Condutores Ferroviários

Transporte e Movimentação de Materiais

Exposição à IA

  • Fonte dos dados: BLSPublicado: 2026-08

    Moderado· relativa

    BaixoQuatro faixas relativasMuito alto

    Valor por grupo ocupacional

    Escala, base e fonte

    Quatro faixas relativas (Baixo / Moderado / Alto / Muito alto)

    831 ocupações detalhadas da tabela de projeções de emprego do BLS. O valor é atribuído por código da National Employment Matrix (NEM), pelo que as ocupações que partilham um código NEM recebem a mesma banda

    Conjunto de dados de origem (transferência XLSX)

  • Fonte dos dados: AnthropicPublicado: 2026-03

    0.000

    0.000Intervalo dos valores aqui apresentados0.745
    Escala, base e fonte

    Índice de exposição observada, 0–1 tal como publicado

    Mapeado sobre tarefas O*NET

    Conjunto de dados de origem

  • Fonte dos dados: ILOPublicado: 2025

    0.17

    0.09Intervalo dos valores aqui apresentados0.70

    Valor por grupo ocupacional

    Escala, base e fonte

    Índice de exposição à IA generativa, 0–1 tal como publicado

    Grupo de base CITP-08 — todas as ocupações com o mesmo código recebem este valor

    Calculado por este site, não publicado pela OIT: das 1.012 ocupações que este site liga ao conjunto de dados da OIT, 91% atingem ou superam este valor.

    Conjunto de dados de origem

Que tipo de valor esta fonte publica

A categoria de BLS é uma posição relativa, não um nível absoluto, e também não é uma medição de primeira mão: agrupa em quatro faixas as posições percentis da ocupação em vários estudos publicados. Não é uma previsão de emprego ou de salários, não é uma probabilidade de adoção e não distingue automação de aumento.

Task-level exposure

Apenas tarefas expostas

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
Document and prepare reports of accidents, unscheduled stops, or delays.

O*NET Task ID 10703

1.0
Record departure and arrival times, messages, tickets and revenue collected, and passenger accommodations and destinations.

O*NET Task ID 10707

1.0
Receive information regarding train or rail problems from dispatchers or from electronic monitoring devices.

O*NET Task ID 10691

0.5
Keep records of the contents and destination of each train car, and make sure that cars are added or removed at proper points on routes.

O*NET Task ID 10693

0.5
Receive instructions from dispatchers regarding trains' routes, timetables, and cargoes.

O*NET Task ID 10697

0.5
Review schedules, switching orders, way bills, and shipping records to obtain cargo loading and unloading information and to plan work.

O*NET Task ID 10698

0.5
Confer with engineers regarding train routes, timetables, and cargoes, and to discuss alternative routes when there are rail defects or obstructions.

O*NET Task ID 10699

0.5
Observe yard traffic to determine tracks available to accommodate inbound and outbound traffic.

O*NET Task ID 10702

0.5
Confirm routes and destination information for freight cars.

O*NET Task ID 10704

0.5
Inspect freight cars for compliance with sealing procedures, and record car numbers and seal numbers.

O*NET Task ID 10708

0.5
Signal engineers to begin train runs, stop trains, or change speed, using telecommunications equipment or hand signals.

O*NET Task ID 10690

0.0
Direct and instruct workers engaged in yard activities, such as switching tracks, coupling and uncoupling cars, and routing inbound and outbound traffic.

O*NET Task ID 10692

0.0
Operate controls to activate track switches and traffic signals.

O*NET Task ID 10694

0.0
Instruct workers to set warning signals in front and at rear of trains during emergency stops.

O*NET Task ID 10695

0.0
Direct engineers to move cars to fit planned train configurations, combining or separating cars to make up or break up trains.

O*NET Task ID 10696

0.0
Arrange for the removal of defective cars from trains at stations or stops.

O*NET Task ID 10700

0.0
Inspect each car periodically during runs.

O*NET Task ID 10701

0.0
Supervise and coordinate crew activities to transport freight and passengers and to provide boarding, porter, maid, and meal services to passengers.

O*NET Task ID 10705

0.0
Supervise workers in the inspection and maintenance of mechanical equipment to ensure efficient and safe train operation.

O*NET Task ID 10706

0.0
Collect tickets, fares, or passes from passengers.

O*NET Task ID 10709

0.0
Verify accuracy of timekeeping instruments with engineers to ensure trains depart on time.

O*NET Task ID 10710

0.0
Instruct workers to regulate air conditioning, lighting, and heating in passenger cars to ensure passengers' comfort.

O*NET Task ID 10711

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

Informação ocupacional