Protecting sensitive data in AI apps

About this Video

• Video Title: Protecting sensitive data in AI apps
• Channel: Google Cloud Tech
• Speakers: Martin Ommander, Aron Eidelman
• Duration: 00:08:50

Introduction

This video discusses methods for protecting sensitive data within AI applications built on Google Cloud. The speakers address common concerns about data privacy and demonstrate how Google Cloud's Data Loss Prevention (DLP) API can safeguard data across three key data flows: data input to the AI model, application logging, and user responses.

Key Takeaways

• Google Cloud does not use customer data to train its own models. Customer data remains under customer control.
• Three main data flows require protection in AI apps: data to the AI model, application logging, and responses to the user.
• The Data Loss Prevention (DLP) API is a single solution for protecting all three data flows. It can redact sensitive data from text and images and allows for customizable filtering of data types.
• The DLP API can be applied to various stages of data processing: filtering data before it reaches the model, redacting sensitive information from logs, and filtering responses to users. The approach can be tailored to the specific application's needs and security requirements.
• The DLP API can also inspect and classify data stored in various locations: including Cloud Storage, BigQuery, and even data sources outside Google Cloud.