Narrative review: governance-aware autonomous GIS and ethical/privacy risks in LLM-enabled GeoAI
This arXiv narrative review (arXiv:2609.16232v1) synthesizes eight recurring ethical, privacy, and governance issues in LLM-enabled geospatial AI—including data provenance, spatial privacy and inference risks, spatially structured bias (e.g., spatial autocorrelation and MAUP), hallucinated spatial facts, and compounding uncertainty—and proposes a governance-aware architecture with enforceable controls illustrated via a flood-response routing scenario while noting a lack of field-tested evaluations. The paper concludes with a research agenda stressing empirical validation, spatially specific interpretability tools, and workforce development aligned to these risks.