In a 2022 field scan of algorithmic auditors (survey of 152 and 10 interviews), only 7% said their audit process used a standardized framework, 80% had recommended changes to AI systems that were not implemented, and half of third-party auditors reported lacking access, against none of the first-party auditors.

SocioLens project,

Claim LD06-SL-C26 (v1.0)

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with qualifiers: vintage
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: Current practice for frontier-model evaluation, which postdates the scan
Limitations: Self-selected respondents; before generative AI and the EU code; only 56 of the 152 respondents had worked on an audit (12 first-, 16 second- and 11 third-party; roles could overlap), so the access figures describe a handful of people (the third-party figure rests on 11 auditors)
Source (as cited): Costanza-Chock, Harvey, Raji, Czernuszenko & Buolamwini, “Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem,” FAccT 2022, arXiv:2310.02521
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

Costanza-Chock, Harvey, Raji, Czernuszenko & Buolamwini, “Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem,” FAccT 2022, arXiv:2310.02521 (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 (VINTAGE) (as printed: “ELIGIBLE WITH VINTAGE QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY
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	LD06-SL-C26	—
2	PUBLIC-FACING CLAIM	In a 2022 field scan of algorithmic auditors (survey of 152 and 10 interviews), only 7% said their audit process used a standardized framework, 80% had recommended changes to AI systems that were not implemented, and half of third-party auditors reported lacking access, against none of the first-party auditors.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	C — Evaluation in governance, audits and red-teaming	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Costanza-Chock, Harvey, Raji, Czernuszenko & Buolamwini, “Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem,” FAccT 2022, arXiv:2310.02521	source_ids: SRC-SL-COSTANZA-CHOCK-ET-AL-FACCT-2022
7	SOURCE TYPE	Peer-reviewed conference paper	classes: PEER_REVIEWED_CONFERENCE_PAPER
8	INSTITUTIONAL POSITION	Not checked	—
9	SCOPE	The algorithmic auditing field, 2021–2022	—
10	DESIGN	Field scan: catalogue of auditors, anonymous survey and interviews	—
11	SAMPLE / DATASET	438 individuals and 189 organizations catalogued; 152 survey respondents; 10 interviews	—
12	MODEL / TOOL / VERSION	Not applicable	—
13	COMPARATOR	First-, second- and third-party auditors	—
14	MAIN RESULT	7% standardized framework; 80% recommendations not implemented; 65% say auditees will not commit to fix problems; access lacking for 58% of second-party and 50% of third-party auditors; 75% call audit regulation not or barely present; 95% favour mandated audits	—
15	INFERENTIAL TARGET	Whether audits produce accountability	—
16	DOES NOT LICENSE	Current practice for frontier-model evaluation, which postdates the scan	—
17	VERIFICATION STATE	CONTENT VERIFIED	state: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18	LIMITATIONS	Self-selected respondents; before generative AI and the EU code; only 56 of the 152 respondents had worked on an audit (12 first-, 16 second- and 11 third-party; roles could overlap), so the access figures describe a handful of people (the third-party figure rests on 11 auditors)	—
19	CONTRADICTORY / SUPPORTING SOURCES	Consistent with LD06-SL-C28	—
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?	A repeat scan under mandated audit regimes	—
24	PUBLICATION STATUS	ELIGIBLE WITH VINTAGE QUALIFIER	state: ELIGIBLE · qualifiers: VINTAGE
25	RECORDED DATE	2026-10-15	—

Field 22 references resolved against Field Map v0.2: LD-06 (LIVING_DEBATE); D4b (SUB_AREA)

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

Pinned Sources (field 6, version-specific)

“Costanza-Chock, Harvey, Raji, Czernuszenko & Buolamwini, “Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem,” FAccT 2022, arXiv:2310.02521” → Costanza-Chock et al. (2022), “Who Audits the Auditors?…” (SRC-SL-COSTANZA-CHOCK-ET-AL-FACCT-2022--v1.0) — Costanza-Chock, Harvey, Raji, Czernuszenko & Buolamwini, “Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem,” FAccT 2022, arXiv:2310.02521; class PEER_REVIEWED_CONFERENCE_PAPER (explicit public provenance pin)

Cited by Living Debate versions

The evaluation apparatus: Can benchmarks, leaderboards and audits carry the weight placed on them? (v0.1) LD-06

Cite this page

SocioLens project. (2026, October 15). In a 2022 field scan of algorithmic auditors (survey of 152 and 10 interviews), only 7% said their audit process used a standardized framework, 80% had recommended changes to AI systems that were not implemented, and half of third-party auditors reported lacking access, against none of the first-party auditors [Claim LD06-SL-C26, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld06-sl-c26/v1.0/

@misc{sociolens_ld06_sl_c26_v1_0,
  author = {{SocioLens project}},
  title = {In a 2022 field scan of algorithmic auditors (survey of 152 and 10 interviews), only 7\% said their audit process used a standardized framework, 80\% had recommended changes to AI systems that were not implemented, and half of third-party auditors reported lacking access, against none of the first-party auditors.},
  year = {2026},
  date = {2026-10-15},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld06-sl-c26/v1.0/}},
  note = {Claim LD06-SL-C26, 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 217afc1b1553c203d86378876ca2591ca6da18f943f27142d2fa26114bea006e.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD06-SL-C26 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 26 — LD06-SL-C26” SHA-256 740e17f1d5332e0c8f9951b9db7c7ba68b93e7ccf022254147de79f20c49d69b; fixture fixtures/authored/claims/LD06-SL-C26--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-C26 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-C26 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-COSTANZA-CHOCK-ET-AL-FACCT-2022--v1.0 — basis: field 6 of ENTRY 26 — LD06-SL-C26 cites "Costanza-Chock, Harvey, Raji, Czernuszenko & Buolamwini, “Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem,” FAccT 2022, arXiv:2310.02521"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-COSTANZA-CHOCK-ET-AL-FACCT-2022--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Costanza-Chock, Harvey, Raji, Czernuszenko & Buolamwini, “Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem,” FAccT 2022, arXiv:2310.02521".