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Members Warn USDA, NOAA, EPA Cuts and Data Purges Threaten Agrochemical Research and AI Models
Summary
Several members told the same House subcommittee that recent agency staffing cuts, proposed budget reductions and removal of climate data undermine the public datasets and scientific capacity that AI systems and university researchers need to develop safer agrochemicals.
Members of the House Science, Space, and Technology Subcommittee on the Environment used opening statements and questioning to flag recent federal data removals and proposed science funding cuts as direct threats to AI‑enabled agrochemical research.
Speakers described how AI models depend on long‑running, high‑quality public datasets and on agency science workers who collect, curate and publish those data. They said workforce reductions at NOAA, USDA and EPA and proposed budget cuts to NSF and EPA Office of Research and Development risk degrading the inputs that drive AI models and could slow or invalidate regulatory health assessments.
A member warned bluntly that "No algorithm is better than the data that it…
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