Latest Posts

Q2 closes open-weight scoring, a buyer-facing content arc, security hardening, and a full look back at the quarter that built the evidence layer.

Three letters arrive from three regulators in three different professions. Each one names a single human being. Not the firm, not the AI vendor, not the committee that approved the tool. That is the accountability gap.

A practical framework for documenting AI-assisted decisions so you can answer "how was this decision made?" when regulators, auditors, or courts ask

What happens when AI collaboration verification fails in regulated industries, from malpractice exposure to regulatory fines to license risk

A practical framework for enterprise buyers building internal support for behavioral AI collaboration assessment and risk reduction

Pricing goes public with no sales gate, the site finishes going trilingual, PAICE wires into the obligation graph, and an outside finding backs the collaboration thesis.

OpenRouter found that a panel of models beats the single best one. That is the PAICE thesis at the model layer, and why we built Turnfile and our newest protocol: Tokenese

PAICE measures human behavior in AI collaboration. ObligationFirst represents legal obligations in a form agents can reason about. Together, the two layers connect what a person did in a real assessment to which specific obligation, under which statute, was at stake. A worked example, end to end.

The entire PAICE.work website is now available in Spanish, French, and Brazilian Portuguese. Three languages graduate from beta to fully supported.

Every PAICE pricing tier explained: what each one covers, who it is for, and why individual scores never appear in organizational reports.

Scoring benchmark bake-off across four models, three paper spotlights, full Fable 5 security & documentation audit, and multilingual site completed beta exit.

Four teams are managing four slices of AI risk right now—and none of them are talking to each other. The maturity gap isn't the distance to the top of the curve. It's the distance between you and knowing where you are on it.

New paper: why privacy by architecture is what makes behavioral AI measurement adoptable. The answer to the objection that stops deployment.

New paper: mapping PAICE behavioral assessment to NIST AI RMF, ISO/IEC 42001, and the EU AI Act. The governance evidence your audit file is missing.

New paper: a board-level business case for measuring AI-collaboration reliability. The exposure your dashboards cannot see, priced through real rulings.

Three new papers launched under /papers, the PAICE dimensions series completed, EU Article 50 transparency consultation submitted, and agent metadata hardened across the platform.

Three teams present three solid reports to the board. One question ends the meeting in silence. The posture gap is the distance between "we're doing a lot" and "we can tell you exactly where we stand."

Understanding PAICE's Performance dimension and why communication clarity is the foundation of AI collaboration — but not the ceiling

I submitted comments on the EU's draft Article 50 transparency rules. The gap I kept circling: a label can't reach an agent, survive time, or become a skill.

Two new papers from PAICE.work PBC address the same gap: measuring what People+AI collaboration actually produces, at the organization and governance level.