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Claim LD04-SL-C14 (v1.0)

In an observational study at four Polish centres, experienced endoscopists’ adenoma detection in colonoscopies done without AI fell from 28.4% to 22.4% in the three months after an AI detection system was introduced; the study is observational, and its authors list differences between the cohorts and a near doubling of colonoscopy volume after AI was introduced among its limitations.

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
Publication status
Eligible for publication, with qualifiers: strong scope
Verification state
Checked against the primary source. 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
Causal deskilling; claims about generative AI; claims about trainees
Limitations
Observational; cohorts may differ; no blinding or withdrawal-time data; post-AI volume nearly doubled after Poland suspended screening; regression to the mean possible in high-baseline centres; read from the authors’ accepted manuscript, which may differ from the published version
Source (as cited)
Budzyń et al., “Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: a multicentre, observational study,” Lancet Gastroenterology & Hepatology 10(10), 2025
Source type
Peer-reviewed journal article (recorded as “Peer-reviewed journal article”)
Institutional position
Independent academic
Maturity of the evidence
Contested 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 is the current version, v1.0. Earlier versions stay available, and their records never change.

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 (STRONG_SCOPE) (as printed: “ELIGIBLE WITH STRONG SCOPE QUALIFIER”)
Verification state (coded)
CONTENT_VERIFIED_PRIMARY
Source type (coded)
PEER_REVIEWED_JOURNAL_ARTICLE
Maturity (coded)
CONTESTED
#Canonical fieldCanonical value (verbatim)Normalized (Claim Value Vocabulary v1.0.2)
1CLAIM IDLD04-SL-C14—
2PUBLIC-FACING CLAIMIn an observational study at four Polish centres, experienced endoscopists’ adenoma detection in colonoscopies done without AI fell from 28.4% to 22.4% in the three months after an AI detection system was introduced; the study is observational, and its authors list differences between the cohorts and a near doubling of colonoscopy volume after AI was introduced among its limitations.—
3CLAIM TYPEESTIMATEbase_types: ESTIMATE
4RESEARCH STRANDB — Skill after the tool is removed—
5MATURITYCONTESTEDstates: CONTESTED
6SOURCEBudzyń et al., “Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: a multicentre, observational study,” Lancet Gastroenterology & Hepatology 10(10), 2025source_ids: SRC-SL-BUDZYN-ET-AL-LANCET-GH-2025
7SOURCE TYPEPeer-reviewed journal articleclasses: PEER_REVIEWED_JOURNAL_ARTICLE
8INSTITUTIONAL POSITIONIndependent academic—
9SCOPEFour centres in Poland within the ACCEPT trial; September 2021 to March 2022; diagnostic AI, not generative AI—
10DESIGNRetrospective before–after comparison of non-AI colonoscopies around AI introduction—
11SAMPLE / DATASET795 colonoscopies before and 648 after; 19 endoscopists with over 2,000 colonoscopies each—
12MODEL / TOOL / VERSIONComputer-aided polyp detection system—
13COMPARATORNon-AI colonoscopies by the same endoscopists before AI was introduced—
14MAIN RESULTAdenoma detection rate 28.4% → 22.4% (−6.0 points, 95% CI −10.5 to −1.6); AI exposure odds ratio 0.69 (0.53–0.89) in the main multivariable model; adenomas per colonoscopy, advanced adenomas and cancers did not differ significantly—
15INFERENTIAL TARGETWhether unaided detection changes after routine AI exposure—
16DOES NOT LICENSECausal deskilling; claims about generative AI; claims about trainees—
17VERIFICATION STATECONTENT VERIFIEDstate: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18LIMITATIONSObservational; cohorts may differ; no blinding or withdrawal-time data; post-AI volume nearly doubled after Poland suspended screening; regression to the mean possible in high-baseline centres; read from the authors’ accepted manuscript, which may differ from the published version—
19CONTRADICTORY / SUPPORTING SOURCESA single-centre Japanese prospective study is reported to find no decline (not read for this debate)—
20GEOGRAPHY / LANGUAGEPoland / English—
21DISTRIBUTIONAL LEDGERMost endoscopists fell, four rose; drop larger in high-baseline centres—
22R01 / FIELD-MAP LINKSLD-04, D3—
23WHAT WOULD CHANGE THIS CLAIM?A trial with planned AI-off sessions, or prospective studies that find no decline—
24PUBLICATION STATUSELIGIBLE WITH STRONG SCOPE QUALIFIERstate: ELIGIBLE · qualifiers: STRONG_SCOPE
25RECORDED DATE2026-10-14—

Field 22 references resolved against Field Map v0.2: LD-04 (LIVING_DEBATE); D3 (DOMAIN)

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

Pinned Sources (field 6, version-specific)

  • “Budzyń et al., “Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: a multicentre, observational study,” Lancet Gastroenterology & Hepatology 10(10), 2025” → Budzyń et al. (2025), “Endoscopist deskilling risk after…” (SRC-SL-BUDZYN-ET-AL-LANCET-GH-2025--v1.0) — Budzyń et al., “Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: a multicentre, observational study,” Lancet Gastroenterology & Hepatology 10(10), 2025; class PEER_REVIEWED_JOURNAL_ARTICLE (explicit public provenance pin)

Cited by Living Debate versions

Cite this page

SocioLens project. (2026, October 14). In an observational study at four Polish centres, experienced endoscopists’ adenoma detection in colonoscopies done without AI fell from 28.4% to 22.4% in the three months after an AI detection system was introduced; the study is observational, and its authors list differences between the cohorts and a near doubling of colonoscopy volume after AI was introduced among its limitations [Claim LD04-SL-C14, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld04-sl-c14/v1.0/

@misc{sociolens_ld04_sl_c14_v1_0,
  author = {{SocioLens project}},
  title = {In an observational study at four Polish centres, experienced endoscopists’ adenoma detection in colonoscopies done without AI fell from 28.4\% to 22.4\% in the three months after an AI detection system was introduced; the study is observational, and its authors list differences between the cohorts and a near doubling of colonoscopy volume after AI was introduced among its limitations.},
  year = {2026},
  date = {2026-10-14},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld04-sl-c14/v1.0/}},
  note = {Claim LD04-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 e616aba770a3ff95c126754c08851568f9f048ee5c0b205daf135251cdb42ef9.

Repository-authored inputs (not Drive exports)

  • SocioLens claim — LD04-SL-C14 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 14 — LD04-SL-C14” SHA-256 182ceddbcc85d70d9dbab46e3fd81a32806865b3eda2a2e94db4537a1784eba7; fixture fixtures/authored/claims/LD04-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 — LD04-SL-C14 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-C14 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-BUDZYN-ET-AL-LANCET-GH-2025--v1.0 — basis: field 6 of ENTRY 14 — LD04-SL-C14 cites "Budzyń et al., “Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: a multicentre, observational study,” Lancet Gastroenterology & Hepatology 10(10), 2025"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
  • SOURCE_PROVENANCE_PIN = SRC-SL-BUDZYN-ET-AL-LANCET-GH-2025--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Budzyń et al., “Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: a multicentre, observational study,” Lancet Gastroenterology & Hepatology 10(10), 2025".