Discussion at the intersection of AI and data privacy and recommend best practices to achieve higher efficiency while safeguarding sensitive data

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Large Language Models (LLMs) are transforming business operations through AI-driven insights and efficiency. However, leveraging pretrained LLMs like GPT and Claude raises critical data privacy concerns, particularly when handling Personally Identifiable Information (PII) or Protected Health Information (PHI). This webinar panel will explore the intersection of AI and data privacy, providing actionable best practices for businesses to maximize LLM efficiency while ensuring robust data protection. We will address the challenges of using LLM API tools with sensitive corporate data and offer strategies to mitigate risks.

• Participants will be able to:
  
  
  • Understand the data privacy challenges associated with using LLM APIs.
  • Identify potential risks of exposing PII and PHI on LLM platforms.
  • Learn best practices for safeguarding sensitive data in LLM applications.
  • Explore strategies for balancing AI efficiency with data protection.
  • Understand how to properly use LLMs in a corporate setting.

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Introduction: The Impact of LLMs - Case scenarios

Data Privacy Challenges in LLM Applications

Identifying and Mitigating Risks: PII and PHI

Best Practices for Secure LLM Implementation

Question and Answers

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