Definitions[]
Artificial intelligence[]
Auditability is
| “ | the ability of an AI system to undergo the assessment of the system's algorithms, data and design processes. This does not necessarily imply that information about business models and Intellectual Property related to the AI system must always be openly available. Ensuring traceability and logging mechanisms from the early design phase of the AI system can help enabling the system's auditability.[1] | ” |
General[]
Auditability is "[t]he degree to which transactions can be traced and audited through a system."[2]
Auditability means
| “ | that it is possible to establish whether a system is functioning properly and, thereafter, that it has worked properly.[3]. | ” |
| “ | [t]he capability of supporting a systematic, independent and documented process for obtaining audit evidence and evaluating it objectively to determine the extent to which audit criteria are fulfilled.[4] | ” |
Overview[]
"One aspect of auditability is to provide sufficient knowledge about the system and its structure, functions, controls, etc. by means of appropriate documentation. Another important aspect of auditability is to make visible all integrity-related modifications to the system and its data. Logging data should make it possible to answer the questions 'who?', 'what?' and 'when?'"[5]
References[]
- ↑ Ethics Guidelines for Trustworthy AI, at 36.
- ↑ Internet Banking: Comptroller's Handbook, at 64.
- ↑ Report on Electronic Money, Annex 1, Glossary, at 37.
- ↑ Cloud Service Level Agreement Standardisation Guidelines, at 10.
- ↑ Id.