Who's Missing?
An AI works great for some people — and gets things wrong for others. The reason hides in who was in its data. Crack four locks to find out who's missing.
The premise
AI learns from examples. When some groups or voices are left out of those examples, the AI knows them less well — so its answers can be wrong or unfair for them. Read the clues, then open all four locks. Each lock reveals the reasoning behind the answer.
How this breakout builds CLEAR thinking
Every Critical Thinking Online Breakout runs on the CLEAR process — Claim, Lens, Evidence, Alternatives, Response (full framework). Here is where students practice each step in this activity:
- Claim — for each lock, decide what answer it is really asking for, and make it specific.
- Lens — notice what you already assume before you choose.
- Evidence — weigh the six clues; “Talent Show” is true but off-topic, so it is not evidence for any lock.
- Alternatives — the multiple-choice and multi-select locks force a comparison of competing options.
- Response — the reason revealed after each lock models the justified answer to act on.
Standards alignment
Aligned to Texas TEKS Technology Applications, Grade 7, §126.18 — the AI-adjacent strands (Computational Thinking; Creativity & Innovation; Data Literacy; and Practical Technology Concepts), subsections (c)(6). Skills are paraphrased; read the official standard at tea.texas.gov. This page shows the reasoning focus of each lock — not the answers.
| Lock | Reasoning focus | TEKS substrand |
|---|---|---|
| Lock 1 Why It Fails Some People |
Why It Fails Some People | (c)(6) Data Literacy — Analyze Data |
| Lock 2 Spot the Gaps |
Spot the Gaps | (c)(6) Data Literacy — Analyze Data |
| Lock 3 Name the Fix |
Name the Fix | (c)(6) Data Literacy — Analyze Data |
| Lock 4 Check It for Fairness |
Check It for Fairness | (c)(6) Data Literacy — Analyze Data |
In the classroom
- Warm up (5 min). Ask: “Be a Representation Detective” — what does this mean when working with AI? Surface prior experience before the activity.
- Model one clue. Open a single clue together and think aloud: what does this tell us, and which lock might it help?
- Reason, don’t guess. Require students to say why before checking a lock. After each solve, read the revealed reason and compare it to their thinking.
- Spot the decoy. One clue is true but useless. Debrief which one and how they knew — a core evaluation skill that mirrors judging an AI’s output.
- Language support. The 🌐 picker offers 7 languages; pair newcomers to discuss clues in their home language, then answer.
- Extend. Have students find (or safely describe) a real example of the focus skill — a biased result, a hallucination, a good prompt — without using any real product’s screenshots.