Roughly 15% or less of peer-reviewed responsible-AI publications each year had a co-author affiliated with industry; from 2018 to 2022 industry’s participation at responsible-AI conferences stayed between about 20% and 23% while at leading AI conferences it rose from 29% to 37%; 34.5% of 519 AI-publishing firms published any responsible-AI research.

SocioLens project,

Claim LD08-SL-C11 (v1.0)

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with qualifiers: preprint
Verification state: Checked against the primary source; the source is a preprint. 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Does not license: A claim that firms do not influence such research through funding, data or agenda, or about unpublished internal work
Limitations: Read in arXiv version 2 (revised 28 January 2026); the firm denominator is firms holding US AI patents; the main classifier is SciBERT with XGBoost (92.4% on 500 papers); about half of the 50 most-cited responsible-AI conference papers have industry authors, as the authors report; publication counts miss internal and unpublished work; "responsible AI" is defined broadly
Source (as cited): Ahmed, Das, Martin & Banerjee, “The Narrow Depth and Breadth of Corporate Responsible AI Research,” arXiv:2405.12193, 2026
Source type: Preprint (recorded as “Preprint”)
Institutional position: Independent academic (University of Arkansas, University of Oregon, University of Notre Dame and Southern Illinois University)
Maturity of the evidence: Emerging evidence
Recorded date: 16 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Ahmed, Das, Martin & Banerjee, “The Narrow Depth and Breadth of Corporate Responsible AI Research,” arXiv:2405.12193, 2026 (Preprint)
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 (PREPRINT) (as printed: “ELIGIBLE WITH PREPRINT QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY (PREPRINT)
Source type (coded): PREPRINT
Maturity (coded): EMERGING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD08-SL-C11	—
2	PUBLIC-FACING CLAIM	Roughly 15% or less of peer-reviewed responsible-AI publications each year had a co-author affiliated with industry; from 2018 to 2022 industry’s participation at responsible-AI conferences stayed between about 20% and 23% while at leading AI conferences it rose from 29% to 37%; 34.5% of 519 AI-publishing firms published any responsible-AI research.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	A — Who produces knowledge about AI	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Ahmed, Das, Martin & Banerjee, “The Narrow Depth and Breadth of Corporate Responsible AI Research,” arXiv:2405.12193, 2026	source_ids: SRC-SL-AHMED-DAS-MARTIN-BANERJEE-ARXIV-2405-12193
7	SOURCE TYPE	Preprint	classes: PREPRINT
8	INSTITUTIONAL POSITION	Independent academic (University of Arkansas, University of Oregon, University of Notre Dame and Southern Illinois University)	—
9	SCOPE	Peer-reviewed publications and patent citations, 2010–2022	—
10	DESIGN	Classification of publications as responsible AI (keyword and language-model labelling cross-checked); affiliation analysis; patent-citation analysis	—
11	SAMPLE / DATASET	Over 6 million peer-reviewed articles and 32 million patent citations across five datasets	—
12	MODEL / TOOL / VERSION	Gemini used as one of the classifiers	—
13	COMPARATOR	Industry participation at conventional AI conferences	—
14	MAIN RESULT	About 15% or less of responsible-AI publications with an industry co-author, stable over time; industry at responsible-AI conferences 20–23% against 29% to 37% at leading AI conferences; 34.5% of AI-publishing firms engage in responsible-AI research	—
15	INFERENTIAL TARGET	How much firms publish research on the ethics and social effects of AI	—
16	DOES NOT LICENSE	A claim that firms do not influence such research through funding, data or agenda, or about unpublished internal work	—
17	VERIFICATION STATE	CONTENT VERIFIED PREPRINT	state: CONTENT_VERIFIED_PRIMARY · qualifiers: PREPRINT · verified_by: UNKNOWN
18	LIMITATIONS	Read in arXiv version 2 (revised 28 January 2026); the firm denominator is firms holding US AI patents; the main classifier is SciBERT with XGBoost (92.4% on 500 papers); about half of the 50 most-cited responsible-AI conference papers have industry authors, as the authors report; publication counts miss internal and unpublished work; "responsible AI" is defined broadly	—
19	CONTRADICTORY / SUPPORTING SOURCES	LD08-SL-C10; contrast LD08-SL-C01 and LD08-SL-C04	—
20	GEOGRAPHY / LANGUAGE	Global / English	—
21	DISTRIBUTIONAL LEDGER	Not analysed in this claim	—
22	R01 / FIELD-MAP LINKS	LD-08, D3	—
23	WHAT WOULD CHANGE THIS CLAIM?	Counts that include unpublished corporate research or research funded but not authored by firms	—
24	PUBLICATION STATUS	ELIGIBLE WITH PREPRINT QUALIFIER	state: ELIGIBLE · qualifiers: PREPRINT
25	RECORDED DATE	2026-10-16	—

Field 22 references resolved against Field Map v0.2: LD-08 (LIVING_DEBATE); D3 (DOMAIN)

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

Pinned Sources (field 6, version-specific)

“Ahmed, Das, Martin & Banerjee, “The Narrow Depth and Breadth of Corporate Responsible AI Research,” arXiv:2405.12193, 2026” → Ahmed et al. (2026), “The Narrow Depth and Breadth of…” (SRC-SL-AHMED-DAS-MARTIN-BANERJEE-ARXIV-2405-12193--v1.0) — Ahmed, Das, Martin & Banerjee, “The Narrow Depth and Breadth of Corporate Responsible AI Research,” arXiv:2405.12193, 2026; class PREPRINT (explicit public provenance pin)

Cited by Living Debate versions

Who can know about AI? Epistemic dependence and jurisdiction over the field (v0.1) LD-08

Cite this page

SocioLens project. (2026, October 16). Roughly 15% or less of peer-reviewed responsible-AI publications each year had a co-author affiliated with industry; from 2018 to 2022 industry’s participation at responsible-AI conferences stayed between about 20% and 23% while at leading AI conferences it rose from 29% to 37%; 34.5% of 519 AI-publishing firms published any responsible-AI research [Claim LD08-SL-C11, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld08-sl-c11/v1.0/

@misc{sociolens_ld08_sl_c11_v1_0,
  author = {{SocioLens project}},
  title = {Roughly 15\% or less of peer-reviewed responsible-AI publications each year had a co-author affiliated with industry; from 2018 to 2022 industry’s participation at responsible-AI conferences stayed between about 20\% and 23\% while at leading AI conferences it rose from 29\% to 37\%; 34.5\% of 519 AI-publishing firms published any responsible-AI research.},
  year = {2026},
  date = {2026-10-16},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld08-sl-c11/v1.0/}},
  note = {Claim LD08-SL-C11, 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 f4e8bd040102d7edb36be357b1e9a805017e5d9ce3def36ed9359f3cf105676b.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD08-SL-C11 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-16; 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 16 October 2026 to build the LD-08 debate; a new Claim, first version, written from the project's LD-08 source notes, checked against full texts, official web pages or official abstracts. Block “ENTRY 11 — LD08-SL-C11” SHA-256 f08aee7f7e09eb77e3cdf1c8d62cb2d4063f6868c2ff704d71718fbebfe40c99; fixture fixtures/authored/claims/LD08-SL-C11--v1.0.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD08-SL-C11 v1.0); the first version of a new Claim of the LD-08 debate
CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD08-SL-C11 v1.0" (Project Lead (Claude, AI), 2026-10-16); 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 16 October 2026 to build the LD-08 debate; a new Claim, first version, written from the project's LD-08 source notes, checked against full texts, official web pages or official abstracts
FIELD_6_SOURCE_REFERENCE = SRC-SL-AHMED-DAS-MARTIN-BANERJEE-ARXIV-2405-12193--v1.0 — basis: field 6 of ENTRY 11 — LD08-SL-C11 cites "Ahmed, Das, Martin & Banerjee, “The Narrow Depth and Breadth of Corporate Responsible AI Research,” arXiv:2405.12193, 2026"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-AHMED-DAS-MARTIN-BANERJEE-ARXIV-2405-12193--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Ahmed, Das, Martin & Banerjee, “The Narrow Depth and Breadth of Corporate Responsible AI Research,” arXiv:2405.12193, 2026".