In a preregistered online experiment with 453 college-educated professionals doing occupation-specific writing tasks, ChatGPT access cut time taken by 40% and raised output quality by 18%, and inequality between workers decreased.

SocioLens project,

Claim LD04-SL-C01 (v1.0)

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with a qualifier
Verification state: Checked against the abstract of the primary source only. 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: Retained skill without the tool; effects on careers, wages or real workplaces
Limitations: Short standalone tasks; no measure of learning or of performance after the tool is removed; checked against the official abstract only, read in the article's DOI record (Crossref) on 14 October 2026; the full text was not read
Source (as cited): Noy & Zhang, “Experimental evidence on the productivity effects of generative artificial intelligence,” Science 381(6654), 2023
Source type: Peer-reviewed journal article (recorded as “Peer-reviewed journal article”)
Institutional position: Independent academic
Maturity of the evidence: Rapidly maturing evidence
Recorded date: 14 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Noy & Zhang, “Experimental evidence on the productivity effects of generative artificial intelligence,” Science 381(6654), 2023 (Peer-reviewed journal article)
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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 (as printed: “ESTIMATE”)
Publication status (coded): ELIGIBLE (QUALIFIED) (as printed: “ELIGIBLE WITH QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY (ABSTRACT_ONLY)
Source type (coded): PEER_REVIEWED_JOURNAL_ARTICLE
Maturity (coded): RAPIDLY_MATURING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD04-SL-C01	—
2	PUBLIC-FACING CLAIM	In a preregistered online experiment with 453 college-educated professionals doing occupation-specific writing tasks, ChatGPT access cut time taken by 40% and raised output quality by 18%, and inequality between workers decreased.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	A — Performance while the tool is in use	—
5	MATURITY	RAPIDLY MATURING	states: RAPIDLY_MATURING
6	SOURCE	Noy & Zhang, “Experimental evidence on the productivity effects of generative artificial intelligence,” Science 381(6654), 2023	source_ids: SRC-SL-NOY-ZHANG-SCIENCE-2023
7	SOURCE TYPE	Peer-reviewed journal article	classes: PEER_REVIEWED_JOURNAL_ARTICLE
8	INSTITUTIONAL POSITION	Independent academic	—
9	SCOPE	Short standalone occupation-specific writing tasks; participants recruited online	—
10	DESIGN	Preregistered randomized online experiment	—
11	SAMPLE / DATASET	453 college-educated professionals	—
12	MODEL / TOOL / VERSION	ChatGPT (2023)	—
13	COMPARATOR	Participants without ChatGPT access	—
14	MAIN RESULT	Time −40%; quality +18%; inequality between workers decreased; treated participants more likely to use ChatGPT at work weeks later	—
15	INFERENTIAL TARGET	Assisted task performance and its spread across workers	—
16	DOES NOT LICENSE	Retained skill without the tool; effects on careers, wages or real workplaces	—
17	VERIFICATION STATE	CONTENT VERIFIED ABSTRACT	state: CONTENT_VERIFIED_PRIMARY · qualifiers: ABSTRACT_ONLY · verified_by: UNKNOWN
18	LIMITATIONS	Short standalone tasks; no measure of learning or of performance after the tool is removed; checked against the official abstract only, read in the article's DOI record (Crossref) on 14 October 2026; the full text was not read	—
19	CONTRADICTORY / SUPPORTING SOURCES	Consistent with compression in customer support and coding; contrasts with widening in open-ended entrepreneurial and creative tasks	—
20	GEOGRAPHY / LANGUAGE	Not checked / English	—
21	DISTRIBUTIONAL LEDGER	Lower performers gain more while assisted	—
22	R01 / FIELD-MAP LINKS	LD-04, D2	—
23	WHAT WOULD CHANGE THIS CLAIM?	Full-text reading that changes the reported figures, or replications on longer, non-standalone tasks that reverse the dispersion result	—
24	PUBLICATION STATUS	ELIGIBLE WITH QUALIFIER	state: ELIGIBLE · qualifiers: QUALIFIED
25	RECORDED DATE	2026-10-14	—

Field 22 references resolved against Field Map v0.2: LD-04 (LIVING_DEBATE); D2 (DOMAIN)

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

Pinned Sources (field 6, version-specific)

“Noy & Zhang, “Experimental evidence on the productivity effects of generative artificial intelligence,” Science 381(6654), 2023” → Noy & Zhang (2023), “Experimental evidence on the…” (SRC-SL-NOY-ZHANG-SCIENCE-2023--v1.0) — Noy & Zhang, “Experimental evidence on the productivity effects of generative artificial intelligence,” Science 381(6654), 2023; class PEER_REVIEWED_JOURNAL_ARTICLE (explicit public provenance pin)

Cited by Living Debate versions

Cite this page

SocioLens project. (2026, October 14). In a preregistered online experiment with 453 college-educated professionals doing occupation-specific writing tasks, ChatGPT access cut time taken by 40% and raised output quality by 18%, and inequality between workers decreased [Claim LD04-SL-C01, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld04-sl-c01/v1.0/

@misc{sociolens_ld04_sl_c01_v1_0,
  author = {{SocioLens project}},
  title = {In a preregistered online experiment with 453 college-educated professionals doing occupation-specific writing tasks, ChatGPT access cut time taken by 40\% and raised output quality by 18\%, and inequality between workers decreased.},
  year = {2026},
  date = {2026-10-14},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld04-sl-c01/v1.0/}},
  note = {Claim LD04-SL-C01, 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 e2c5839da995e8aeaafe35deb3b39aee57d33e5fb2166cade814ee69710cae2f.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD04-SL-C01 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-14; 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 14 October 2026 to build the LD-04 debate; a new Claim, first version, written from the project's LD-04 source notes, checked against full texts or official abstracts. Block “ENTRY 01 — LD04-SL-C01” SHA-256 2b327fc5b5b855c9abb77ff6e046f131c9d193cac1eb015a31ff333b565b23c2; fixture fixtures/authored/claims/LD04-SL-C01--v1.0.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD04-SL-C01 v1.0); the first version of a new Claim of the LD-04 debate
CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD04-SL-C01 v1.0" (Project Lead (Claude, AI), 2026-10-14); 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 14 October 2026 to build the LD-04 debate; a new Claim, first version, written from the project's LD-04 source notes, checked against full texts or official abstracts
FIELD_6_SOURCE_REFERENCE = SRC-SL-NOY-ZHANG-SCIENCE-2023--v1.0 — basis: field 6 of ENTRY 01 — LD04-SL-C01 cites "Noy & Zhang, “Experimental evidence on the productivity effects of generative artificial intelligence,” Science 381(6654), 2023"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-NOY-ZHANG-SCIENCE-2023--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Noy & Zhang, “Experimental evidence on the productivity effects of generative artificial intelligence,” Science 381(6654), 2023".