Claim LD04-SL-C04 (v1.0)
In a preregistered online experiment with a sample of the UK working-age population, ChatGPT use raised productivity on every task tested, more on complex and less ambiguous tasks, but compression between tasks was limited and ChatGPT use did not change productivity differences between gender, age, education or occupation groups.
Provenance and status
- Claim type
- ESTIMATE (as printed: “ESTIMATE”)
- Publication status
- ELIGIBLE (WORKING_PAPER) (as printed: “ELIGIBLE WITH WORKING-PAPER QUALIFIER”)
- Verification state
- CONTENT_VERIFIED_PRIMARY (ABSTRACT_ONLY) (as printed: “CONTENT VERIFIED ABSTRACT”; verified by: UNKNOWN)
- Does not license
- Labour-market inequality effects; retained skill
- Source (field 6, as printed)
- Haslberger, Gingrich & Bhatia, “No Great Equalizer: Experimental Evidence on Productivity Effects of Generative AI Use in the UK Labor Market,” SSRN Working Paper 4594466, 2023
- Source type (field 7)
- WORKING_PAPER (as printed: “Academic working paper”)
- Institutional position
- Independent academic
- Maturity (claim evidence / publication maturity)
- EMERGING (as printed: “EMERGING”)
- Recorded date
- 2026-10-14
- Currentness / correction
- This is the current version. No correction or concern relation is recorded on its Sources.
Version
Pinned version v1.0 (entry LD04-SL-C04--v1.0) — this page never floats to newer evidence.
This pinned version is also the current version.
Pinned Sources (field 6, version-specific)
- “Haslberger, Gingrich & Bhatia, “No Great Equalizer: Experimental Evidence on Productivity Effects of Generative AI Use in the UK Labor Market,” SSRN Working Paper 4594466, 2023” → SRC-SL-HASLBERGER-GINGRICH-BHATIA-SSRN-4594466--v1.0 — Haslberger, Gingrich & Bhatia, “No Great Equalizer: Experimental Evidence on Productivity Effects of Generative AI Use in the UK Labor Market,” SSRN Working Paper 4594466, 2023; class WORKING_PAPER (explicit public provenance pin)
All 25 canonical Claim fields (raw values and normalized values)
| # | Canonical field | Canonical value (verbatim) | Normalized (Claim Value Vocabulary v1.0.2) |
|---|---|---|---|
| 1 | CLAIM ID | LD04-SL-C04 | — |
| 2 | PUBLIC-FACING CLAIM | In a preregistered online experiment with a sample of the UK working-age population, ChatGPT use raised productivity on every task tested, more on complex and less ambiguous tasks, but compression between tasks was limited and ChatGPT use did not change productivity differences between gender, age, education or occupation groups. | — |
| 3 | CLAIM TYPE | ESTIMATE | base_types: ESTIMATE |
| 4 | RESEARCH STRAND | A — Performance while the tool is in use | — |
| 5 | MATURITY | EMERGING | states: EMERGING |
| 6 | SOURCE | Haslberger, Gingrich & Bhatia, “No Great Equalizer: Experimental Evidence on Productivity Effects of Generative AI Use in the UK Labor Market,” SSRN Working Paper 4594466, 2023 | source_ids: SRC-SL-HASLBERGER-GINGRICH-BHATIA-SSRN-4594466 |
| 7 | SOURCE TYPE | Academic working paper | classes: WORKING_PAPER |
| 8 | INSTITUTIONAL POSITION | Independent academic | — |
| 9 | SCOPE | Sample of the UK working-age population; realistic work tasks done online | — |
| 10 | DESIGN | Preregistered online experiment encouraging or discouraging ChatGPT use | — |
| 11 | SAMPLE / DATASET | Sample of the UK working-age population (size not checked) | — |
| 12 | MODEL / TOOL / VERSION | ChatGPT (2023) | — |
| 13 | COMPARATOR | Participants discouraged from using ChatGPT | — |
| 14 | MAIN RESULT | Productivity up on all tasks, more on complex and less ambiguous ones; compression effects between tasks limited; no effect on productivity differentials between gender, age, educational or occupational groups | — |
| 15 | INFERENTIAL TARGET | Whether assisted gains equalize across demographic and occupational groups | — |
| 16 | DOES NOT LICENSE | Labour-market inequality effects; retained skill | — |
| 17 | VERIFICATION STATE | CONTENT VERIFIED ABSTRACT | state: CONTENT_VERIFIED_PRIMARY · qualifiers: ABSTRACT_ONLY · verified_by: UNKNOWN |
| 18 | LIMITATIONS | Online tasks; encouragement design; checked against the official abstract only, read in the paper's SSRN DOI record (Crossref) on 14 October 2026; an earlier abstract summarised in the source notes reported narrowing within most occupational groups and a widening young–old gap, which this abstract does not report; sample size and magnitudes not checked | — |
| 19 | CONTRADICTORY / SUPPORTING SOURCES | Qualifies within-task compression findings: gains on every task need not narrow gaps between groups of workers | — |
| 20 | GEOGRAPHY / LANGUAGE | UK / English | — |
| 21 | DISTRIBUTIONAL LEDGER | No change in productivity differences between gender, age, education or occupation groups | — |
| 22 | R01 / FIELD-MAP LINKS | LD-04, D2, L-A | — |
| 23 | WHAT WOULD CHANGE THIS CLAIM? | A full-text reading or a published version with different subgroup results | — |
| 24 | PUBLICATION STATUS | ELIGIBLE WITH WORKING-PAPER QUALIFIER | state: ELIGIBLE · qualifiers: WORKING_PAPER |
| 25 | RECORDED DATE | 2026-10-14 | — |
Field 22 references resolved against Field Map v0.2: LD-04 (LIVING_DEBATE); D2 (DOMAIN); L-A (LENS)
Cited by Living Debate versions
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 9bbc8ed8209092ffee36ad8cdf2b1b199bba91011a94b32c65e8dbfd7a071b2e.
Repository-authored inputs (not Drive exports)
- SocioLens claim — LD04-SL-C04 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 04 — LD04-SL-C04” SHA-256
f6eb149d6ae84a5d2bef0d81c0274cee81255d4905dc747ec9ef4564d30533ce; fixturefixtures/authored/claims/LD04-SL-C04--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-C04 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-C04 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-HASLBERGER-GINGRICH-BHATIA-SSRN-4594466--v1.0 — basis: field 6 of ENTRY 04 — LD04-SL-C04 cites "Haslberger, Gingrich & Bhatia, “No Great Equalizer: Experimental Evidence on Productivity Effects of Generative AI Use in the UK Labor Market,” SSRN Working Paper 4594466, 2023"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
- SOURCE_PROVENANCE_PIN = SRC-SL-HASLBERGER-GINGRICH-BHATIA-SSRN-4594466--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Haslberger, Gingrich & Bhatia, “No Great Equalizer: Experimental Evidence on Productivity Effects of Generative AI Use in the UK Labor Market,” SSRN Working Paper 4594466, 2023".