Neuroscientists

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

    0.038

    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

    0.40

    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, 39% 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 2 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 and publish articles in scientific journals.

O*NET Task ID 20201

1.0
Write applications for research grants.

O*NET Task ID 23906

1.0
Plan and direct studies to investigate human or animal disease, preventive methods, and treatments for disease.

O*NET Task ID 7513

0.5
Evaluate effects of drugs, gases, pesticides, parasites, and microorganisms at various levels.

O*NET Task ID 7515

0.5
Teach principles of medicine and medical and laboratory procedures to physicians, residents, students, and technicians.

O*NET Task ID 7516

0.5
Prepare and analyze organ, tissue, and cell samples to identify toxicity, bacteria, or microorganisms or to study cell structure.

O*NET Task ID 7517

0.5
Standardize drug dosages, methods of immunization, and procedures for manufacture of drugs and medicinal compounds.

O*NET Task ID 7518

0.5
Investigate cause, progress, life cycle, or mode of transmission of diseases or parasites.

O*NET Task ID 7519

0.5
Confer with health departments, industry personnel, physicians, and others to develop health safety standards and public health improvement programs.

O*NET Task ID 7520

0.5
Study animal and human health and physiological processes.

O*NET Task ID 7521

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