Industrial Ecologists

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

    0.055

    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

    0.38

    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, 48% 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

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
Create complex and dynamic mathematical models of population, community, or ecological systems.

O*NET Task ID 16891

1.0
Prepare technical and research reports, such as environmental impact reports, and communicate the results to individuals in industry, government, or the general public.

O*NET Task ID 19978

1.0
Investigate accidents affecting the environment to assess ecological impact.

O*NET Task ID 16879

0.5
Investigate the adaptability of various animal and plant species to changed environmental conditions.

O*NET Task ID 16880

0.5
Review industrial practices, such as the methods and materials used in construction or production, to identify potential liabilities and environmental hazards.

O*NET Task ID 16881

0.5
Research sources of pollution to determine environmental impact or to develop methods of pollution abatement or control.

O*NET Task ID 16882

0.5
Provide industrial managers with technical materials on environmental issues, regulatory guidelines, or compliance actions.

O*NET Task ID 16883

0.5
Plan or conduct studies of the ecological implications of historic or projected changes in industrial processes or development.

O*NET Task ID 16884

0.5
Plan or conduct field research on topics such as industrial production, industrial ecology, population ecology, and environmental production or sustainability.

O*NET Task ID 16885

0.5
Monitor the environmental impact of development activities, pollution, or land degradation.

O*NET Task ID 16886

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