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Week 24 · Term Three · How machines learn, and how they fail

The Machine That Learned Wrong

Catch a machine that learned the snow instead of the wolf, see how a 99% score can find nothing, read the study that split face-scanner errors by group, write a fair rule for an AI essay detector, and file a model card that tells the truth.

A machine learns exactly what its examples teach.

Monday finds a shortcut hiding behind a high score. Tuesday shows why accuracy can mislead when the thing you care about is rare. Wednesday compares error rates by group from a real 2018 audit. Thursday decides how a school should use an AI-writing detector. Friday writes the label every machine should carry.

Day 1

Monday

25 minutes

AI · A machine learns whatever pattern its examples hold

Catch the Snow Shortcut

Explain that a machine learns from patterns in its training examples, including accidental ones, and calculate how a shortcut rule can still score well.

Make

A shortcut report

Audit handoff: The shortcut report is filed. Tomorrow a machine scores 99% and still misses everything that matters.

Day 2

Tuesday

25 minutes

Statistics · Accuracy can hide the thing you care about

The 99% Bird Spotter

Calculate accuracy as a percent, and explain why a high accuracy can hide a machine that misses every rare case.

Make

An accuracy check

Audit handoff: The accuracy check is filed. Tomorrow, one real audit split the score by group and found a gap of more than 40 times.

Day 3

Wednesday

25 minutes

Ethics · Test the machine for every group

Split the Score by Group

Explain how a single overall score can hide unfair errors for one group, compare error rates by group, and list the steps of a fair test.

Make

A group audit

Audit handoff: The group audit is filed. Tomorrow a machine is used to judge students' writing.

Day 4

Thursday

25 minutes

Ethics · A flag is a question, not a verdict

The Essay Detector

Weigh the tradeoffs of using an AI tool to make decisions about people, and decide where a human must check before anyone is affected.

Make

A detector policy

Audit handoff: The detector policy is filed. Tomorrow you write the label every machine should carry.

Day 5

Friday

30 minutes

Writing · The label every machine should carry

Write the Model Card

Write a clear informative report about an AI tool: its purpose, its training data, its errors by group, its limits, and who checks it.

Make

A model card

Audit handoff: The model card is filed. Your week's report is ready for the portfolio.

Open the audit journal.

The audit uses only work entered here. It is a family record of this week’s work, not a grade, an attendance record, or proof of mastery.

Quest progressProgress recorded