Claim LD06-SL-C28 (v1.0)
Reviewing 341 academic AI audit studies and non-academic audits, researchers found that only a subset led to accountability outcomes, that many prominent academic audits were collaborations with large technology companies examining their own systems, and that journalistic audits resulted in the most impactful outcomes.
Provenance and status
- Claim type
- ESTIMATE + INTERPRETATION (as printed: “ESTIMATE / INTERPRETATION”)
- 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 rate of audit impact
- Source (field 6, as printed)
- Birhane, Steed, Ojewale, Vecchione & Raji, “AI auditing: The Broken Bus on the Road to AI Accountability,” IEEE SaTML 2024, arXiv:2401.14462
- Source type (field 7)
- PEER_REVIEWED_CONFERENCE_PAPER (as printed: “Peer-reviewed conference paper”)
- Institutional position
- Independent academic
- 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
Pinned version v1.0 (entry LD06-SL-C28--v1.0) — this page never floats to newer evidence.
This pinned version is also the current version.
Pinned Sources (field 6, version-specific)
- “Birhane, Steed, Ojewale, Vecchione & Raji, “AI auditing: The Broken Bus on the Road to AI Accountability,” IEEE SaTML 2024, arXiv:2401.14462” → SRC-SL-BIRHANE-ET-AL-AI-AUDITING-SATML-2024--v1.0 — Birhane, Steed, Ojewale, Vecchione & Raji, “AI auditing: The Broken Bus on the Road to AI Accountability,” IEEE SaTML 2024, arXiv:2401.14462; 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 | LD06-SL-C28 | — |
| 2 | PUBLIC-FACING CLAIM | Reviewing 341 academic AI audit studies and non-academic audits, researchers found that only a subset led to accountability outcomes, that many prominent academic audits were collaborations with large technology companies examining their own systems, and that journalistic audits resulted in the most impactful outcomes. | — |
| 3 | CLAIM TYPE | ESTIMATE / INTERPRETATION | base_types: ESTIMATE, INTERPRETATION |
| 4 | RESEARCH STRAND | C — Evaluation in governance, audits and red-teaming | — |
| 5 | MATURITY | EMERGING | states: EMERGING |
| 6 | SOURCE | Birhane, Steed, Ojewale, Vecchione & Raji, “AI auditing: The Broken Bus on the Road to AI Accountability,” IEEE SaTML 2024, arXiv:2401.14462 | source_ids: SRC-SL-BIRHANE-ET-AL-AI-AUDITING-SATML-2024 |
| 7 | SOURCE TYPE | Peer-reviewed conference paper | classes: PEER_REVIEWED_CONFERENCE_PAPER |
| 8 | INSTITUTIONAL POSITION | Independent academic | — |
| 9 | SCOPE | AI audit studies and their outcomes | — |
| 10 | DESIGN | Taxonomy and survey of audit studies | — |
| 11 | SAMPLE / DATASET | 341 academic audit studies plus non-academic audits | — |
| 12 | MODEL / TOOL / VERSION | Not applicable | — |
| 13 | COMPARATOR | Academic versus journalistic and civil-society audits | — |
| 14 | MAIN RESULT | Only a subset of audits translate into accountability; company-collaborative audits of companies’ own systems common; critics warn of audit washing | — |
| 15 | INFERENTIAL TARGET | Whether audits hold AI developers to account | — |
| 16 | DOES NOT LICENSE | A rate of audit impact | — |
| 17 | VERIFICATION STATE | CONTENT VERIFIED | state: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN |
| 18 | LIMITATIONS | Pre-2024 audits, mostly not of generative AI | — |
| 19 | CONTRADICTORY / SUPPORTING SOURCES | Consistent with LD06-SL-C26 | — |
| 20 | GEOGRAPHY / LANGUAGE | Not checked / English | — |
| 21 | DISTRIBUTIONAL LEDGER | Not analysed in this claim | — |
| 22 | R01 / FIELD-MAP LINKS | LD-06, D4b | — |
| 23 | WHAT WOULD CHANGE THIS CLAIM? | Outcome tracking of audits under mandated regimes | — |
| 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-06 (LIVING_DEBATE); D4b (SUB_AREA)
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 154444800909f2886e24b109f440ca9b58ebf3fc92b47eccc215c259cc8e38de.
Repository-authored inputs (not Drive exports)
- SocioLens claim — LD06-SL-C28 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-06 debate; a new Claim, first version, written from the project's LD-06 source notes, checked against full texts or official abstracts. Block “ENTRY 28 — LD06-SL-C28” SHA-256
659fb0bc637c9069300d1a0b7d03c8d22d286257072fc7cd6db1ac6905a494d6; fixturefixtures/authored/claims/LD06-SL-C28--v1.0.
Builder decisions (not Drive data)
- VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD06-SL-C28 v1.0); the first version of a new Claim of the LD-06 debate
- CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD06-SL-C28 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-06 debate; a new Claim, first version, written from the project's LD-06 source notes, checked against full texts or official abstracts
- FIELD_6_SOURCE_REFERENCE = SRC-SL-BIRHANE-ET-AL-AI-AUDITING-SATML-2024--v1.0 — basis: field 6 of ENTRY 28 — LD06-SL-C28 cites "Birhane, Steed, Ojewale, Vecchione & Raji, “AI auditing: The Broken Bus on the Road to AI Accountability,” IEEE SaTML 2024, arXiv:2401.14462"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
- SOURCE_PROVENANCE_PIN = SRC-SL-BIRHANE-ET-AL-AI-AUDITING-SATML-2024--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Birhane, Steed, Ojewale, Vecchione & Raji, “AI auditing: The Broken Bus on the Road to AI Accountability,” IEEE SaTML 2024, arXiv:2401.14462".