Crossing Guards and Flaggers

Protective Service

AI exposure

  • Data source: BLSPublished: 2026-08

    Moderate· 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

    0.000

    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

    0.20

    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, 86% 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

Exposed tasks only

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
Learn the location and purpose of street traffic signs within assigned patrol areas.

O*NET Task ID 11123

1.0
Record license numbers of vehicles disregarding traffic signals, and report infractions to appropriate authorities.

O*NET Task ID 11121

0.5
Monitor traffic flow to locate safe gaps through which pedestrians can cross streets.

O*NET Task ID 11116

0.0
Direct or escort pedestrians across streets, stopping traffic, as necessary.

O*NET Task ID 11117

0.0
Guide or control vehicular or pedestrian traffic at such places as street and railroad crossings and construction sites.

O*NET Task ID 11118

0.0
Communicate traffic and crossing rules and other information to students and adults.

O*NET Task ID 11119

0.0
Report unsafe behavior of children to school officials.

O*NET Task ID 11120

0.0
Direct traffic movement or warn of hazards, using signs, flags, lanterns, and hand signals.

O*NET Task ID 11122

0.0
Stop speeding vehicles to warn drivers of traffic laws.

O*NET Task ID 11124

0.0
Distribute traffic control signs and markers at designated points.

O*NET Task ID 11125

0.0
Discuss traffic routing plans and control-point locations with superiors.

O*NET Task ID 11126

0.0
Inform drivers of detour routes through construction sites.

O*NET Task ID 11127

0.0

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