From Consumption to Reflection: Designing Human-AI Relations for Stable Reasoning
2026-06-11T07:23:53Z•b42e4e5b3ffc17b141972bd3b46a2190b0391ec3f4da6610cf22f32416c255ca
AI agentsAI ethicsEeVAFairness-to-ActionLLMsMoReBenchRRIRelational Reflective Intelligencealgorithmic fairnessarms controlbehavioral biometricscarbon accountingenvironmental impactethical deliberationexperimentation standardsgender biasgenerative searchhuman-AI interactioninference-time governancemilitary AImoral reasoningpreregistrationpublic healthregulation (AIA,RAR)shadow banning
What happened
Collection of arXiv CS/AI papers (June 11, 2026) covering governance, evaluation, and societal impacts of LLMs and agentic AI. Key contributions include: Relational Reflective Intelligence (RRI) — an inference-time, auditable layer (Rose‑Frame, Architect's Pen, workflow) to embed reflection into human‑AI reasoning; a Fairness‑to‑Action framework diagnosing the research‑practice gap for algorithmic fairness in public health; a method and tools for measuring computational and environmental costs of LLMs in AIED; analysis of generative search and shadow‑banning harms with legal/regulatory options
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cy
- Record identifier
- b42e4e5b3ffc17b141972bd3b46a2190b0391ec3f4da6610cf22f32416c255ca
- Enrichment time
- 2026-06-11T07:23:53Z
- AI-assisted enrichment
- Yes
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