Assist pathologists or other physicians to collect cell samples by fine needle aspiration (FNA) biopsy or other method.
Work task
“Assist pathologists or other physicians to collect cell samples by fine needle aspiration (FNA) biopsy or other method.” is a core task performed by Cytotechnologists. Among the occupation's 13 rated tasks, workers place it 6th by importance (#8 most important). About 100% of workers say it is relevant to their job.
This is a single occupation-specific task statement from O*NET. The figures below describe how central the task is to the job and what independent studies measure about AI and this kind of work — not a prediction that the task will be automated.
Work activities this task rolls up to
O*NET groups concrete tasks into broader work activities shared across many occupations.
AI exposure
The OpenAI / Eloundou “GPTs are GPTs” study rates this task E0. No direct exposure — current language models give little or no time savings on this task.
Exposure measures whether a model could meaningfully speed the task up — it is an estimate of overlap with model capabilities, not a measure of whether the work will be done by software. The study's intermediate score (β) for this task is 0.00. Automation potential label: T0.
Other tasks in this occupation
- Examine cell samples to detect abnormalities in the color, shape, or size of cellular components and patterns. · importance 5.0
- Document specimens by verifying patients' and specimens' information. · importance 5.0
- Submit slides with abnormal cell structures to pathologists for further examination. · importance 5.0
- Prepare and analyze samples, such as Papanicolaou (PAP) smear body fluids and fine needle aspirations (FNAs), to detect abnormal conditions. · importance 4.9
- Examine specimens, using microscopes, to evaluate specimen quality. · importance 4.8
- Maintain effective laboratory operations by adhering to standards of specimen collection, preparation, or laboratory safety. · importance 4.8
- Provide patient clinical data or microscopic findings to assist pathologists in the preparation of pathology reports. · importance 4.7
- Prepare cell samples by applying special staining techniques, such as chromosomal staining, to differentiate cells or cell components. · importance 4.3
- Adjust, maintain, or repair laboratory equipment, such as microscopes. · importance 4.1
- Assign tasks or coordinate task assignments to ensure adequate performance of laboratory activities. · importance 4.0
- Attend continuing education programs that address laboratory issues. · importance 3.7
- Examine specimens to detect abnormal hormone conditions. · importance 2.4
See all tasks on the Cytotechnologists page.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Singulariki. "Assist pathologists or other physicians to collect cell samples by fine needle aspiration (FNA) biopsy or other method.." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026. https://singulariki.com/tasks/task-17399
Singulariki. (2026). Assist pathologists or other physicians to collect cell samples by fine needle aspiration (FNA) biopsy or other method.. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/tasks/task-17399
@misc{singulariki-task-17399,
title = {Assist pathologists or other physicians to collect cell samples by fine needle aspiration (FNA) biopsy or other method.},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
url = {https://singulariki.com/tasks/task-17399}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.