Participants will leave with a better behind-the-scenes understanding of the current state of AI technologies, including strengths, limitations, impacts, and biases. They will have the tools to be critical users and teachers of this technology and cut through marketing hype. It will be a mix of interactive simulations where participants are trained as AI models, metaphors/visuals so all concepts are accessible regardless of background, and examples of AI mishaps in research settings as well as the real world Outline Large Language Models -How do they work? -Why don't they understand what they say? Image Classification -How do they work? -Why are they so easily confused? It's all numbers - how can it be biased? -Examples where training data skews the model, ranging from silly to life-altering to deadly -Examples where biases slip by testing and make it into the real world Human involvement -Real-world examples that show how much humans are involved behind-the-scenes