Decency Meter
Decency Meter is the public-facing signal layer built on top of DBaD decision traces. It connects everyday moral intuitions to a larger effort around structured review, AI governance, human decision oversight, and interpretable advisory systems.
Decency Meter is the public advisory signal layer; DBaD is the underlying decision trace protocol and governance model.
DBaD governs decisions across time, not just at the moment they are made.
Built for the public, researchers, governance teams, and implementation partners exploring practical AI oversight.
64% say “Act with transparency”
Decency Meter is the public signal layer built on top of DBaD decision traces. What starts as a short civility survey feeds a broader effort to make public judgment signals more transparent, testable, and useful for AI governance.
As AI systems make or influence real-world decisions, organizations need more than policy documents. They need operational models that help determine whether a proposed action should proceed, be modified, or be blocked.
DBaD is being developed as one such model: interpretable enough to explain, compact enough to test, and practical enough to sit beside real systems.
DBaD began as a compact rule about decency. It has evolved into a formal, testable model designed to support structured decision review, AI governance, and transparent trace visibility.
The five measurable dimensions are harm, consent, intent, proportionality, and transparency.
DBaD is being developed to make proposed actions reviewable, constrain trust propagation, and keep decision traces auditable over time.
| DBaD factor | AI governance equivalent |
|---|---|
| Harm | Risk, safety, and impact scoring |
| Consent | User autonomy, permissions, and data rights |
| Intent | Objective alignment and misuse prevention |
| Proportionality | Fairness, policy fit, and appropriate response |
| Transparency | Explainability, auditability, and reviewability |
AI deployment is accelerating across infrastructure, healthcare, finance, defense, education, and public services. Policy language alone is not enough. Organizations need operational models for structured decision review.
DBaD is an attempt to provide a simple, interpretable protocol for that purpose, bridging public moral intuitions and executable review logic.
DBaD is being developed as an open, testable decision-trace protocol for AI and human decision systems. We welcome interest from researchers, institutions, implementation partners, and organizations exploring practical AI governance.
Decency Meter is the public signal layer. The DBaD portal holds the executive summary, methodology, papers, demo evaluator, and API surfaces for the underlying decision-trace protocol.
For the public: take the quick test and compare the live pulse.
For researchers: use the full survey, papers, and methodology.
For enterprises: start with the DBaD protocol site and demo surfaces.
No new public submissions in the last 7 days yet.
“DBaD sure sounds like a reasonable path!”
— AnonymousTransparency lowers harm by exposing assumptions early. It turns private guesses into public, testable claims.
In the DBaD model, transparency is not fluff. It changes accountability across every other pillar.
Use the quick test for a lightweight public signal, the full survey for deeper research input, and the demo evaluator when you want to see the advisory and protocol framing directly.
This host is the front door. The technical framework, methodology, and papers live on the ethics portal.
Copy and paste this snippet into your site where you want the meter to appear.
Decency Meter is the public signal layer. DBaD is the underlying decision-trace protocol and governance framework. Use the DBaD portal for the longer argument: executive summary, methodology, papers, evaluator demo, API docs, version compare, and scenario intake all live there.