Detailed Agenda

As AI capabilities expand within ArcGIS, educators must prepare students to critically evaluate ethical implications. This session will examine bias in training data, spatial inequities amplified through predictive modeling, privacy concerns in location analytics, and responsible automation. Participants will discuss transparency, model interpretability, and governance considerations in academic settings. The session equips instructors with language, case studies, and discussion frameworks to ensure ethical reasoning remains central to AI-driven geospatial education.