Companion and foundational papers across the portfolio. Aggregated Intelligence pairs directly with “One Number You Can Defend,” which details the AI Posture instrument.
AI Posture
The companion paper to Aggregated Intelligence; details the AI Posture instrument.
Details the AI Posture instrument: one governance score, bounded by the weakest vector, for governance, risk, and compliance leaders. Companion to Aggregated Intelligence.
June 2026
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PAICE.work
A Board-Level Business Case for Measuring AI-Collaboration Reliability
A board-level business case for measuring AI-collaboration reliability: quantifies the operational exposure created by ungoverned human-AI workflows and the cost of running without behavioral evidence.
June 2026
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PAICE.work
Mapping Behavioral Assessment to NIST AI RMF, ISO/IEC 42001, and the EU AI Act
Maps PAICE behavioral assessment to the people-vector requirements inside NIST AI RMF, ISO/IEC 42001, and the EU AI Act. Shows what each framework asks for on the human side of AI-assisted work, and what behavioral evidence satisfies it.
June 2026
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PAICE.work
Why Privacy by Architecture Is What Makes Behavioral AI Measurement Adoptable
Privacy by architecture is the precondition for behavioral AI measurement to be adoptable inside regulated organizations. Behavioral evidence without surveillance: what the design has to refuse to capture, and why that refusal is what unlocks the assessment.
May 2026
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PAICE.work
A Behavioral Skill Framework for Human-AI Performance Improvement
Maps People+AI collaboration measurement to established performance-improvement frameworks from Gilbert, Mager, Rummler-Brache, Thalheimer, Phillips, and Brinkerhoff.
March 2026 · 2026 ISPI Performance Improvement Conference, Nashville, Tennessee
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PAICE.work
Privacy-Preserving Assessment with Cryptographic Integrity
Verifies human-AI collaboration without exposing the collaboration itself. Behavioral observation routed through Trusted Execution Environments on NEAR AI Cloud; assessment results committed as tamper-proof on-chain attestations. Provable privacy with verifiable integrity, in regulated industries where the observation data is high-stakes.
February 2026 · NEARCON 2026, San Francisco
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PAICE.work
A framework for assessing collaboration capability, governance readiness, and risk in AI-assisted systems
Rationale, framework, and architecture behind PAICE: the evidence layer for AI governance, measuring observable behavior rather than self-report.
December 2025 · Originally presented at DevLearn 2025, Las Vegas
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