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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›Writer and author›How we know

Writer and author — 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
2026-09-30
With evidence
3/4
Verified events
11

Which technologies matter here#

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

Cognitive automation
Writing fiction and booksScreenwriting and rewritesShort fiction and open submission markets
Process & self-service
Rights and licensing

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. 20 → 52.
1007550250
Writer and author employment will show little or no change from 2025 to 2035, with increasing use of AI for writing expected to dampen demand, the US Bureau of Labor Statistics estimatedA $1.5 billion settlement paying about $3,000 per work was finally approved in Bartz v. Anthropic, with 440,490 of 482,460 listed works claimedThe US screenwriters' 2026 agreement keeps the 2023 AI protections and requires notice to the union when a company licenses scripts to train a commercial AI systemExpert readers who disfavoured prompted AI imitations of authors' styles favoured them once the model was fine-tuned on each author's complete works, a preregistered study foundRuling for Meta on the record in Kadrey v. Meta, a US federal judge said this does not make training on copyrighted books lawful and called market dilution the potentially winning argumentTraining on the books at issue was fair use but building a central library from pirated copies was not, a US federal judge ruled in Bartz v. AnthropicA user who only writes prompts is not the author of AI output, and purely AI-generated material is not protected, the US Copyright Office concludedA world-class novelist outscored GPT-4 Turbo in literary critics' ratings of short stories, and the researchers concluded models are still far from challenging top writersNeither traditional nor generative AI is a writer under the US screenwriters' 2023 agreement, and a company may not require a writer to use ChatGPT to write literary materialStories generated by language models passed 3–10 times fewer creativity tests than stories by professional authors, an expert assessment foundMachine-written spam submissions surged at Clarkesworld and the science-fiction magazine temporarily closed submissions, its editor reported in February 2023123456789not assessed
2022 H22024 H2Now

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

● 11 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 20 because word processing, grammar checkers and self-publishing platforms had changed how books are made and sold before this chart begins, while the writing itself stayed with authors. It climbs with the releases that could draft stories and scripts, which flooded open markets first, and stays in the middle because prompted models still fall well short of professional fiction, the screenwriters' contract defines the writer as a person, and courts are setting terms for training on books.

12022 H220General-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 H124A general model that passes professional exams. First-draft quality crosses the threshold where professional work starts using it. GPT-4 (2023-03-14) ↗
32023 H230Vision 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 H136The same capability gets much cheaper and faster. Nothing new becomes possible; a lot becomes affordable at volume, which is when deployment decisions change.
52024 H241Reasoning 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 H145Agents 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 H248Long 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 H150Long-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) ↗
9Now52The 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
2026-09-30
Basis of the task judgements
3 evidence-backed · 1 platform inference · 0 not enough evidence
Verified events
11

How we assess an occupation →

← Back to Writer and authorThe other layer: every task, one by one →Skills, knowledge and related jobs (O*NET) →