Private preview. Not published and not indexed.

Claim LD03-SL-C14 (v1.0)

In a METR survey of 349 technical workers in early 2026, the median respondent reported that AI tools made them about 3 times faster but changed the value of their work by only 1.4 to 2 times; METR warns that such self-reports have overstated measured effects in its own trials.

Research opportunities this claim motivates

What this claim leaves open for research. Each is a hypothesis about a gap, not a finding.

Provenance and status

Claim type
ESTIMATE (as printed: “ESTIMATE”)
Publication status
ELIGIBLE (QUALIFIED) (as printed: “ELIGIBLE WITH QUALIFIER”)
Verification state
CONTENT_VERIFIED_PRIMARY (as printed: “CONTENT VERIFIED”; verified by: UNKNOWN)
Does not license
Measured productivity; a population estimate
Source (field 6, as printed)
Becker, “Measuring the Self-Reported Impact of Early-2026 AI on Technical Worker Productivity,” METR, 11 May 2026
Source type (field 7)
SURVEY (as printed: “Research nonprofit post”)
Institutional position
Independent research nonprofit
Maturity (claim evidence / publication maturity)
EMERGING (as printed: “EMERGING”)
Recorded date
2026-10-15
Currentness / correction
This is the current version. No correction or concern relation is recorded on its Sources.

Version

Current version v1.0, resolved through the explicit current pointer CLAIM--LD03-SL-C14.

Versions:v1.0 · current

Pinned Sources (field 6, version-specific)

All 25 canonical Claim fields (raw values and normalized values)
#Canonical fieldCanonical value (verbatim)Normalized (Claim Value Vocabulary v1.0.2)
1CLAIM IDLD03-SL-C14—
2PUBLIC-FACING CLAIMIn a METR survey of 349 technical workers in early 2026, the median respondent reported that AI tools made them about 3 times faster but changed the value of their work by only 1.4 to 2 times; METR warns that such self-reports have overstated measured effects in its own trials.—
3CLAIM TYPEESTIMATEbase_types: ESTIMATE
4RESEARCH STRANDC — Work reorganization and verification—
5MATURITYEMERGINGstates: EMERGING
6SOURCEBecker, “Measuring the Self-Reported Impact of Early-2026 AI on Technical Worker Productivity,” METR, 11 May 2026source_ids: SRC-SL-BECKER-METR-SELF-REPORT-SURVEY-2026-05-11
7SOURCE TYPEResearch nonprofit postclasses: SURVEY
8INSTITUTIONAL POSITIONIndependent research nonprofit—
9SCOPETechnical workers (software engineers, researchers, academics, founders); February–April 2026—
10DESIGNConvenience-sample survey—
11SAMPLE / DATASET349 respondents—
12MODEL / TOOL / VERSIONAI tools in general—
13COMPARATORRespondents' own estimates without AI—
14MAIN RESULTMedian self-reported speed change 3x; median self-reported value change 1.4–2x; recalled 1.3x for March 2025 and forecast 2.5x for March 2027—
15INFERENTIAL TARGETHow workers judge AI's effect on speed and on the value of their work—
16DOES NOT LICENSEMeasured productivity; a population estimate—
17VERIFICATION STATECONTENT VERIFIEDstate: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18LIMITATIONSConvenience sample with about a 2% response rate and most respondents paid; self-reports, which in METR's 2025 trial overstated AI's effect on time by about 40 percentage points; METR staff gave the lowest answers—
19CONTRADICTORY / SUPPORTING SOURCESConsistent with the theoretical point that time saved overstates value; contrasts with executives reporting little firm-level impact—
20GEOGRAPHY / LANGUAGENot checked / English—
21DISTRIBUTIONAL LEDGERNot analysed in this claim—
22R01 / FIELD-MAP LINKSLD-03, D2—
23WHAT WOULD CHANGE THIS CLAIM?Measured output data for the same population—
24PUBLICATION STATUSELIGIBLE WITH QUALIFIERstate: ELIGIBLE · qualifiers: QUALIFIED
25RECORDED DATE2026-10-15—

Field 22 references resolved against Field Map v0.2: LD-03 (LIVING_DEBATE); D2 (DOMAIN)

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 7771b2b5d7cf31898b005e5aea5d5539d20f520149c40803aedb2857d15c02dc.

Repository-authored inputs (not Drive exports)

  • SocioLens claim — LD03-SL-C14 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-15; 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 15 October 2026 to build the LD-03 debate; a new Claim, first version, written from the project's LD-03 source notes, checked against full texts or official abstracts. Block “ENTRY 14 — LD03-SL-C14” SHA-256 998fdc394b37c3ca2e6df42147fc4951e62ac5b9ada1f0b77d29f33fb14a4d8a; fixture fixtures/authored/claims/LD03-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 — LD03-SL-C14 v1.0); the first version of a new Claim of the LD-03 debate
  • CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD03-SL-C14 v1.0" (Project Lead (Claude, AI), 2026-10-15); 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 15 October 2026 to build the LD-03 debate; a new Claim, first version, written from the project's LD-03 source notes, checked against full texts or official abstracts
  • FIELD_6_SOURCE_REFERENCE = SRC-SL-BECKER-METR-SELF-REPORT-SURVEY-2026-05-11--v1.0 — basis: field 6 of ENTRY 14 — LD03-SL-C14 cites "Becker, “Measuring the Self-Reported Impact of Early-2026 AI on Technical Worker Productivity,” METR, 11 May 2026"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
  • SOURCE_PROVENANCE_PIN = SRC-SL-BECKER-METR-SELF-REPORT-SURVEY-2026-05-11--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Becker, “Measuring the Self-Reported Impact of Early-2026 AI on Technical Worker Productivity,” METR, 11 May 2026".