Nine judges carry two votes’ worth of information. Run the same task across many AI platforms and the agreement that comes back may be a shared blind spot rather than a finding. HAIA-CAIPR is the governance framework for orchestrating that comparison so it produces evidence instead of confidence. It sets nine invariants, five configuration variables that each name what they cost, and a named human who reads the raw returns before anyone decides.
HAIA-CAIPR
The Governance Layer Perplexity’s Model Council Needs
Perplexity built the right architecture for multi-model AI: dispatch three frontier models in parallel and compare their outputs. What the product does not have is governance over the synthesizer that combines those outputs before any human reads them. This case study maps the gap, proposes four published open-source governance components as the overlay, and identifies why Perplexity’s own engineering culture already practices the checkpoint pattern the synthesizer needs.
The Inevitable Is a Choice: Testing Mo Gawdat’s FACE RIPS Forecast Across Two Interviews Against the Governance Architecture That Could Make It Optional
Mo Gawdat predicts 12 to 15 years of dystopia before AI becomes benevolent enough to save humanity. He says the transit corridor is inevitable. This paper tests every Gawdat claim against the published governance architecture that could prevent it. The dystopia is contingent, not foreordained, because the infrastructure to stop it already exists. The decade ahead will be shaped by which prediction the public frame adopts.
Empire of Evidence: Testing Karen Hao’s Claims Against the Governance Infrastructure They Require
A Governance Practitioner’s Examination of the Diary of a CEO Interview and Empire of AI A journalist with engineering training spent eight years investigating the AI industry and concluded that the major companies operate as empires. A governance practitioner who builds open-source infrastructure for the same industry watched the two-hour interview where she made that […]
Open Letter to the UN Scientific Advisory Board on AI Deception
From Basil C. Puglisi, MPAHuman-AI Collaboration Strategist | basilpuglisi.comMarch 23, 2026 To the Members of the Scientific Advisory Board of the United Nations: The Brief of the Scientific Advisory Board on AI Deception correctly identifies a problem that practitioners working across multiple AI platforms encounter daily. Sycophancy and related deceptive behaviors are no longer theoretical […]
HAIA-RECCLIN: Reasoning and Dispatch
Nine AI platforms reviewed the same paper and eight agreed. Agreement proved nothing, because platforms trained on the same data carry the same blind spots. HAIA-RECCLIN is the ten-field format that makes any platform cite its sources and hand the decision back, and the dispatch method that assigns seven roles by proven strength.