Transit Police
Protective ServiceAI exposure
- Data source: BLSPublished: 2026-08
Moderate· 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
0.000
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.14
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, 95% 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
Exposed tasks onlyValues 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 |
|---|---|
Prepare reports documenting investigation activities and results.O*NET Task ID 9478 | 1.0 |
Examine credentials of unauthorized persons attempting to enter secured areas.O*NET Task ID 9476 | 0.5 |
Investigate or direct investigations of freight theft, suspicious damage or loss of passengers' valuables, or other crimes on railroad property.O*NET Task ID 9479 | 0.5 |
Interview neighbors, associates, or former employers of job applicants to verify personal references or to obtain work history data.O*NET Task ID 9482 | 0.5 |
Record and verify seal numbers from boxcars containing frequently pilfered items, such as cigarettes or liquor, to detect tampering.O*NET Task ID 9483 | 0.5 |
Plan or implement special safety or preventive programs, such as fire or accident prevention.O*NET Task ID 9484 | 0.5 |
Patrol railroad yards, cars, stations, or other facilities to protect company property or shipments and to maintain order.O*NET Task ID 9475 | 0.0 |
Apprehend or remove trespassers or thieves from railroad property or coordinate with law enforcement agencies in apprehensions and removals.O*NET Task ID 9477 | 0.0 |
Direct security activities at derailments, fires, floods, or strikes involving railroad property.O*NET Task ID 9480 | 0.0 |
Direct or coordinate the daily activities or training of security staff.O*NET Task ID 9481 | 0.0 |
Seal empty boxcars by twisting nails in door hasps, using nail twisters.O*NET Task ID 9485 | 0.0 |
Monitor transit areas and conduct security checks to protect railroad properties, patrons, and employees.O*NET Task ID 21002 | 0.0 |
Enforce traffic laws regarding the transit system and reprimand individuals who violate them.O*NET Task ID 21003 | 0.0 |
Provide training to the public or law enforcement personnel in railroad safety or security.O*NET Task ID 21004 | 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