AI Bias Analysis

This worksheet helps students in Grades 6, 7, and 8 strengthen critical reading, analytical reasoning, and digital literacy skills by examining how biased data can affect artificial intelligence systems. Using two engaging “data recipe” scenarios, students analyze training data, missing information, and flawed assumptions to understand how unfair outcomes emerge and how more equitable decisions can be designed.

Learning Goals

• Data Bias Analysis (Grades 6-8): Identify how specific data “ingredients” can lead to biased AI predictions.
• Critical Reading: Closely analyze informational scenarios and extract relevant evidence.
• Ethical Reasoning: Understand the connection between data quality, fairness, and real-world consequences.
• Problem-Solving: Propose substitutions or changes that would improve equity in AI systems.

Instructional Benefits

• Educator-Designed Resource: Created by teachers to support clear explanations and meaningful analysis.
• Higher-Order Thinking: Encourages evaluation, reasoning, and justification rather than simple recall.
• Cross-Curricular Fit: Works well in ELA, social studies, or technology education units.
• Flexible Use: Suitable for independent work, small groups, class discussion, or homeschool learning.
• No-Prep Friendly: Ready-to-use format with clear prompts and structured questions.

This printable worksheet supports students as they explore how training data, assumptions, and omissions influence automated decision-making and fairness. By evaluating biased “data recipes” and suggesting improvements, learners practice citing evidence, explaining reasoning, and applying ethical thinking to technology. Whether used in a classroom or homeschool setting, this activity builds strong foundations in critical analysis, digital citizenship, and responsible evaluation of AI systems.

Social Studies – Evaluating Sources and Recognizing Bias

This worksheet is part of our Role of Bias in AI collection.