Eloundou, Manning, Mishkin and Rock conclude that language models “exhibit traits of general-purpose technologies,” estimating that about 80% of the US workforce could have at least 10% of their tasks affected and about 19% at least half; they “do not make predictions about the development or adoption timeline.”

SocioLens project,

Claim LD01-SL-C14 (v1.0)

Provenance and status

Claim type: Estimate and Interpretation
Publication status: Eligible for publication, with qualifiers: institutional position
Verification state: Checked against the primary source; the source is a preprint. Who checked this claim is not recorded for it; claim checks so far were AI-led, and no person has checked claims against their sources.
Does not license: Adoption, productivity or employment effects; the authors say exposure does not guarantee them
Limitations: Read in arXiv version 5 (21 August 2023), labelled a working paper; the Science version was not compared; three authors work for the developer of the models assessed, and one of two annotators is that developer’s model; the human annotators, who include the authors, are a group the paper says “is not occupationally diverse”
Source (as cited): Eloundou, Manning, Mishkin & Rock, “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models,” arXiv:2303.10130, 2023
Source type: Preprint (recorded as “Preprint (working paper; a journal version was published in Science)”)
Institutional position: Mixed: AI developer (three of four authors at OpenAI) and independent academic (University of Pennsylvania)
Maturity of the evidence: Emerging evidence
Recorded date: 16 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Eloundou, Manning, Mishkin & Rock, “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models,” arXiv:2303.10130, 2023 (Preprint)
Read the original

Version

This page shows version v1.0. Its record never changes, even when newer evidence arrives; the site may add a note to the page or withhold a figure not cleared for public use.

This pinned version is also the current version.

Versions: v1.0 · current

Raw record: every recorded field, with its coded values

All 25 canonical Claim fields, verbatim, with the coded values derived from them. The plain-language labels above are read from these.

Claim type (coded): ESTIMATE + INTERPRETATION (as printed: “ESTIMATE / INTERPRETATION”)
Publication status (coded): ELIGIBLE (INSTITUTIONAL_POSITION) (as printed: “ELIGIBLE WITH INSTITUTIONAL-POSITION QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY (PREPRINT)
Source type (coded): PREPRINT
Maturity (coded): EMERGING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD01-SL-C14	—
2	PUBLIC-FACING CLAIM	Eloundou, Manning, Mishkin and Rock conclude that language models “exhibit traits of general-purpose technologies,” estimating that about 80% of the US workforce could have at least 10% of their tasks affected and about 19% at least half; they “do not make predictions about the development or adoption timeline.”	—
3	CLAIM TYPE	ESTIMATE / INTERPRETATION	base_types: ESTIMATE, INTERPRETATION
4	RESEARCH STRAND	A — What each account says generative AI is, and what it predicts	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Eloundou, Manning, Mishkin & Rock, “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models,” arXiv:2303.10130, 2023	source_ids: SRC-SL-ELOUNDOU-ET-AL-ARXIV-2303-10130
7	SOURCE TYPE	Preprint (working paper; a journal version was published in Science)	classes: PREPRINT
8	INSTITUTIONAL POSITION	Mixed: AI developer (three of four authors at OpenAI) and independent academic (University of Pennsylvania)	—
9	SCOPE	United States; occupations and tasks in O*NET; exposure as of 2023	—
10	DESIGN	Task-exposure rubric applied by human annotators and by GPT-4	—
11	SAMPLE / DATASET	O*NET tasks for US occupations	—
12	MODEL / TOOL / VERSION	GPT-3.5- and GPT-4-era models; GPT-4 also used as an annotator	—
13	COMPARATOR	Tasks performed without language models	—
14	MAIN RESULT	About 80% of workers with at least 10% of tasks exposed; about 19% with at least half; the authors say the paper presents evidence for two of the three criteria for a general-purpose technology (pervasiveness and complementary innovation)	—
15	INFERENTIAL TARGET	Technical exposure of work to language models	—
16	DOES NOT LICENSE	Adoption, productivity or employment effects; the authors say exposure does not guarantee them	—
17	VERIFICATION STATE	CONTENT VERIFIED PREPRINT	state: CONTENT_VERIFIED_PRIMARY · qualifiers: PREPRINT · verified_by: UNKNOWN
18	LIMITATIONS	Read in arXiv version 5 (21 August 2023), labelled a working paper; the Science version was not compared; three authors work for the developer of the models assessed, and one of two annotators is that developer’s model; the human annotators, who include the authors, are a group the paper says “is not occupationally diverse”	—
19	CONTRADICTORY / SUPPORTING SOURCES	Adoption measured: LD01-SL-C15; general-purpose technology in official analysis: LD01-SL-C33	—
20	GEOGRAPHY / LANGUAGE	US / English	—
21	DISTRIBUTIONAL LEDGER	Higher-wage jobs are more exposed	—
22	R01 / FIELD-MAP LINKS	LD-01, T4, D2	—
23	WHAT WOULD CHANGE THIS CLAIM?	Exposure scores that fail to predict later adoption or task change	—
24	PUBLICATION STATUS	ELIGIBLE WITH INSTITUTIONAL-POSITION QUALIFIER	state: ELIGIBLE · qualifiers: INSTITUTIONAL_POSITION
25	RECORDED DATE	2026-10-16	—

Field 22 references resolved against Field Map v0.2: LD-01 (LIVING_DEBATE); T4 (TENSION); D2 (DOMAIN)

The sources as recorded, with their record IDs and coded source types:

Pinned Sources (field 6, version-specific)

“Eloundou, Manning, Mishkin & Rock, “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models,” arXiv:2303.10130, 2023” → Eloundou et al. (2023), “GPTs are GPTs: An Early Look at…” (SRC-SL-ELOUNDOU-ET-AL-ARXIV-2303-10130--v1.0) — Eloundou, Manning, Mishkin & Rock, “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models,” arXiv:2303.10130, 2023; class PREPRINT (explicit public provenance pin)

Cited by Living Debate versions

What kind of thing is generative AI, and does the answer predict anything? (v0.1) LD-01

Cite this page

SocioLens project. (2026, October 16). Eloundou, Manning, Mishkin and Rock conclude that language models “exhibit traits of general-purpose technologies,” estimating that about 80% of the US workforce could have at least 10% of their tasks affected and about 19% at least half; they “do not make predictions about the development or adoption timeline.” [Claim LD01-SL-C14, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld01-sl-c14/v1.0/

@misc{sociolens_ld01_sl_c14_v1_0,
  author = {{SocioLens project}},
  title = {Eloundou, Manning, Mishkin and Rock conclude that language models “exhibit traits of general-purpose technologies,” estimating that about 80\% of the US workforce could have at least 10\% of their tasks affected and about 19\% at least half; they “do not make predictions about the development or adoption timeline.”},
  year = {2026},
  date = {2026-10-16},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld01-sl-c14/v1.0/}},
  note = {Claim LD01-SL-C14, version v1.0}
}

The link points to this version, whose record never changes. For a finding, cite the original study as well: SocioLens summarizes research and does not replace it.

Research-of-record provenance

Materialized by sociolens-materializer 0.6.0 at 2026-09-28T20:00:00.000Z; normalization contract SocioLens — Claim Value Vocabulary v1.0.2 — Pre-Spike Materialization Contract (v1.0.2). Content seal SHA-256 753b79bb1093f3015ae4a1b8b0719872624e18d4dc848b4901d6e559e51d05fc.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD01-SL-C14 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-16; no Drive identity exists. Authority: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 16 October 2026 to build the LD-01 debate; a new Claim, first version, written from the project's LD-01 source notes, checked against full texts, official web pages or official abstracts. Block “ENTRY 14 — LD01-SL-C14” SHA-256 5afaf58f94676f2e5247efce751955b2c76ea38b9df4255b213afaa73536fa3f; fixture fixtures/authored/claims/LD01-SL-C14--v1.0.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD01-SL-C14 v1.0); the first version of a new Claim of the LD-01 debate
CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD01-SL-C14 v1.0" (Project Lead (Claude, AI), 2026-10-16); basis: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 16 October 2026 to build the LD-01 debate; a new Claim, first version, written from the project's LD-01 source notes, checked against full texts, official web pages or official abstracts
FIELD_6_SOURCE_REFERENCE = SRC-SL-ELOUNDOU-ET-AL-ARXIV-2303-10130--v1.0 — basis: field 6 of ENTRY 14 — LD01-SL-C14 cites "Eloundou, Manning, Mishkin & Rock, “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models,” arXiv:2303.10130, 2023"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-ELOUNDOU-ET-AL-ARXIV-2303-10130--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Eloundou, Manning, Mishkin & Rock, “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models,” arXiv:2303.10130, 2023".