OBSERVED IN REAL USE · Anthropic 2026
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Not yet measured in the Anthropic Economic Index. The exposure figure is a capability estimate only.
The machines are eyeing your desk.
50% of this role’s O*NET tasks are within reach of today’s AI. That is the core-weighted exposure score from Eloundou et al. 2023 (“GPTs are GPTs”). It measures a capability ceiling, not a headcount forecast. Heavily exposed. Most of the tasks are within reach of today’s AI.
WHAT AI CAN ALREADY DO
- Develop computer models for hydrologic predictions
- Write groundwater contamination reports on known, suspected, or potential hazardous waste sites
- Write materials for research publications, such as maps, tables, and reports, to disseminate findings
- Analyze ecological data about the impact of pollution, erosion, floods, and other environmental problems on bodies of water
- Answer technical questions from hydrologists, policymakers, or other customers developing water conservation plans
WHAT IT STILL CAN’T
- Collect water and soil samples to test for physical, chemical, or biological properties, such as pH, oxygen level, temperature, and pollution
- Measure the properties of bodies of water, such as water levels, volume, and flow
- Prepare, install, maintain, or repair equipment used for hydrologic study, such as water level recorders, stream flow gauges, and water analyzers
THE HONEST PART. A percentage is not a pink slip. High exposure usually means a role shrinks and shifts toward judgment, direction and responsibility: the parts a model can’t sign its name to. Exposure ≠ displacement. Breathe.
"My job is 50% cooked. What’s yours?"
SOURCES: O*NET 30.3 occupational tasks · Eloundou et al. 2023 (“GPTs are GPTs”,
arXiv:2303.10130) · Anthropic Economic Index 2026 (CC-BY) |
how this is calculated |
last updated 2026-07-16