AI Ethics (Bias, Fairness, Safety)

👩‍🏫 Teacher’s Guide

Objective
Students will describe AI ethics using simple ideas: bias, fairness, and safety, and explain why people must use AI responsibly.

Teaching Notes

Define bias as unfairness that can happen if data is not balanced.
Use simple examples: a system works better for some people than others.
Discuss safety: AI should not cause harm and should be used carefully.
Encourage empathy and fairness when designing and using technology.

🧒 Student Worksheet

Concept and Helping Material

AI ethics means using AI in a fair and safe way. Bias can make AI treat people unfairly. Fairness means AI should work well for everyone. Safety means AI should not cause harm.

Computer Vocabulary and Definition

— Doing what is right and fair.
— Unfair results that can happen in AI.
— Treating people equally and giving everyone a chance.
— Being protected from harm.
— Making careful and good choices.

Computer QA

What are ethics?
What is bias in AI?
What is fairness?
What does safety mean?
What does responsible mean?
True or False: AI should be fair to everyone.
True or False: Bias can happen if data is not balanced.
Why is AI safety important?
What is one way to reduce bias?
Who should think about AI ethics?
Can AI make unfair choices?
What should you do if you see unfair technology?
True or False: Ethics only matter offline.
What is one example of responsible AI use?
Why should we test AI systems?
What is one way AI could be unsafe?
What should you do with important AI answers?
Can people improve AI fairness?
What is one rule for safe AI use?
Why should we care about fairness?

Computer Prtactices

Fair or unfair? Sort scenarios about AI recommendations and choices.
Bias example: Make two small data lists and see how results change.
Safety checklist: Write 5 rules for using AI tools safely.
Class discussion: How can we be responsible digital citizens with AI?

Reflection

What does fairness mean in AI?
Why is AI ethics important?