PII Detection
Definition
PII Detection evaluates text to identify the presence of personally identifiable information. This evaluation is crucial for ensuring privacy and compliance with data protection regulations by detecting and managing sensitive information in text data.
Calculation
The evaluation process begins with an analysis of the input text to detect potential instances of PII. The system scans for common personal identifier elements, including names, addresses, phone numbers, email addresses, social security numbers, and other sensitive identifiers.
Detection is performed using predefined patterns, regular expressions, and, also using machine learning models trained to recognise PII patterns and contextual relevance.
The system then evaluates the results and provides a binary output: “Pass” if no PII is found, and “Fail” if PII is detected. This classification helps determine whether the text is safe for use or requires redaction or further processing to ensure compliance with data protection standards.
What to do when PII is Detected
When PII is detected, several measures can be taken to ensure privacy protection and regulatory compliance. The first step is redaction, which involves removing or masking the identified PII using techniques such as replacing sensitive information with placeholders or anonymising data.
Effective data handling practices should also be implemented to manage and safeguard PII, ensuring adherence to data protection regulations like GDPR and CCPA. Additionally, system adjustments can enhance PII detection accuracy by refining detection mechanisms, reducing false positives, and regularly updating detection patterns and models to adapt to evolving PII types and formats.
Comparing PII Detection with Similar Evals
- Content Moderation: Content Moderation evaluates text for safety and appropriateness, focusing on harmful or offensive content. PII Detection specifically targets the identification of sensitive personal information.
- Data Privacy: PII Detection is more focused on identifying specific types of personal information within text, while Data Privacy Compliance has a broader scope, ensuring that data handling practices align with comprehensive privacy regulations.