Generative AI Unveiled

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Curriculum Area and Level

• Subject: Technology
• Grade Level: 12th Grade
• US Curriculum Alignment:
  • ISTE Standard 1.2.c: Students evaluate the accuracy, bias, and impact of digital content created using cutting-edge technology.
  • CSTA Standards: Computational Thinking (2-IC-23), focusing on the ethical implications and applications of emerging AI tools.

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Learning Objective

By the end of this 15-minute lesson, students will be able to:

1. Explain the concept of Generative AI and how it differs from traditional AI models.
2. Identify real-world applications of Generative AI in areas they interact with daily.
3. Understand ethical concerns, such as bias and misinformation, related to Generative AI usage.

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Materials Needed

• Projector for visuals/slides
• Whiteboard and markers
• One printed chart showcasing types of Generative AI applications (like art, text generation, music, etc.)
• A laptop with a simple pre-trained AI text generator tool locally installed (e.g., GPT-based tool or similar demo model, no internet access needed for live demo).

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Lesson Plan Outline

1. Engagement Hook (3 minutes)

1. Play a 30-second audio clip of AI-generated music. Follow this with a humorous, AI-generated text that is slightly nonsensical. (Example: "A cat flew a spaceship to the moon and sold it for marshmallows.")
2. Ask the class: “What do you think created this? A human or AI?” (Take 2-3 raised hands for a quick discussion.)
3. Introduce the term "Generative AI" and write it on the board. Define it briefly:
   “Generative AI refers to machine learning systems that can CREATE new data, such as text, images, music, or even videos, based on patterns from existing data!”

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2. Explanation (6 minutes)

What is Generative AI? (2 minutes)

1. Briefly describe how Generative AI models work (keeping it high-level and relatable):

   • Comparisons: Traditional AI vs. Generative AI (e.g., Traditional AI recognizes patterns; Generative AI generates new creations based on those patterns.)
   • Mention terms students can connect with, like ChatGPT, DALL-E, and deepfake videos.

2. On the whiteboard, draw a quick visual: Input Data → Pattern Recognition → AI Generates New Outputs (like new text, an image, etc.).

Applications in Daily Life (2 minutes)

1. Explain current generative AI applications:
   • AI in social media (e.g., creating captions, chat replies).
   • AI for creative content (e.g., turning written prompts into art or music).
   • Professional uses (e.g., summarizing documents, coding assistants).
2. Ask students if they’ve used a Generative AI tool (e.g., “Have you used tools like ChatGPT or AI art generators before? If yes, what for?”).

Ethical Concerns (2 minutes)

1. Discuss real-world implications:
   • Bias Amplification: AI-generated results can reflect the biases in training data.
   • Misinformation/Debates: Deepfake videos or text generators can make it hard to distinguish real from fake.
   • Intellectual Property: Who owns AI-generated content?

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3. Short Activity (5 minutes)

AI in Action: Text Generation Demo

1. Use the pre-installed, simple text generator tool to demonstrate. Type in an engaging prompt like: “Describe a futuristic classroom powered by AI.”
2. Read the AI's response aloud (or display it on the projector).
3. Assign students the task below:
   • Think Pair Share: In pairs (two students at one desk), brainstorm ONE new creative use for Generative AI in their daily lives or future careers. Examples: "AI helping create unique sports strategies" or "AI designing original fashion for a perfect prom dress."
   • After 2 minutes, randomly ask 2-3 pairs to share their ideas.

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4. Wrap-Up and Reflection (1 minute)

1. Recap key points on the board:
   • Generative AI creates new data like text, images, and music.
   • It’s already influencing our lives in creative, professional, and ethical ways.
2. Call to action: Encourage students to explore Generative AI responsibly and think critically during its use.

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Adaptations and Extensions

• Advanced Learners: Provide a quick analogy to neural networks and explain how these models learn patterns (e.g., “Imagine teaching a toddler by showing them 10,000 cat pictures; now they can ‘imagine’ their own cat!”).
• Extra Time: If there’s more time, facilitate a classroom debate on “Should Generative AI have limits in what it’s allowed to create?”

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Assessment

• Informal: Observe students’ engagement during the discussion and activity (e.g., their ability to connect everyday scenarios to Generative AI).
• Formal (Exit Ticket Idea, Time Permitting): Students answer one of two questions on an index card:
  1. What excites you the most about Generative AI?
  2. What’s one potential downside of Generative AI?

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"Wow" Factor

• Tying the demo to the real-world impact of Generative AI will make the lesson relatable and memorable.
• The AI-generated music or fun examples (e.g., the cat and marshmallow spaceship) at the start grabs student attention, setting a playful yet thought-provoking tone.