Question 1: Define Machine Learning

What is machine learning in your own words? Use an example from today's activity to explain your answer.

Question 2: The Importance of Training Data

Why does AI need lots of training data? Explain what happens when an AI has only a few examples versus when it has many examples.

Question 3: Show Your Data

Draw a simple bar graph below showing how your group's AI improved from Round 1 to Round 2.

• Label the x-axis (horizontal) with "Round 1" and "Round 2"
• Label the y-axis (vertical) with "Accuracy Percentage (%)"
• Number the y-axis from 0 to 100
• Draw bars showing your actual results
• Give your graph a title

Question 4: Real-World Applications

Name three real-world applications that use machine learning. For each one, explain how you think they were trained.

Application 1:

Application 2:

Application 3:

Question 5: Personal Connection

Imagine you are training an AI to recognize your face for phone unlock. What different types of training examples would you need to give it? Think about things like lighting, angles, and facial expressions.

Question 6: Reflection and Learning

What was the most interesting or surprising thing you learned today about how AI systems learn? Explain why it interested or surprised you.

Bonus Question: Critical Thinking

What could go wrong if an AI is trained on bad or biased data? Give an example of a problem this might cause.