Subway Operators

Transportation & Material Moving

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
Report delays, mechanical problems, and emergencies to supervisors or dispatchers, using radios.

O*NET Task ID 12770

1.0
Make announcements to passengers, such as notifications of upcoming stops or schedule delays.

O*NET Task ID 12771

1.0
Complete reports, including shift summaries and incident or accident reports.

O*NET Task ID 12772

1.0
Greet passengers, provide information, and answer questions concerning fares, schedules, transfers, and routings.

O*NET Task ID 12773

1.0
Record transactions and coin receptor readings to verify the amount of money collected.

O*NET Task ID 12776

1.0
Operate controls to open and close transit vehicle doors.

O*NET Task ID 12765

0.0
Drive and control rail-guided public transportation, such as subways, elevated trains, and electric-powered streetcars, trams, or trolleys, to transport passengers.

O*NET Task ID 12766

0.0
Monitor lights indicating obstructions or other trains ahead and watch for car and truck traffic at crossings to stay alert to potential hazards.

O*NET Task ID 12767

0.0
Direct emergency evacuation procedures.

O*NET Task ID 12768

0.0
Regulate vehicle speed and the time spent at each stop to maintain schedules.

O*NET Task ID 12769

0.0
Attend meetings on driver and passenger safety to learn ways in which job performance might be affected.

O*NET Task ID 12774

0.0
Collect fares from passengers, and issue change and transfers.

O*NET Task ID 12775

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