Document methods used and write technical reports containing information collected.
Work task
“Document methods used and write technical reports containing information collected.” is a supplemental task performed by Remote Sensing Technicians. Among the occupation's 22 rated tasks, workers place it 6th by importance (#17 most important). About 65% 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 E1. Direct exposure — a language model could plausibly cut the time to do this task by at least half.
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 1.00. Automation potential label: T3.
How AI is actually used on this kind of task
The Anthropic Economic Index observes how people actually use AI on tasks like this one across millions of real conversations.
- 0.024% share of AI-use records mapped to this task
- 54% of that use is work-related
- Most common interaction: directive
- Average autonomy of the AI: 3.4 (1–5; higher = more autonomous)
- 93% of interactions still needed a human in the loop
Observed AI use describes people choosing to use AI as a tool on this kind of task today. It is augmentation and assistance, not a measure of jobs replaced.
Working with AI vs. handing it off
Of the AI conversations mapped to this task, the split between people working alongside AI and people delegating the task to it.
How people interact with AI on this task
| Interaction pattern | Share | % | What it means |
|---|---|---|---|
| directive | 45% | you give the instruction; AI produces a finished result | |
| learning | 24% | you ask AI to explain or teach you |
Other tasks in this occupation
- Collect geospatial data, using technologies such as aerial photography, light and radio wave detection systems, digital satellites, or thermal energy systems. · importance 4.4
- Verify integrity and accuracy of data contained in remote sensing image analysis systems. · importance 4.2
- Correct raw data for errors due to factors such as skew or atmospheric variation. · importance 4.1
- Integrate remotely sensed data with other geospatial data. · importance 4.1
- Consult with remote sensing scientists, surveyors, cartographers, or engineers to determine project needs. · importance 4.0
- Adjust remotely sensed images for optimum presentation by using software to select image displays, define image set categories, or choose processing routines. · importance 4.0
- Manipulate raw data to enhance interpretation, either on the ground or during remote sensing flights. · importance 3.9
- Merge scanned images or build photo mosaics of large areas, using image processing software. · importance 3.9
- Calibrate data collection equipment. · importance 3.9
- Develop or maintain geospatial information databases. · importance 3.8
- Monitor raw data quality during collection, and make equipment corrections as necessary. · importance 3.8
- Participate in the planning or development of mapping projects. · importance 3.7
- Maintain records of survey data. · importance 3.5
- Evaluate remote sensing project requirements to determine the types of equipment or computer software necessary to meet project requirements, such as specific image types or output resolutions. · importance 3.4
See all tasks on the Remote Sensing Technicians 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
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
- “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. "Document methods used and write technical reports containing information collected.." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026. https://singulariki.com/tasks/task-16983
Singulariki. (2026). Document methods used and write technical reports containing information collected.. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/tasks/task-16983
@misc{singulariki-task-16983,
title = {Document methods used and write technical reports containing information collected.},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
url = {https://singulariki.com/tasks/task-16983}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.