The Fairness Test for AI: Who Wins, Who Loses

Most AI choices have winners and losers. Asking 'who wins, who loses' helps you spot when AI use is unfair — even if you did not mean it to be.

Some examples

• AI homework helper: you win, nobody loses. ✓
• AI to make a deepfake of a classmate: you win, they lose. ✗
• AI for a fundraiser: you win, charity wins. ✓
• AI to fake reviews on a competitor: you win, they lose unfairly. ✗

Try it!

Pick one AI use you are considering. Run the test. Notice if it changes your decision.

When the fairness test gets tricky

Some AI uses feel fair at first but become unfair when you look more carefully. Using AI to help you brainstorm a science project idea seems totally fine — no one loses. But what if everyone in your class uses AI to brainstorm, and some kids have better AI tools than others? Now the kids with the best tools might have an unfair advantage. That is a sneakier kind of unfairness. The fairness test works best when you also ask: what happens if EVERYONE does this? Would it still be fair? Great thinkers throughout history have called this idea the 'veil of ignorance' — imagining you don't know which person you'd be in the situation. If you would be okay being anyone in the scenario, it's probably fair. If you'd only be okay if you were the winner, that's worth thinking harder about.

• Ask 'who wins, who loses?' as the first step
• Ask 'what if everyone did this?' as the second step
• Notice when fairness depends on having better tools or more access
• Talk to a trusted adult if you're unsure whether something is fair