Level Up Ai

The central aim of Level Up AI is to provide a replicable, flexible model for AI literacy instruction that mirrors the interdisciplinary and uncertain nature of real-world AI systems. Rather than isolating AI education within computer science, the book invites learners to explore connections across astronomy, biology, literature, history, and the arts-fields where ambiguity, interpretation, and context deeply matter.

Game-based learning serves as a pedagogical approach to confront these complexities. By immersing students in interactive simulations and narrative-rich scenarios, games create safe environments to navigate uncertainty, make decisions with incomplete data, and reason through the ethical and civic dilemmas AI often presents. Students grapple with questions like: How should an algorithm rank applicants for public housing, and what trade-offs are fair? What might an AI misinterpret in a historical photograph, and how do biases enter the system? How do AI models classify galaxies-or generate visual art-and what happens when those classifications go wrong?