Will AI replace Shoe Machine Operators and Tenders?
Estimated risk score: 9 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 28).
For the occupation as a whole, from ratings of its 19 O*NET tasks published in 2023 and calibrated to our hand scores. A specialty inside it can sit higher or lower.
O*NET-SOC 51-6042.00 · Production
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 19 rated tasks. In O*NET’s words.
- Study work orders or shoe part tags to obtain information about workloads, specifications, and the types of materials to be used.
Tasks rated in 2023 as not sped up by AI
Tasks such a model was rated as not speeding up or taking over: 18 of its 19 rated tasks; the first 6 are shown. In O*NET’s words.
- Cut excess thread or material from shoe parts, using scissors or knives.
- Perform routine equipment maintenance such as cleaning and lubricating machines or replacing broken needles.
- Remove and examine shoes, shoe parts, and designs to verify conformance to specifications such as proper embedding of stitches in channels.
- Align parts to be stitched, following seams, edges, or markings, before positioning them under needles.
- Collect shoe parts from conveyer belts or racks and place them in machinery such as ovens or on molds for dressing, returning them to conveyers or racks to send them to the next work station.
- Draw thread through machine guide slots, needles, and presser feet in preparation for stitching, or load rolls of wire through machine axles.
What the job is
Operate or tend a variety of machines to join, decorate, reinforce, or finish shoes and shoe parts.
Also called: Inseamer, Side Laster, Faker, Soler, Treer, Barrer, Flamer, Fudger.
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