Claim LD04-SL-C01 (v1.0)
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.
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
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.
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; fixturefixtures/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".