Striking the Balance: Safeguarding Customer Privacy While Empowering Employees

Tuesday, September 12, 2023 - 9:00 am9:15 am

Emily Greene, Moveworks


Discover practical solutions for preserving customer privacy while empowering employees in the era of Large Language Models (LLMs). This talk discusses how to balance different employee use cases with privacy-protecting data handling solutions. We explore scenarios such as debugging, analytics, and machine learning, highlighting the unique challenges of LLMs to customer privacy. Drawing from real-world experiences at Moveworks, we showcase two effective solutions: automated data masking for de-identification and just-in-time, role-based access provisioning. By examining tradeoffs and sharing lessons learned, we demonstrate how LLMs can meet a business' goals while still preserving customer privacy. Join us to gain valuable insights into striking the right balance between safeguarding customer privacy and enabling employee productivity through broadly applicable privacy solutions.

Emily Greene, Moveworks

Emily Greene is a Security & Privacy Engineer at Moveworks, where she leads their data privacy and security. Emily specializes in the security and privacy of artificial intelligence (AI) systems. Her expertise extends to privacy-preserving machine learning (ML) techniques, such as evaluating ML models for privacy leaks. Emily brings valuable insights from her time at Amazon, where she spent 5 years owning application security for Alexa AI, building end-to-end security review and data protection solutions. Emily is dedicated to enabling forward-thinking organizations to prioritize customer privacy when using AI.

@conference {290877,
author = {Emily Greene},
title = {Striking the Balance: Safeguarding Customer Privacy While Empowering Employees},
year = {2023},
address = {Santa Clara, CA},
publisher = {USENIX Association},
month = sep

Presentation Video