Cosmochemists

Life, Physical & Social Sciences

AI exposure

  • Data source: BLSPublished: 2026-08

    Very high· relative

    LowFour relative bandsVery high

    Group-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

    Source dataset (XLSX download)

  • Data source: AnthropicPublished: 2026-03

    0.261

    0.000Range of values carried here0.745
    Scale, basis and source

    Observed exposure index, 0–1 as published

    Mapped onto O*NET tasks

    Source dataset

  • Data source: ILOPublished: 2025

    0.39

    0.09Range of values carried here0.70

    Group-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, 44% score at or above this value.

    Source dataset

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 4 hidden tasks

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.

TaskβE1 + 0.5 × E2
Write technical papers or reports or prepare standards and specifications for processes, facilities, products, or tests.

O*NET Task ID 1511

1.0
Analyze organic or inorganic compounds to determine chemical or physical properties, composition, structure, relationships, or reactions, using chromatography, spectroscopy, or spectrophotometry techniques.

O*NET Task ID 1505

0.5
Develop, improve, or customize products, equipment, formulas, processes, or analytical methods.

O*NET Task ID 1506

0.5
Compile and analyze test information to determine process or equipment operating efficiency or to diagnose malfunctions.

O*NET Task ID 1507

0.5
Confer with scientists or engineers to conduct analyses of research projects, interpret test results, or develop nonstandard tests.

O*NET Task ID 1508

0.5
Direct, coordinate, or advise personnel in test procedures for analyzing components or physical properties of materials.

O*NET Task ID 1509

0.5
Study effects of various methods of processing, preserving, or packaging on composition or properties of foods.

O*NET Task ID 1512

0.5
Evaluate laboratory safety procedures to ensure compliance with standards or to make improvements as needed.

O*NET Task ID 20388

0.5
Purchase laboratory supplies, such as chemicals, when supplies are low or near their expiration date.

O*NET Task ID 20389

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®, Eloundou et al. (2023): see full notices on the Credits page

Occupation information