School Psychologists

Education & Training

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

    0.047

    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
Compile and interpret students' test results, along with information from teachers and parents, to diagnose conditions and to help assess eligibility for special services.

O*NET Task ID 5446

0.5
Assess an individual child's needs, limitations, and potential, using observation, review of school records, and consultation with parents and school personnel.

O*NET Task ID 5448

0.5
Select, administer, and score psychological tests.

O*NET Task ID 5449

0.5
Provide consultation to parents, teachers, administrators, and others on topics such as learning styles and behavior modification techniques.

O*NET Task ID 5450

0.5
Promote an understanding of child development and its relationship to learning and behavior.

O*NET Task ID 5451

0.5
Collaborate with other educational professionals to develop teaching strategies and school programs.

O*NET Task ID 5452

0.5
Develop individualized educational plans in collaboration with teachers and other staff members.

O*NET Task ID 5454

0.5
Maintain student records, including special education reports, confidential records, records of services provided, and behavioral data.

O*NET Task ID 5455

0.5
Attend workshops, seminars, or professional meetings to remain informed of new developments in school psychology.

O*NET Task ID 5457

0.5
Design classes and programs to meet the needs of special students.

O*NET Task ID 5458

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