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$20

AI Ethics & Bias in Practice

Learn what fair and responsible AI means in everyday work, then test it yourself. You will take an AI tool that screens job applicants, measure whether it treats groups differently, find where the unfairness comes from, fix it, and see what the fix costs. You finish with a short ethics review your team can use on any new AI tool. All practice data is made up. Educational, not legal advice.

"We checked our AI screen for unfair results, we know why it happened, we fixed it, and we can explain the trade-off to anyone who asks"

6 Interactive Sessions

Short, interactive sessions — watch it work, steer it, then build it yourself. Go deeper anytime with the full written chapters.

  1. 1

    What fairness means at work

    An AI tool at work can harm people in four main ways. Before you test a tool, you list who it touches and how it could hurt them.

  2. 2

    Where bias comes from

    Bias in an AI tool usually comes from one of three places: the data it learned from, the labels it was taught to copy, or a stand-in field that tracks a group. You test each one against the data.

  3. 3

    Measure it: selection rate and error rate

    Two numbers per group tell you most of what you need: the selection rate (who gets picked) and the error rate (good people the tool turned away). One overall average can hide both.

  4. 4

    Fix it, and see what the fix costs

    There are two kinds of fix: remove the cause, or adjust the result. You compare them before and after on the same numbers, including what each one costs, and then choose.

  5. 5

    Tell people, and let them challenge it

    People should know when AI is used on them, and have a simple way to ask a person to look again. You write the notice and set up the review route.

  6. 6

    An ethics review for your team

    Everything in this course fits on one page: eight questions to ask before an AI tool goes live, and a decision at the end. You fill it in for the Larkmoor screen, then for one real AI use at your company.

Skills you'll practise

Harm MappingBias SourcesSelection & Error RatesFix Trade-offsNotice & Human ReviewEthics Review

Practice data included

  • 2,000 made-up job applicants with AI screen scores
  • Customer-chat transcripts from an AI assistant
  • 8 short workplace scenarios

What you walk away with

Shareable portfolio

A public URL showing your module timeline, patterns mastered, and completion status.

Everything you build

Download all your work as a ZIP file. It is yours to keep.

Module walkthrough

Each module documented with deliverables and the production pattern you implemented.

Ready to start AI Ethics & Bias in Practice?

First course free. $20 per course after that.