AI Stole My Job

Will AI replace Textile Knitting and Weaving Machine Setters, Operators, and Tenders?

Estimated risk score: 23 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 (4 to 42).

For the occupation as a whole, from ratings of its 20 O*NET tasks published in 2023 and calibrated to our hand scores. A specialty inside it can sit higher or lower.

O*NET-SOC 51-6063.00 · 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: 3 of its 20 rated tasks. In O*NET’s words.

  1. Record information about work completed and machine settings.
  2. Program electronic equipment.
  3. Study guides, loom patterns, samples, charts, or specification sheets, or confer with supervisors or engineering staff to determine setup requirements.

Tasks rated in 2023 as not sped up by AI

Tasks such a model was rated as not speeding up or taking over: 16 of its 20 rated tasks; the first 6 are shown. In O*NET’s words.

  1. Examine looms to determine causes of loom stoppage, such as warp filling, harness breaks, or mechanical defects.
  2. Remove defects in cloth by cutting and pulling out filling.
  3. Set up, or set up and operate textile machines that perform textile processing and manufacturing operations such as winding, twisting, knitting, weaving, bonding, or stretching.
  4. Start machines, monitor operations, and make adjustments as needed.
  5. Stop machines when specified amounts of product have been produced.
  6. Thread yarn, thread, and fabric through guides, needles, and rollers of machines for weaving, knitting, or other processing.

What the job is

Set up, operate, or tend machines that knit, loop, weave, or draw in textiles.

Also called: Weaver, Tufting Operator, Footer, Ribber, Latcher, Smasher, Tag Maker, Hose Maker.

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