Responsible AIAI Bias and Fairness Assessment
AI bias and fairness assessment evaluates how data, labels, objectives, design choices, and deployment conditions can create uneven errors or harms across groups.
Third-party AI riskAI Procurement and Contract Controls
AI procurement and contract controls convert governance, security, privacy, performance, audit, incident, and exit requirements into enforceable supplier obligations.
AI transparencyAI Transparency Notices
AI transparency notices tell people when AI is used, what it does, what information it relies on, important limitations, and how to seek review or correction.
AI third-party riskAI Vendor Change Notification
AI vendor change notification requires providers to disclose material changes that could alter risk, performance, data handling, compliance, or system behavior.
API securityAPI-Based Data Ingestion Security
API-based data ingestion security validates the source, identity, authorization, format, rate, and integrity of data accepted through programmatic interfaces.
Privacy engineeringAnonymization and De-identification
Anonymization and de-identification reduce the ability to associate released or shared data with a specific person, while accounting for linkage and re-identification risk.