Accuracy
The output correctly reflects the underlying data, model, and domain rules.
Failure mode: Wrong outputs at scale without detection.
Decision Integrity
The architectural property of digital systems that produce correct, contextualized, explainable, auditable, and risk-proportionate decision outputs — preserving the distinction between data, model, estimate, and interpretation.
Formal definition
Decision Integrity = Accuracy × Contextualization × Explainability × Auditability × Robustness × GovernanceEach factor is necessary but not sufficient. A system can be accurate but not auditable, or explainable but ungoverned. Decision Integrity requires all six dimensions to be present and measurable.
The six dimensions
Contextualization
The output is conditioned on the relevant operational context (jurisdiction, time, entity type).
Failure mode: Correct formula, wrong context — structurally invalid outputs.
Explainability
The logic path from input to output can be traced, described, and communicated.
Failure mode: Decisions that cannot be audited, contested, or understood.
Auditability
Every output is traceable to its inputs, model version, rules, and timestamp.
Failure mode: Regulatory exposure; no forensic path for disputes.
Robustness
The system behaves correctly under edge cases, adversarial inputs, and domain boundary conditions.
Failure mode: Silent failures at the edges of valid input space.
Governance
Changes to logic, data, or models follow a controlled process with versioning and approval gates.
Failure mode: Regressions introduced without accountability.
Where Decision Integrity applies in Fidamen's work
Kernel Business OS
Decision logic is formalized as versioned computational kernels with explicit input/output contracts.
Production workflows
QA gates enforce integrity checks before any output is published or executed.
Release policy
MAJOR changes (logic-breaking) require formal review; PATCH changes are logged and tested.
Research
All published frameworks explicitly declare assumptions, scope, and failure conditions.
Relationship to Research and Systems
Decision Integrity is not an abstract ideal — it is an architectural requirement. Fidamen's research corpus investigates the conditions under which organizations and systems produce (or fail to produce) decision-grade outputs. The systems we build are designed to implement these requirements operationally.