AI Literacy Essentials introduces how large language models process and generate content, covering neural network architecture and training processes. Students will learn to identify AI limitations including hallucinations, bias, and reasoning failures, developing a balanced perspective on when to leverage these tools effectively.

Areas Covered in the Webinar

• What Generative AI actually means
• Difference between AI, Machine Learning, and GenAI
• Popular AI tools and platforms
• Why AI literacy matters today

How GenAI Works

• Training data and pattern learning
• Tokens and prediction models
• Large Language Models explained simply
• Why AI generates human-like responses
• Understanding prompts and outputs

What AI Gets Wrong

• AI hallucinations
• Fabricated facts and fake citations
• Bias in AI systems
• Outdated or incomplete knowledge
• Overconfidence and misinformation risks

Human vs AI Intelligence

• Why AI does not “think” like humans
• Pattern prediction vs reasoning
• The limits of AI understanding
• Why human oversight still matters

Responsible AI Usage

• Best practices for using AI safely
• Fact-checking AI outputs
• Protecting sensitive information
• Ethical considerations
• Transparency and accountability

Practical Prompting Techniques

• Writing better prompts
• Improving AI-generated responses
• Using context effectively
• Common prompting mistakes