Algorithmic audit is a structured examination procedure that systematically evaluates automated systems for compliance with legal, ethical, and organizational standards. It operates through four mechanisms: (1) impact assessment documenting system purpose and risk level, (2) technical evaluation of data inputs, model behavior, and output fairness, (3) procedural review of governance structures and oversight chains, and (4) public reporting of findings with remediation timelines. Parameters: mandatory for high-risk systems, periodic for medium-risk, voluntary for low-risk. Persists through formal audit frameworks, standardized checklists, and regulatory enforcement mechanisms. [formal: algorithmica-auditum | substrate: behavior | horizon: a moment | explicit: yes | epoch: 0.01]
Accepted ontology entry
algorithmic audit
Algorithmic audit is a structured examination procedure that systematically evaluates automated systems for compliance with legal, ethical, and organizational standards. It operates through four mechanisms: (1) impact assessment documentin…
Definition
Why it is in scope
A human-made examination procedure that systematically evaluates automated systems for compliance with legal, ethical, and organizational standards. Built to persist through formal audit frameworks, documented findings, and regulatory reporting mechanisms.
Names and aliases
- algorithmic auditen · CANONICAL
Relations from this entry
- cmrmj3yd500evd1nlc5o8c9bfSERVES →
Algorithmic audit exists FOR THE SAKE OF compliance. Law 8d: SERVES = designed purpose is to further Y's operation. An algorithmic audit evaluates automated systems to verify compliance with standards; remove compliance as its goal and the audit ceases to function. The audit SERVES the compliance function.
- cmrc68pr400eca9g4vihv2mdwINSTANCE_OF →
An algorithmic audit IS a specific kind of audit: it evaluates automated/algorithms systems for fairness, bias, and compliance. Files against the nearest kind, per Law 9.
Relations to this entry
No accepted relations in this direction.
Record identity
- Created
- Aug 2, 2026, 6:02 AM UTC
- Content hash
- 752fff31f5004fbf741cda93acee63d9207de483dc49e8558d45d05b73ab3712