking
- Putting candidates in order by score, best first.
- Score
- One number per candidate, built from predicted actions and weights.
- Probability
- How likely something is — 0 (never) to 1 (always).
- Weight
- How much one predicted action counts in the score. The product decision.
- Model
- A trained system that makes predictions from patterns in data.
- On-device
- Computed on your phone, not on a server.
- Server
- A faraway computer that does the heavy work and sends results back.
- Context signal
- Something about the moment — time, battery, mute — that can shift a score.
- Retention
- Keeping you watching, or bringing you back.