All three use AI, though mostly as a tool to process large amounts of scientific or operational data—not as a substitute for professional judgment.
| Agency | Documented uses |
|---|---|
| USGS | Machine learning for terrain and landscape mapping, contaminant and harmful-algal-bloom monitoring, streamflow estimates in ungaged rivers, Landsat telemetry and anomaly analysis, and searching or synthesizing scientific publications. USGS overview |
| National Park Service | Identifying birds from sound recordings, processing wildlife-camera and drone imagery, modeling visitor use, and limited interpretive/archival work such as clearly labeled machine-colorized historic photographs. NPS BirdNET example |
| BLM | Most visibly, AI-assisted camera networks that flag smoke and new ignitions, helping dispatchers respond more quickly to wildfire. BLM Nevada fire-camera example |
Because USGS, NPS, and BLM are all within the Department of the Interior, they operate under Interior-wide AI policy. The Department says AI must be used responsibly and securely, with risk management and human oversight. Interior AI program
USGS is especially clear on scientific use: generative AI tools must be approved, and any AI contribution to a scientific product must be documented, checked for accuracy, and meet standards for reproducibility and scientific integrity. USGS AI-use requirements
The important distinction is this: using AI to help find a bird call, detect smoke, classify satellite pixels, or search thousands of studies is not the same as allowing AI to determine a land-use decision, publish unverified history, or replace a biologist, historian, ranger, or public review process.