Grade 7: Thinking Critically About AI

Thinking Critically About AI

Approximate Total Time: 5 class periods (approximately 50 minutes each)

Recommended for Ages 12–13 (typically U.S. Grade 7)

About This Unit

Students build a more critical and nuanced understanding of artificial intelligence by examining how AI systems work, why they make mistakes, who shapes their development, and how they affect people and work. Students compare rule-based, data-driven, and hybrid technologies and investigate why generative AI can produce convincing but inaccurate information. They develop practical fact-checking strategies, including lateral reading and the Rule of Three.

Students then investigate the people and decisions behind AI, including how representation can influence system performance. They analyze a real-world case of unequal AI performance and consider possible solutions and tradeoffs. Finally, students explore automation, augmentation, and the human skills that remain important as AI changes learning and work.

Lessons

1. Rules, Patterns, and How Machines Learn
Students compare rule-based and data-driven systems and determine why different types of problems require different approaches.

2. When AI Makes Mistakes
Students investigate why AI can produce convincing but inaccurate outputs and practice strategies for verifying AI-generated information.

3. The People Behind the AI
Students investigate the researchers, developers, data workers, companies, and users involved in AI development and consider how representation and human decisions shape AI systems.

4. AI Doesn't Work the Same for Everyone
Students investigate a real-world example of AI bias, identify possible causes and impacts, and propose ways to improve AI systems while considering competing priorities and tradeoffs.

5. Human Skills in an AI World
Students distinguish between automation and augmentation, examine how AI is changing work, and reflect on the human skills and judgment that remain important.