Data resources may be subject to deterioration over the medium and long term. In addition, the business, operational, IT, and regulatory environments and stakeholder pressures will change over time. These processes may jeopardize data access or data quality and lead to unacceptable risks.
The AI System Owner should ensure that the organization designs processes for regular comprehensive reviews of the AI system resources (Data health checks) to ensure that the data-related risks are acceptable and align with the organization’s values and risk tolerance.
The AI System Owner should ensure that the organization defines, documents, and entrenches workflows and technical interfaces to review
1) AI system and algorithm data sources,
1) data preprocessing practices,
1) data quality, and
2) data ontology, inferences, and proxies.