Will AI replace Laborers and Freight, Stock, and Material Movers, Hand?
Estimated risk score: 11 out of 100
Very low replacement risk
Estimate from published task research, not reviewed by a person · how we estimate
Within about 19 points for 4 in 5 of the jobs we checked (0 to 30).
For the occupation as a whole, from ratings of its 21 O*NET tasks published in 2023 and calibrated to our hand scores. A specialty inside it can sit higher or lower.
O*NET-SOC 53-7062.00 · Transportation and Material Moving
Tasks rated in 2023 as ones AI could do or speed up
Tasks a GPT-4-class model could do, or do in half the time or less: 1 of its 21 rated tasks. In O*NET’s words.
- Record numbers of units handled or moved, using daily production sheets or work tickets.
Tasks rated in 2023 as not sped up by AI
Tasks such a model was rated as not speeding up or taking over: 20 of its 21 rated tasks; the first 6 are shown. In O*NET’s words.
- Attach identifying tags to containers or mark them with identifying information.
- Move freight, stock, or other materials to and from storage or production areas, loading docks, delivery vehicles, ships, or containers, by hand or using trucks, tractors, or other equipment.
- Sort cargo before loading and unloading.
- Read work orders or receive oral instructions to determine work assignments or material or equipment needs.
- Attach slings, hooks, or other devices to lift cargo and guide loads.
- Carry needed tools or supplies from storage or trucks and return them after use.
What the job is
Manually move freight, stock, luggage, or other materials, or perform other general labor. Includes all manual laborers not elsewhere classified.
Also called: Cager, Piler, Lifter, Lugger, Lumper, Mucker, Ragman, Spiker.
Closest jobs we score by hand
In the same field (Transportation and Material Moving). Different jobs, each scored by a person.
Source. This site includes information from the O*NET 30.1 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA. USDOL/ETA has not approved, endorsed, or tested these modifications. (O*NET, CC BY 4.0.) Task ratings: Eloundou, Manning, Mishkin and Rock (2023), “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models”, data used under the MIT licence (licence texts). Our change: we averaged the ratings over this occupation’s tasks and calibrated them to our 0–100 scale. It is not a prediction about any one person and not career advice. Disagree? Write to hello@yourstopwashit.com. How we estimate