Authentic Inclusion: Utilizing AI to Amplify Historically Marginalized Voices

AI is often discussed as a tool for efficiency, but what if we reframed it as a tool for equity? This session moves beyond fear-based narratives to explore how thoughtfully implemented AI can amplify historically underserved students. Drawing on classroom practice, UDL principles and research in algorithmic equity, you will examine whether you approach AI through a lens of restriction or possibility. Through interactive discussion, media analysis and hands-on exploration, you will consider how AI tools can authentically support Indigenous, Black, Latino/a/x, LGBTQIA+, special education and twice-exceptional students by honoring intersectional identities rather than erasing them. You will be introduced to equity-focused AI researchers, including Dr. Timnit Gebru and Dr. Jason Edward Lewis, and learn how personal and systemic bias shapes AI adoption. Leave with a practical framework for evaluating AI tools through an equity lens and a draft plan for at least one UDL-aligned, AI-integrated lesson that reflects the full humanity of your students.