WEKID™ is evolving from a framework into an industry ecosystem for evaluating knowledge maturity and governing AI Decision Authority. The Community program brings together practitioners, domain experts, researchers, and public-sector leaders to refine domain profiles, contribute documented failure cases, advance research, and strengthen the evidence behind both models. We are assembling a founding cohort now.
Where you can contribute
The closer to the core, the higher the bar to change it.
Frameworks become standards when an ecosystem helps test, refine, and steward them. WEKID's Epistemic Maturity and Decision Authority models are intended to evolve through disciplined evidence, domain experience, and transparent governance. Community is the structured way to contribute to that evolution.
For individuals: practitioners, researchers, academics, auditors, and government participants who want to contribute to the framework, its domain profiles, and the body of evidence behind it. You can take part without belonging to a partner organization.
Ways to take partFor organizations: consulting firms, technology providers, training companies, and assessment firms that license, implement, and build WEKID-enabled solutions. WEKID enables partners rather than competing with them.
Visit PartnersThe rings beside the page title are these three surfaces: the closer a contribution sits to the core of the framework, the higher the bar to change it. The Epistemic Maturity Model evaluates what an intelligent system knows; the Decision Authority Model governs what it may be trusted to decide or do. The core stays stable; calibration and the evidence corpus are where most of the work happens.
The core includes the five WEKID layers — Wisdom, Experience, Knowledge, Information, and Data — the hierarchical dependency rules, the Epistemic Maturity Model, the Decision Authority Model, and the principle that authority delegation is subject to explicit governance gates. This is the framework's constitution. It is published and held stable so others can teach and build on it.
Governed by the Standards Council · changes are rare and deliberate.
Scoring weights, evidence requirements, maturity thresholds, authority boundaries, gate conditions, decision-matrix outcomes, and domain-specific risk profiles. This is where industry adds the most value — a Healthcare profile may require higher epistemic-maturity thresholds, mandatory human review, and non-delegable decision categories. A Financial Services profile may impose stricter source-fidelity, explainability, and authority limits for trading or lending decisions. The result is a versioned profile such as WEKID for Healthcare.
Governed by domain working groups, ratified by the Standards Council.
Documented AI failure cases, examples of knowledge-maturity breakdowns, instances of misdelegated decision authority, regulatory crosswalks (NIST AI RMF, ISO/IEC 42001, EU AI Act), scored outputs, and reusable control patterns. The lowest bar and the highest volume — every entry is attributed to its contributor.
Governed by contributors and working groups · curated, not gatekept.
Pick the one that fits how you want to engage. Founding participants help define the ones still forming.
Submit AI failure cases, scored examples, best practices, and control patterns to the evidence corpus. The fastest way to get on the contributor registry and earn recognition.
Contribute a caseHelp build a domain profile with a small group of practitioners. The first group is forming in a regulated domain where the evidence is strongest — healthcare or financial services. Founding members shape the charter.
Join a working groupContribute whitepapers, studies, regulatory mappings, and WEKID layer mappings. The relationship among knowledge quality, human reliance, machine expertise, delegated authority, and responsible AI governance is an active research area. We want that scholarship connected to the continued development of both WEKID models.
Submit researchThe RFC process, the founding Standards Council, and the path to neutral stewardship. If you lead AI governance in an enterprise, agency, or university, this is where framework decisions are made.
How it worksEvery change moves through one pipeline, modeled on open standards practice. The rigor scales with the surface: a corpus entry clears quickly; a calibration profile takes a comment window and a Council vote; a core change is rare. Each proposal gets a stable identifier — for example, WEKID-RFC-001.
Any participant opens a Request for Contribution describing the change, the surface it affects, and the evidence behind it.
The proposal is sorted to a surface — corpus, calibration, or core — which sets the review path and the bar it has to meet.
Domain experts assess the proposal against the evidence and the framework, and recommend accept, revise, or decline.
Calibration and core proposals open for a comment window so the wider community can weigh in before a decision.
The Standards Council ratifies, returns for revision, or declines — with the rationale recorded against the RFC.
Accepted changes ship in a numbered release. Certification tracks named releases so credentials stay aligned with the framework.
The corpus holds 45 publicly documented AI failure cases, each mapped to the WEKID layer where the knowledge failure emerged, the relevant authority or governance failure, and the Decision Authority outcome the framework would recommend. A few are below; the full, searchable catalogue masks every organization so the focus stays on the governance lesson, with named detail released in the Executive Brief.
The Community program is new, but it builds on real, published work. These are the assets it starts from.
WEKID is stewarded today by WEKID LLC, which maintains the framework, the certification program, and the WEKID™ trademark. A founding Standards Council and the first domain working group are forming now.
Help define the working groups, the RFC register, and the first domain profiles.