📚 Topic Summary
This unplugged activity introduces the concept of AI bias and its potential impact, even before students start coding. AI bias occurs when an AI system produces results that are unfairly skewed due to biased data used during its training. This activity explores how biases can creep into datasets and how this can affect the outcomes of AI algorithms. By understanding bias early, students can design and build fairer AI systems in Scratch and beyond.
🧠 Part A: Vocabulary
Match the term with its definition.
| Term |
Definition |
| 1. Algorithm |
A. Unfairly prejudiced for or against someone or something. |
| 2. Bias |
B. A set of rules to be followed in calculations or other problem-solving operations, especially by a computer. |
| 3. Data |
C. Facts and statistics collected together for reference or analysis. |
| 4. Model |
D. A simplified representation or abstraction of a real-world object, system, or concept. |
| 5. Fairness |
E. Impartial and just treatment or behavior without favoritism or discrimination. |
(Answers: 1-B, 2-A, 3-C, 4-D, 5-E)
📊 Part B: Fill in the Blanks
AI systems learn from _____. If this _____ contains _____, the AI can develop a _____. Striving for _____ in AI means ensuring the system doesn't discriminate and treats everyone _____.
(Answers: data, data, bias, bias, fairness, equally)
🤔 Part C: Critical Thinking
Imagine you are creating an AI to recommend books. What steps can you take to ensure that the AI doesn't show bias based on gender or culture? Explain your approach.