Lesson Stacks

This stack invites students to examine AI as a system shaped by human choices and therefore open to scrutiny, rather than as a neutral tool. Beginning with the foundations of algorithmic bias, students move toward understanding how bias affects real-world applications, then confront its global consequences, especially for communities in the Global South who are rarely centered in AI development. From there, students turn to questions about how their own data is collected and used, before arriving at a capstone lesson that asks them to articulate the principles that should guide ethical AI use. Together, these five lessons build a progressive argument that recognizing bias is only the first step and that responsibility requires attention to whose voices are included, whose data is used, and what values guide design decisions. This stack is well suited for social studies, ethics, or interdisciplinary AI literacy courses.

This stack asks a simple question: does AI help or harm the planet? Students begin by confronting an uncomfortable fact, that AI itself consumes significant energy and water, before exploring how AI is being applied to combat climate change and expand renewable energy. The stack then turns to a concrete application, examining how AI-powered forecasting models help communities prepare for floods, a growing threat as climate change intensifies. The sequence closes with a debate lesson asking students to weigh everything they have learned and form their own evidence-based position on whether AI's environmental costs are justified by its benefits. Rather than presenting AI as either a solution or a problem, this stack pushes students toward nuanced judgment about real trade-offs. This stack is well suited for science or environmental studies classrooms.

This stack explores how generative AI is reshaping creative practice across visual art, music, and writing, inviting students to question assumptions about what creativity means and who, or what, can be creative. Students begin by debating whether AI is disrupting or expanding traditional art-making, then examine specific generative tools used to produce visual artwork. The stack continues into music, where students experiment with composing using generative AI, before turning to language arts, first exploring AI's role in storytelling broadly, then applying the same lens to narrative writing in an English classroom. Across all five lessons, students will be invited to weigh AI's creative possibilities against its limitations, considering questions of authorship, originality, and the human role in the creative process. This stack is well suited for art, music, and language arts classrooms.