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Understanding how automation changes work — task by task, with the evidence shown and the uncertainty admitted.

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On this pageWhich technologiesHow it got hereMethod and sources
Occupations›Land surveyor›How we know

Land surveyor — how we know

The page itself gives the judgements. This one gives what they rest on: which technologies bear on the work, how the estimate moved since language models reached the public, and the method behind both.

Assessed
2026-10-01
With evidence
4/5
Verified events
6

Which technologies matter here#

Four separate signals. They are deliberately not added together — a job exposed to two technologies is not twice as exposed.

Physical automation
Field measurementSetting out construction
Cognitive automation
Field measurementResearching and determining boundariesProcessing data and drafting plansCertifying and signing surveys

How it got here#

The index is not a static number. This is where it would have sat at each capability checkpoint since ChatGPT — reconstructed, and labelled as such.

Reconstructed · platform inferenceEstimated today for each past checkpoint — not measured at the time. 14 → 32.
1007550250
Surveyor employment will grow 6 percent from 2025 to 2035, and surveyors will still be needed to review what drones produce, the US Bureau of Labor Statistics estimatedICT construction became the default on earthworks, used on more than 90 percent of national tenders and cutting survey-stake work, Japan's construction ministry reportedAerial and remote-sensing methods were extended from forest to farmland for official cadastral surveys, while boundaries still rest on owners' confirmation, Japan's land ministry saidA 20-minute drone flight surveys sites that would take a field surveyor a whole day, and its drone team flew 1,300 flights in 2023 alongside over 200 surveyors, Ordnance Survey said123456789not assessed
2022 H22024 H2Now

—— this stretch contains a verified event- - - no event in this stretch — reconstruction only0 = no task exposed, 100 = every task exposed

● 4 verified events for this occupation, plotted at the date it happened — the parts of the line near a marker are anchored to something checkable.

Starts at 14 because total stations, GPS and CAD were standard before this chart begins, while fieldwork, setting out and boundary decisions were done by surveyors. It climbs as drones and laser scanners take over part of the measuring, governments allow aerial methods for official surveys, and machines guided by 3D designs replace stakes on large earthworks. It stays below the middle because rules keep boundary decisions and certification with licensed surveyors, and drone surveys still need ground measurement to fill gaps.

12022 H214General-purpose text generation reaches the public. Before this point, exposure came from automation that was already deployed — OCR, RPA, machine vision, self-checkout, dispatch algorithms. ChatGPT research preview (2022-11-30) ↗
22023 H115A general model that passes professional exams. First-draft quality crosses the threshold where professional work starts using it. GPT-4 (2023-03-14) ↗
32023 H216Vision input, long context and tool calling. Models can be pointed at documents and connected to systems, which is what moves process work rather than writing work. GPT-4 Turbo:128k 上下文、视觉、工具调用(DevDay) (2023-11-06) ↗
42024 H118The same capability gets much cheaper and faster. Nothing new becomes possible; a lot becomes affordable at volume, which is when deployment decisions change.
52024 H220Reasoning models that work through multi-step problems, and the first models that operate a computer by looking at the screen. The second one is what reaches software-operating jobs. OpenAI o1(推理);同期 Claude 的 computer use 进入公测 (2024-09-12) ↗
62025 H123Agents begin operating real software end to end rather than producing text for a person to paste. This is also when the first public reversals appear — organisations that automated and partly undid it. Claude 3.7 Sonnet 与 Claude Code:混合推理 + 命令行编码代理 (2025-02-24) ↗
72025 H226Long context and tool use become the default rather than a feature. Capability gains continue; the visible constraint shifts from what models can do to liability, procurement and cost. GPT-5(2025-08-07);Claude Opus 4.5(2025-11-24) (2025-08-07) ↗
82026 H129Long-horizon agents land inside specific industry workflows. Adoption becomes sector-specific rather than general. GPT-5.5:「专为实际工作打造」 (2026-04-23) ↗
9Now32The current assessment — this point is the impact index published on the occupation's page, so the curve is anchored to a number the site already stands behind. Worth noting for the flat curves: in the same weeks, a research preview of a shared specification for AI agents to operate physical devices was opened to research labs and manufacturers. That is the first capability class pointed at the physical occupations whose lines here barely move. GPT-6 Astra(2026-09-03);Claude Fable 5.1 / Mythos 5.1(2026-09-01);Model Hardware Standard 研究预览(2026-08-27) (2026-09-03) ↗

A flat line is not a forecast of safety. It says which tasks automation has reached so far — the occupations that moved least here are the ones where the constraint is physical or regulatory, and both of those can change.

Method and sources#

Assessment date
2026-10-01
Basis of the task judgements
4 evidence-backed · 1 platform inference · 0 not enough evidence
Verified events
6

How we assess an occupation →

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