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quiz vs the machine

Gold1420

Machine Learning

Equal Opportunity

A relaxed fairness rule focused on the qualified being treated equally.

4 min read · core · beat Gold to climb

One rate to equalize

Equal opportunity is a relaxation of equalized odds. It requires only that the true positive rate be equal across groups. Among people who genuinely deserve the positive outcome, every group should be approved at the same rate. It says nothing directly about false positives.

Why focus on true positives

In many settings the most important harm is missing a qualified person, such as a deserving loan applicant or a sick patient who needs treatment. Equal opportunity targets exactly that error, asking that no group is disproportionately overlooked when it qualifies.

Tradeoffs

  • Looser than equalized odds, so it is easier to satisfy and costs less accuracy.
  • It does not control false positives, so groups can still differ in how often unqualified members are wrongly approved.

When to use it

Choose equal opportunity when the cost of a false negative dominates and you care most that qualified members of every group get their fair chance.

Key idea

Equal opportunity relaxes equalized odds to require only equal true positive rates, ensuring qualified members of every group are approved at the same rate when false negatives are the dominant harm.

Check yourself

Answer to earn rating on the learn ladder.

1. What does equal opportunity require to be equal across groups?

2. When is equal opportunity most appropriate?