📚 Topic Summary
Data bias occurs when the data used to train a computer program doesn't accurately represent the real world. This can lead to unfair or inaccurate results. For example, if a facial recognition system is trained mostly on images of one race, it might not work as well for people of other races. Understanding data bias is super important for creating fair and reliable technology. We need to be aware of where our data comes from and whether it accurately reflects the population it's supposed to represent.
This worksheet will introduce you to the concept of data bias, why it's important, and how to think critically about the data we use in computer science.
🧠 Part A: Vocabulary
Match the term with its correct definition:
| Term |
Definition |
| 1. Data Bias |
A. Data that doesn't accurately represent the real world. |
| 2. Algorithm |
B. A set of instructions for a computer to follow. |
| 3. Representation |
C. The way data reflects the population or situation it describes. |
| 4. Fairness |
D. Ensuring everyone is treated equitably and without prejudice. |
| 5. Sample |
E. A subset of data selected from a larger population. |
Match the terms above with the definitions below:
- 1. ______
- 2. ______
- 3. ______
- 4. ______
- 5. ______
📝 Part B: Fill in the Blanks
Read the paragraph below and fill in the missing words:
When we train a computer program, we use _____. If this data is _____, it can lead to _____ results. It's important to ensure our data has good _____, meaning it accurately reflects the real world. We also need to consider _____ when building these systems, so everyone is treated fairly.
Word Bank: representation, biased, data, unfair, fairness
🤔 Part C: Critical Thinking
Imagine you are building a program to predict which students will need extra help in math. What kind of data might you use? What are some potential sources of bias in that data, and how could you address them?