Trustworthy AI in AGISystem2 is built on four pillars: determinism, auditability, fairness, and validation. Every reasoning step is reproducible, logged, bias-controlled, and consistency-checked—making the system suitable for compliance-sensitive domains.
The four pillars of trustworthiness in AGISystem2: determinism ensures reproducibility, auditability provides traceability, fairness controls bias, and validation guarantees consistency. These work together on every query.
| Feature | What It Provides | Architecture Component |
|---|---|---|
| Determinism | Same input always produces same output | MathEngine (Int8) |
| Audit Trail | Complete provenance for every decision | AuditLog |
| Bias Control | Protected attributes can be masked | BiasController |
| Validation | Consistency checks before commit | ValidationEngine |
| Explainability | Reasoning steps are interpretable | Reasoner |
AGISystem2 uses Int8 arithmetic with saturating operations—no floating-point rounding errors:
// Same query, same context → same result, always
const result1 = reasoner.ask("Dog IS_A ?", context);
const result2 = reasoner.ask("Dog IS_A ?", context);
assert(result1.equals(result2)); // Always true
// Unlike neural networks where:
// - Different runs may give different results
// - Floating-point accumulation varies
// - Hardware affects output
| Domain | Requirement | AGISystem2 Solution |
|---|---|---|
| Healthcare | Explainable diagnoses | Audit trail + reasoning chain |
| Finance | Fair lending decisions | Veil of ignorance + bias audits |
| Legal | Reproducible case analysis | Determinism + query replay |
| HR | Non-discriminatory hiring | Protected dimension masks |