Taming the Text Giants: Governing Language Models for Secure, Compliant AI

Organizations can govern user prompts and model outputs in large language models using data access governance and security solutions that integrate with model libraries. This allows for real-time enforcement of data privacy, regulatory compliance, and access control policies while preserving the benefits of generative AI.

Summary

• Challenges:
  • Securing language models while preserving data privacy, compliance, and access control.
  • Governing user prompts and model outputs across diverse applications and models.
  • Real-time processing of unstructured text data at scale.
• Solution:
  • Data access governance and security solution embedded within model libraries.
  • Scans prompts and outputs for policy violations and applies access control.
  • Leverages natural language understanding to interpret context and intent.
  • Operates in real-time with low latency.
• Benefits:
  • Reduces risks associated with generative AI adoption.
  • Broadens the applicability of language models to more use cases.
  • Centralizes governance for all models within an organization.

Additional notes:

• The solution scales to handle small snippets of text (hundreds of characters), not large volumes.
• The system identifies and redacts sensitive data like PII (Personally Identifiable Information).
• Role-based and attribute-based access controls can be integrated with the governance engine.