Big AI's Regulatory Capture: Mapping Industry Interference and Government Complicity
2026-05-11T07:23:50Z•11a8962f9b3c3ad32d07c47b93f0b94ac1e5cff62094179f1553f36699677e3b
agent-based-modelingai-policyai-regulationalgorithmic-fairnessattribute-inferencechatbotscounterfactual-fairnessdeceptive-designdifferential-privacyeducation-aifederated-learninggenerative-aigovernanceprivacyredistrictingregulatory-capturevertical-federated-learning
What happened
Collection of 11 recent arXiv papers (CS: cybersec/governance/AI) covering AI regulatory capture, perceived AI consciousness, AI adoption in universities, vertical federated learning fairness with a differentially private selective counterfactual consistency (SCC-VFL) method, multi-level agent-based climate governance modeling, classroom studies of AI-assisted learning, critique of chatbot-dominant interfaces, redistricting optimization via composite-move Tabu search, and analyses of deception/banal manipulation in generative AI. Security- and policy-relevant items include SCC-VFL (privacy-by‑
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cy
- Record identifier
- 11a8962f9b3c3ad32d07c47b93f0b94ac1e5cff62094179f1553f36699677e3b
- Enrichment time
- 2026-05-11T07:23:50Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.