Digital Amazonia Archive & Ethical Data Governance
This research cluster stewards the Digital Amazonia Archive, developing digital infrastructure rooted in Indigenous data sovereignty, open access principles, ethical metadata frameworks, cultural reciprocity, collaborative curation, long-term preservation, and epistemic justice. It aligns with KU’s commitment to responsible data governance while creating a scholarly resource that is sustainable, ethically responsive, and globally significant.
Current Research
Computational Infrastructure for AI-Assisted Social Digital Twins and Migration Resilience Simulations
Kiera Eckhardt
PhD Candidate, Department of Anthropology
University of Kansas
Susheel Nath
PhD Candidate, FARI Institute
Vrije Universiteit Brussel
Abstract
Migration is a complex social process shaped by economic conditions, environmental change, public policy, social networks, and individual decision-making. This project develops an AI-driven digital twin of Quito, Ecuador, to simulate migration dynamics and evaluate the medium- and long-term impacts of alternative migration policies. The model integrates four interconnected layers: a spatial layer representing infrastructure, transit systems, climate risk zones, and public services; a population layer consisting of synthetic populations generated from demographic and migration data; a behavioral layer informed by ethnographic and socioeconomic research on migration decision-making; and a policy layer designed to test alternative governance scenarios.
A key innovation of this research is the incorporation of anthropological insights into agent-based modeling, allowing migrants to be represented as heterogeneous actors differentiated by country of origin, education, skills, income, family structure, migration motivations, and legal status pathways. The model will evaluate multiple policy scenarios, including current migration policy, liberalized visa systems, unrestricted entry frameworks, labor-targeted migration programs, climate migration corridors, and high-investment integration strategies. Outcomes will include projected migration flows, labor market effects, housing demand, fiscal impacts, infrastructure stress, healthcare and education capacity, remittance patterns, inequality, and social cohesion indicators. By combining artificial intelligence, digital twin technology, and ethnographic analysis, this project offers a novel framework for migration forecasting and policy evaluation at the intersection of AI and anthropology.