AI and GIS for Social Good

This unit explores how AI-enhanced geographic information systems (GIS) support humanitarian and societal challenges—covering disaster response, food and water security, public health, education, biodiversity, and the risks of surveillance. Students examine case studies and synthesize interdisciplinary data to prepare ethical, actionable GIS solutions that inform decision-making in agriculture and natural resources contexts.

Learning Objectives

• Analyze case studies of natural disasters, food and water security, public health, and biodiversity to identify spatial indicators, stakeholder needs, and priorities for GIS-driven interventions
• Apply GIS and AI techniques to integrate remote sensing, biodiversity, proteomics/health, and socio-economic datasets to generate actionable maps or predictive models for disaster response and resource security
• Evaluate ethical, privacy, and equity implications of spatial AI applications (including surveillance risks and algorithmic bias) and propose concrete mitigation strategies and policy recommendations
• Demonstrate the ability to design an interdisciplinary GIS-based intervention plan with defined objectives, data sources, algorithms, evaluation metrics, and consideration of social and environmental impacts