The authors of a survey of 576 public managers in seven EU member states describe public servants using generative AI to draft reports, refine policy proposals and generate content, often without explicit approval or institutional policies, which they call 'shadow use'; the abstract does not say how much of this the survey itself measured.

SocioLens project,

Claim LD03-SL-C10 (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: Its prevalence by country; effects on output or services
Limitations: Checked against the official abstract only, read in the Crossref record on 15 October 2026; the countries and the share of shadow use were not read; the authors' affiliation with the European Commission's Joint Research Centre was not confirmed
Source (as cited): Tangi, Rodriguez Müller & Combetto, “A Silent Partner: The Shadow Presence of Generative Artificial Intelligence in Public Administrations,” Electronic Participation (ePart 2025), LNCS
Source type: Peer-reviewed conference paper (recorded as “Peer-reviewed conference paper”)
Institutional position: Not checked
Maturity of the evidence: Emerging evidence
Recorded date: 15 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Tangi, Rodriguez Müller & Combetto, “A Silent Partner: The Shadow Presence of Generative Artificial Intelligence in Public Administrations,” Electronic Participation (ePart 2025), LNCS (Peer-reviewed conference paper)
Read the original

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_CONFERENCE_PAPER
Maturity (coded): EMERGING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD03-SL-C10	—
2	PUBLIC-FACING CLAIM	The authors of a survey of 576 public managers in seven EU member states describe public servants using generative AI to draft reports, refine policy proposals and generate content, often without explicit approval or institutional policies, which they call 'shadow use'; the abstract does not say how much of this the survey itself measured.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	E — Organizational practice and decoupling	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Tangi, Rodriguez Müller & Combetto, “A Silent Partner: The Shadow Presence of Generative Artificial Intelligence in Public Administrations,” Electronic Participation (ePart 2025), LNCS	source_ids: SRC-SL-TANGI-RODRIGUEZ-MULLER-COMBETTO-EPART-2025
7	SOURCE TYPE	Peer-reviewed conference paper	classes: PEER_REVIEWED_CONFERENCE_PAPER
8	INSTITUTIONAL POSITION	Not checked	—
9	SCOPE	Public administrations in seven EU member states	—
10	DESIGN	Survey	—
11	SAMPLE / DATASET	576 public managers	—
12	MODEL / TOOL / VERSION	Generative AI tools in general	—
13	COMPARATOR	None	—
14	MAIN RESULT	Generative-AI use for drafting, policy refinement and content generation, often without explicit approval or institutional policy ('shadow use')	—
15	INFERENTIAL TARGET	Whether generative-AI use in public administration runs ahead of formal adoption	—
16	DOES NOT LICENSE	Its prevalence by country; effects on output or services	—
17	VERIFICATION STATE	CONTENT VERIFIED ABSTRACT	state: CONTENT_VERIFIED_PRIMARY · qualifiers: ABSTRACT_ONLY · verified_by: UNKNOWN
18	LIMITATIONS	Checked against the official abstract only, read in the Crossref record on 15 October 2026; the countries and the share of shadow use were not read; the authors' affiliation with the European Commission's Joint Research Centre was not confirmed	—
19	CONTRADICTORY / SUPPORTING SOURCES	Consistent with US survey evidence that worker use runs ahead of firm adoption	—
20	GEOGRAPHY / LANGUAGE	EU / English	—
21	DISTRIBUTIONAL LEDGER	Not analysed in this claim	—
22	R01 / FIELD-MAP LINKS	LD-03, D2	—
23	WHAT WOULD CHANGE THIS CLAIM?	Full-text figures on how common unapproved use is	—
24	PUBLICATION STATUS	ELIGIBLE WITH QUALIFIER	state: ELIGIBLE · qualifiers: QUALIFIED
25	RECORDED DATE	2026-10-15	—

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

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

Pinned Sources (field 6, version-specific)

“Tangi, Rodriguez Müller & Combetto, “A Silent Partner: The Shadow Presence of Generative Artificial Intelligence in Public Administrations,” Electronic Participation (ePart 2025), LNCS” → Tangi et al. (2025), “A Silent Partner: The Shadow…” (SRC-SL-TANGI-RODRIGUEZ-MULLER-COMBETTO-EPART-2025--v1.0) — Tangi, Rodriguez Müller & Combetto, “A Silent Partner: The Shadow Presence of Generative Artificial Intelligence in Public Administrations,” Electronic Participation (ePart 2025), LNCS; class PEER_REVIEWED_CONFERENCE_PAPER (explicit public provenance pin)

Cited by Living Debate versions

Organizational absorption: Why micro gains do not become macro outcomes (v0.1) LD-03

Cite this page

SocioLens project. (2026, October 15). The authors of a survey of 576 public managers in seven EU member states describe public servants using generative AI to draft reports, refine policy proposals and generate content, often without explicit approval or institutional policies, which they call 'shadow use'; the abstract does not say how much of this the survey itself measured [Claim LD03-SL-C10, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld03-sl-c10/v1.0/

@misc{sociolens_ld03_sl_c10_v1_0,
  author = {{SocioLens project}},
  title = {The authors of a survey of 576 public managers in seven EU member states describe public servants using generative AI to draft reports, refine policy proposals and generate content, often without explicit approval or institutional policies, which they call 'shadow use'; the abstract does not say how much of this the survey itself measured.},
  year = {2026},
  date = {2026-10-15},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld03-sl-c10/v1.0/}},
  note = {Claim LD03-SL-C10, 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 3956c215347e53b4f25b5ec21537764c2e463dd15d3fa6da9ee8e56686aaec31.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD03-SL-C10 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 10 — LD03-SL-C10” SHA-256 5c64198443052c2b3a4fe1870824e18750d815ccdad6a14937dcc0ad223d9e76; fixture fixtures/authored/claims/LD03-SL-C10--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-C10 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-C10 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-TANGI-RODRIGUEZ-MULLER-COMBETTO-EPART-2025--v1.0 — basis: field 6 of ENTRY 10 — LD03-SL-C10 cites "Tangi, Rodriguez Müller & Combetto, “A Silent Partner: The Shadow Presence of Generative Artificial Intelligence in Public Administrations,” Electronic Participation (ePart 2025), LNCS"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-TANGI-RODRIGUEZ-MULLER-COMBETTO-EPART-2025--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Tangi, Rodriguez Müller & Combetto, “A Silent Partner: The Shadow Presence of Generative Artificial Intelligence in Public Administrations,” Electronic Participation (ePart 2025), LNCS".