Biomedical Engineers

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

    0.133

    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

    0.30

    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, 67% 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 1 hidden task

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
Adapt or design computer hardware or software for medical science uses.

O*NET Task ID 8979

1.0
Write documents describing protocols, policies, standards for use, maintenance, and repair of medical equipment.

O*NET Task ID 18604

1.0
Collaborate with manufacturing or quality assurance staff to prepare product specification or safety sheets, standard operating procedures, user manuals, or qualification and validation reports.

O*NET Task ID 21840

1.0
Design or develop medical diagnostic or clinical instrumentation, equipment, or procedures, using the principles of engineering and biobehavioral sciences.

O*NET Task ID 21847

1.0
Develop statistical models or simulations, using statistical or modeling software.

O*NET Task ID 21851

1.0
Maintain databases of experiment characteristics or results.

O*NET Task ID 21853

1.0
Prepare technical reports, data summary documents, or research articles for scientific publication, regulatory submissions, or patent applications.

O*NET Task ID 21856

1.0
Evaluate the safety, efficiency, and effectiveness of biomedical equipment.

O*NET Task ID 8968

0.5
Advise hospital administrators on the planning, acquisition, and use of medical equipment.

O*NET Task ID 8970

0.5
Research new materials to be used for products, such as implanted artificial organs.

O*NET Task ID 8972

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