This unit explores Large Language Models (LLMs) by focusing on the interplay between prompts and generated output. It uses a "hands-on" approach, employing unplugged games and simulations to demystify core LLM concepts.
Added in an example of facial recognition bias for asylum seekers. This change was designed for my students, part of who herald from immigrant families and who have darker skin colors. Immigration is a very important topic so adding this slide adds to the relevance of their lives and will help them internalize the information. This change is relevant for teachers that teach in states close to national borders and communities with large immigrant populations.
This unit focuses on how AI is used to create and generate content, including text and images. It discusses GANs (Generative Adversarial Networks) and AI's impact on future jobs.
This unit introduces many of the basic concepts of AI, including supervised machine learning, neural networks, classifying AI vs. Generating AI, and starts to introduce students to thinking about careers in AI.
Most types of AI comprise three parts - a dataset, a learning algorithm, and a prediction - each of which can be influenced by different types of bias (such as algorithmic bias) to prioritize the values of some stakeholders over others.
