Geological Technicians
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
0.229
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.26
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, 76% 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 34 hidden tasks| Task | Claude.aiRaw / share % |
|---|---|
Compile, log, or record testing or operational data for review and further analysis.19-4041 | 0.010440.8 |
Test and analyze samples to determine their content and characteristics, using laboratory apparatus or testing equipment.19-4041 | 0.007629.6 |
Assemble, maintain, or distribute information for library or record systems.19-4041 | 0.004316.8 |
Interview individuals, and research public databases in order to obtain information.19-4041 | 0.003312.8 |
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 |
|---|---|
Assemble, maintain, or distribute information for library or record systems.O*NET Task ID 22272 | 1.0 |
Test and analyze samples to determine their content and characteristics, using laboratory apparatus or testing equipment.O*NET Task ID 22262 | 0.5 |
Compile, log, or record testing or operational data for review and further analysis.O*NET Task ID 22264 | 0.5 |
Prepare notes, sketches, geological maps, or cross-sections.O*NET Task ID 22265 | 0.5 |
Prepare or review professional, technical, or other reports regarding sampling, testing, or recommendations of data analysis.O*NET Task ID 22267 | 0.5 |
Read and study reports in order to compile information and data for geological and geophysical prospecting.O*NET Task ID 22269 | 0.5 |
Interview individuals, and research public databases in order to obtain information.O*NET Task ID 22270 | 0.5 |
Plot information from aerial photographs, well logs, section descriptions, or other databases.O*NET Task ID 22271 | 0.5 |
Plan and direct activities of workers who operate equipment to collect data.O*NET Task ID 22274 | 0.5 |
Record readings in order to compile data used in prospecting for oil or gas.O*NET Task ID 22276 | 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