Claim LD08-SL-C04 (v1.0)
In 100 highly cited NeurIPS and ICML papers, the share with ties to large technology firms (author affiliation or funding) rose from 21% in 2008/09 to 66% in 2018/19, and the share with any corporate tie from 45% to 79%; 15% of the papers justified their work by a societal need and 1% discussed potential negative effects.
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
- A claim about research on AI’s social effects, or that corporate ties caused the values found
- Source (field 6, as printed)
- Birhane, Kalluri, Card, Agnew, Dotan & Bao, “The Values Encoded in Machine Learning Research,” FAccT 2022
- Source type (field 7)
- PEER_REVIEWED_CONFERENCE_PAPER (as printed: “Peer-reviewed conference paper”)
- Institutional position
- Independent academic (with a Mozilla Foundation fellow)
- Maturity (claim evidence / publication maturity)
- EMERGING (as printed: “EMERGING”)
- Recorded date
- 2026-10-16
- 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--LD08-SL-C04.
Pinned Sources (field 6, version-specific)
- “Birhane, Kalluri, Card, Agnew, Dotan & Bao, “The Values Encoded in Machine Learning Research,” FAccT 2022” → SRC-SL-BIRHANE-ET-AL-VALUES-FACCT-2022--v1.0 — Birhane, Kalluri, Card, Agnew, Dotan & Bao, “The Values Encoded in Machine Learning Research,” FAccT 2022; class PEER_REVIEWED_CONFERENCE_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 | LD08-SL-C04 | — |
| 2 | PUBLIC-FACING CLAIM | In 100 highly cited NeurIPS and ICML papers, the share with ties to large technology firms (author affiliation or funding) rose from 21% in 2008/09 to 66% in 2018/19, and the share with any corporate tie from 45% to 79%; 15% of the papers justified their work by a societal need and 1% discussed potential negative effects. | — |
| 3 | CLAIM TYPE | ESTIMATE | base_types: ESTIMATE |
| 4 | RESEARCH STRAND | A — Who produces knowledge about AI | — |
| 5 | MATURITY | EMERGING | states: EMERGING |
| 6 | SOURCE | Birhane, Kalluri, Card, Agnew, Dotan & Bao, “The Values Encoded in Machine Learning Research,” FAccT 2022 | source_ids: SRC-SL-BIRHANE-ET-AL-VALUES-FACCT-2022 |
| 7 | SOURCE TYPE | Peer-reviewed conference paper | classes: PEER_REVIEWED_CONFERENCE_PAPER |
| 8 | INSTITUTIONAL POSITION | Independent academic (with a Mozilla Foundation fellow) | — |
| 9 | SCOPE | Highly cited machine-learning papers from two leading venues, 2008/09 and 2018/19 | — |
| 10 | DESIGN | Line-by-line annotation of paper text for values, plus coding of author affiliations and funding acknowledgements | — |
| 11 | SAMPLE / DATASET | 100 papers (50 per period) | — |
| 12 | MODEL / TOOL / VERSION | Not applicable | — |
| 13 | COMPARATOR | The earlier period (2008/09) | — |
| 14 | MAIN RESULT | Big Tech ties 21% to 66%; any corporate tie 45% to 79%; university ties fell to 81%; 15% cite a societal need; 1% discuss negative potential | — |
| 15 | INFERENTIAL TARGET | Corporate presence in, and the stated values of, influential machine-learning research | — |
| 16 | DOES NOT LICENSE | A claim about research on AI’s social effects, or that corporate ties caused the values found | — |
| 17 | VERIFICATION STATE | CONTENT VERIFIED | state: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN |
| 18 | LIMITATIONS | Read in arXiv version 2; small sample of the most cited papers, which may favour industry work; machine-learning research, not research on AI’s social effects | — |
| 19 | CONTRADICTORY / SUPPORTING SOURCES | LD08-SL-C05; industry papers use social-impact language about as often as academic ones: LD08-SL-C09 | — |
| 20 | GEOGRAPHY / LANGUAGE | Global / English | — |
| 21 | DISTRIBUTIONAL LEDGER | 80% of the university-affiliated papers came from elite universities | — |
| 22 | R01 / FIELD-MAP LINKS | LD-08, D3 | — |
| 23 | WHAT WOULD CHANGE THIS CLAIM? | A larger, venue-wide sample, or the same coding for research on AI’s social effects | — |
| 24 | PUBLICATION STATUS | ELIGIBLE WITH QUALIFIER | state: ELIGIBLE · qualifiers: QUALIFIED |
| 25 | RECORDED DATE | 2026-10-16 | — |
Field 22 references resolved against Field Map v0.2: LD-08 (LIVING_DEBATE); D3 (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 207851bac9758873949e67de26e4e643c2b0564cd8b309cb36b51cf3056ce1ee.
Repository-authored inputs (not Drive exports)
- SocioLens claim — LD08-SL-C04 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 04 — LD08-SL-C04” SHA-256
f8c662fa8e09ca77422c531946e9257c62d6d8e4a4d295fdaf98ff72602733f6; fixturefixtures/authored/claims/LD08-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 — LD08-SL-C04 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-C04 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-BIRHANE-ET-AL-VALUES-FACCT-2022--v1.0 — basis: field 6 of ENTRY 04 — LD08-SL-C04 cites "Birhane, Kalluri, Card, Agnew, Dotan & Bao, “The Values Encoded in Machine Learning Research,” FAccT 2022"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
- SOURCE_PROVENANCE_PIN = SRC-SL-BIRHANE-ET-AL-VALUES-FACCT-2022--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Birhane, Kalluri, Card, Agnew, Dotan & Bao, “The Values Encoded in Machine Learning Research,” FAccT 2022".