Unit #2: Problem Solving (Process)

	Generative AI Students will demystify generative AI models by exploring their internal structures through the familiar lens of input, storage, process, and output. They will gain insights into how these models represent language, the impact of training data on model performance, and the potential for bias.
Topic		Purpose	Lesson
Unit 1: Foundations of Generative AI
L1_Introduction to Generative AI		In order to understand how AI works, students are introduced to its basic framework: Input, Storage, Processing, Output (ISPO).	Click here.
L2_How Smart Is It?		Students explore how "smart" generative AI really is by experimenting with a chatbot	Click here.
L3_Input & Training Data.		Students will explore the process of how AI recognizes and categorizes words.	Click here.
L4_Bias in the Machine		As students develop a 'Recipe Bot', they experience how bias can implicitly and unintentionally creep into large-language models.	Click here.
L5_Is It Biased?		Students explore how bias can show up in AI-generated content, particularly when the system is asked to describe people or recommend things.	Click here.
L6_Understanding Embeddings		Students explore how language models understand and represent word meanings.	Click here.
L7_Understanding Neural Networks		Students learn how word relations and grammar influence word choice.	Click here.
L8_Attention Is All You Need		Students see how language models use embeddings for word meanings and neural networks for relational meaning, introducing the concept of Attention as the process of updating word meanings based on context.	Click here.
L9_Who's Making the Choices?		Students begin to unpack how language models weigh and process input. They connect these patterns to the concept of neural networks and consider how AI “decides” what to say.	Click here.
L10_Outputs & Probabilities		Students see that language models select words with the highest probability from training data.	Click here.
L11_AI Auditing		Students investigate why language models may produce inaccurate outputs, known as hallucinations.	Click here.
L12_Can You Trust the Bot?		Students explore how to recognize and respond to false or misleading information from AI.	Click here.
L13_Demystifying Generative AI			Click here.
L14_Embeddings: How They're Created			Click here.
L15_Neural Networks: How They're Trained			Click here.

Questions? jharrington@sthelenaunified.org