School Social Workers
Education & TrainingAI exposure
- Data source: BLSPublished: 2026-08
High· relative
LowFour relative bandsVery highGroup-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
- Data source: AnthropicPublished: 2026-03
0.007
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.28
0.09Range of values carried here0.70Group-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, 73% score at or above this value.
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 19 hidden tasks| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Counsel individuals, groups, families, or communities regarding issues including mental health, poverty, unemployment, substance abuse, physical abuse, rehabilitation, social adjustment, child care, or medical care.21-1021 | 0.030075.0 | 0.0100100.0 |
Refer clients to community resources for services, such as job placement, debt counseling, legal aid, housing, medical treatment, or financial assistance, and provide concrete information, such as where to go and how to apply.21-1021 | 0.010025.0 | 0.00000.0 |
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.
| Task | βE1 + 0.5 × E2 |
|---|---|
Maintain case history records and prepare reports.O*NET Task ID 237 | 1.0 |
Counsel students whose behavior, school progress, or mental or physical impairment indicate a need for assistance, diagnosing students' problems and arranging for needed services.O*NET Task ID 238 | 0.5 |
Develop and review service plans in consultation with clients and perform follow-ups assessing the quantity and quality of services provided.O*NET Task ID 241 | 0.5 |
Collect supplementary information needed to assist client, such as employment records, medical records, or school reports.O*NET Task ID 242 | 0.5 |
Refer clients to community resources for services, such as job placement, debt counseling, legal aid, housing, medical treatment, or financial assistance, and provide concrete information, such as where to go and how to apply.O*NET Task ID 245 | 0.5 |
Arrange for medical, psychiatric, and other tests that may disclose causes of difficulties and indicate remedial measures.O*NET Task ID 246 | 0.5 |
Administer welfare programs.O*NET Task ID 248 | 0.5 |
Determine clients' eligibility for financial assistance.O*NET Task ID 254 | 0.5 |
Conduct social research.O*NET Task ID 255 | 0.5 |
Serve on policy-making committees, assist in community development, and assist client groups by lobbying for solutions to problems.O*NET Task ID 257 | 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®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page