Conservation Scientists
Life, Physical & Social SciencesAI exposure
- Data source: BLSPublished: 2026-08
High· relative
LowFour relative bandsVery highGroup-level value
Scale, basis and source
Four relative bands (Low / Moderate / High / Very high)
831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band
- Data source: AnthropicPublished: 2026-03
0.000
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.38
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
ISCO-08 unit group — every occupation sharing the code gets this value
Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 48% score at or above this value.
What kind of figure this source publishes
The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.
Task-level exposure
Show 44 hidden tasks| Task | Claude.aiRaw / share % |
|---|---|
Review grant applications or make funding recommendations.19-1031 | 0.010444.7 |
Conduct fact-finding or mediation sessions among government units, landowners, or other agencies to resolve disputes.19-1031 | 0.004217.9 |
Identify or recommend integrated weed and pest management (IPM) strategies, such as resistant plants, cultural or behavioral controls, soil amendments, insects, natural enemies, barriers, or pesticides.19-1031 | 0.003615.6 |
Plan and develop audio-visual devices for public programs.19-1031 | 0.002711.7 |
Analyze results of investigations to determine measures needed to maintain or restore proper soil management.19-1031 | 0.002310.1 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Advise land users, such as farmers or ranchers, on plans, problems, or alternative conservation solutions.O*NET Task ID 22134 | 0.5 |
Monitor projects during or after construction to ensure projects conform to design specifications.O*NET Task ID 22135 | 0.5 |
Visit areas affected by erosion problems to identify causes or determine solutions.O*NET Task ID 22136 | 0.5 |
Apply principles of specialized fields of science, such as agronomy, soil science, forestry, or agriculture, to achieve conservation objectives.O*NET Task ID 22138 | 0.5 |
Gather information from geographic information systems (GIS) databases or applications to formulate land use recommendations.O*NET Task ID 22139 | 0.5 |
Compute design specifications for implementation of conservation practices, using survey or field information, technical guides or engineering manuals.O*NET Task ID 22140 | 0.5 |
Participate on work teams to plan, develop, or implement programs or policies for improving environmental habitats, wetlands, or groundwater or soil resources.O*NET Task ID 22141 | 0.5 |
Conduct fact-finding or mediation sessions among government units, landowners, or other agencies to resolve disputes.O*NET Task ID 22142 | 0.5 |
Respond to complaints or questions on wetland jurisdiction, providing information or clarification.O*NET Task ID 22144 | 0.5 |
Compute cost estimates of different conservation practices, based on needs of land users, maintenance requirements, or life expectancy of practices.O*NET Task ID 22145 | 0.5 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page