AI Bias & Fairness
By Graphene - Digital Life Lessons
This AI bias and fairness lesson plan helps grades 7–12 students explore algorithmic bias, AI fairness, data, inequality, algorithmic justice, ethics, and AI decision-making. AI is often described as objective, as if removing human judgment automatically makes decisions fairer. But AI systems are trained on human data, shaped by human choices, and can reflect existing inequalities rather than removing them. Students analyze real-world AI bias case studies, discuss fairness tensions, and consider whether AI should be used in high-stakes decisions like criminal justice, hiring, healthcare, credit scoring, and education. This resource helps students understand how bias can enter AI systems through training data, proxy variables, feedback loops, and the illusion of objectivity. This is a low-prep, structured discussion lesson designed to help students think clearly, not tell them what to think. It moves beyond treating AI bias as a technical glitch and gives teachers a classroom-ready way to discuss fairness, responsibility, data, and systemic inequality with care. Check my blogpost that dives a bit deeper. Useful for digital literacy, AI literacy, media literacy, social studies, ethics, technology class, advisory, SEL, counseling-related classes, or any lesson on AI bias and fairness. This activity is part of the AI, Technology and the Future bundle — a set of 6 activities covering how AI works, AI and homework, evaluating AI content, deepfakes, and AI and jobs. 📦What’s include
Find it on: Teachers Pay Teachers