Limnologists
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
0.061
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.40
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, 39% 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 11 hidden tasks| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Analyze characteristics of animals to identify and classify them.19-1023 | 0.028681.5 | 0.0211100.0 |
Study characteristics of animals, such as origin, interrelationships, classification, life histories and diseases, development, genetics, and distribution.19-1023 | 0.00308.5 | —0 |
Prepare collections of preserved specimens or microscopic slides for species identification and study of development or disease.19-1023 | 0.00185.1 | —0 |
Inform and respond to public regarding wildlife and conservation issues, such as plant identification, hunting ordinances, and nuisance wildlife.19-1023 | 0.00174.8 | —0 |
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 |
|---|---|
Disseminate information by writing reports and scientific papers or journal articles, and by making presentations and giving talks for schools, clubs, interest groups and park interpretive programs.O*NET Task ID 1496 | 1.0 |
Study animals in their natural habitats, assessing effects of environment and industry on animals, interpreting findings and recommending alternative operating conditions for industry.O*NET Task ID 1492 | 0.5 |
Inventory or estimate plant and wildlife populations.O*NET Task ID 1493 | 0.5 |
Analyze characteristics of animals to identify and classify them.O*NET Task ID 1494 | 0.5 |
Make recommendations on management systems and planning for wildlife populations and habitat, consulting with stakeholders and the public at large to explore options.O*NET Task ID 1495 | 0.5 |
Study characteristics of animals, such as origin, interrelationships, classification, life histories, diseases, development, genetics, and distribution.O*NET Task ID 1497 | 0.5 |
Perform administrative duties, such as fundraising, public relations, budgeting, and supervision of zoo staff.O*NET Task ID 1498 | 0.5 |
Coordinate preventive programs to control the outbreak of wildlife diseases.O*NET Task ID 1501 | 0.5 |
Inform and respond to public regarding wildlife and conservation issues, such as plant identification, hunting ordinances, and nuisance wildlife.O*NET Task ID 18615 | 0.5 |
Check for, and ensure compliance with, environmental laws, and notify law enforcement when violations are identified.O*NET Task ID 18616 | 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