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Railroad Conductors

Transportation & Material Moving
Projected change 2024–34: +1.1%
Median annual wage (2024): $74,080
Employment (2024): 37K

United States · BLS Employment Projections 2024–34 (figures for SOC 53-4031 occupational group)

AI exposure in published research

Figures below are reproduced from external datasets without modification. Where a dataset does not cover this occupation, the value is shown as — rather than as zero.

Data provider: OpenAI · "GPTs are GPTs"

Time basis: 2023 baselineex-ante estimate

Scored against GPT-4-generation capability.

Human rater basis
20.8%
GPT-4 rater basis
27.8%

β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.

22 rated tasks · 10 tasks with β ≥ 0.5 (45.5%)

Version:
gh-main-0471612
License:
MIT License · Copyright (c) 2024 OpenAI

Data provider: Anthropic Economic Index

Time basis: Published 2026-03-05composite index

Observed exposure
0.0%

Theoretical exposure index weighted by measured Claude usage, per the original report's definition.

21 tasks · usage observed in 0 · mean 0.0%

Data: Anthropic Economic Index — labor_market_impacts, CC-BY, https://huggingface.co/datasets/Anthropic/EconomicIndex

AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.

Version:
hf-lmi-2026-03
License:
CC BY 4.0
Observation period:
(not applicable to this release)
Model:
(not stated by the source)

2023 prediction vs observation-based index published 2026-03-05

One card (GPTs are GPTs) is a 2023 estimate of what AI could theoretically do; the other (Anthropic Economic Index) is built from observed usage and was published on 2026-03-05 — that is its publication date, not the period it observed. They measure different things, so the two figures cannot be added, averaged, or ranked against each other. The older figure is kept here as a baseline for comparison rather than removed.

Caution: the Anthropic figures — observed exposure and task penetration — take the Eloundou β as one of their inputs. The two sides resembling each other is therefore not evidence that the earlier prediction came true; reading it that way is circular reasoning.

The Anthropic figures are measured on Claude users, who are not the whole economy and not the whole workforce.

The mapping of O*NET tasks and occupation codes was performed by AI Changing Work. The source figures themselves were not modified.

These indices are not forecasts. Which point in time each one belongs to is stated on the badge on its card.

Task Breakdown

  • Signal train operations
  • Inspect rolling stock
  • Coordinate train schedules

About This Occupation

If you work as a Railroad Conductors, AI is reshaping your profession. With an automation risk of 12/100 and overall exposure at 14%, this role faces low transformation. The highest-impact area is coordinate train schedules at 50% automation. This is classified as an 'augment' role. BLS projects -1% decline through 2034. Professionals who embrace AI tools will see their capabilities significantly amplified.

ISCO-08 classification

Unit group 8312ILO official

Railway Brake, Signal and Switch Operators

Definition

ILO original text (English)

Railway brakers, signallers and shunters take charge of and safeguard railway freight trains during runs, control the movement of railway traffic by operating signals, switch rolling stock and make up trains in railway yards, make up trains for hauling in mines and control their movement.

Definition & vocabulary source

Source: International Labour Organization (ILO) — ISCO-08 Structure

License: ILO CC BY 4.0

View original

Official occupational information

  • ONET53-4031.00

    Railroad Conductors and Yardmasters

    Coordinate activities of switch-engine crew within railroad yard, industrial plant, or similar location. Conductors coordinate activities of train crew on passenger or freight trains. Yardmasters review train schedules and switching orders and coordinate activities of workers engaged in railroad traffic operations, such as the makeup or breakup of trains and yard switching.

    View original

Source: O*NET 30.2, U.S. DOL/ETA

License: CC BY 4.0

View original

Frequently Asked Questions

The Anthropic Economic Index puts observed exposure at 0.0%. The OpenAI "GPTs are GPTs" rubric puts occupation-level β at 20.8% under human raters. Both figures are reproduced from published research without modification.

They come from two published datasets: the Anthropic Economic Index (labor_market_impacts, CC BY 4.0) and the OpenAI "GPTs are GPTs" exposure rubric (MIT License, Copyright (c) 2024 OpenAI). AI Changing Work maps them onto O*NET occupation and task codes and does not calculate exposure scores of its own. AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.

No. They are a diagnosis of exposure as measured at the time each source dataset was published. AI Changing Work publishes no prediction of future automation or job displacement for this occupation.