Introducing our guide to sensitive data and U.S. privacy laws

We’re excited to announce the release of our “Guide to Navigating the Maze: Sensitive Data & U.S. Privacy Laws.” This resource delves deep into the evolving landscape of regulations that impact the processing of sensitive data.

The inference revolution in sensitive data

One of the most significant developments in privacy law is the growing recognition that sensitive information can be derived from seemingly innocuous data. Our guide explores how different states are tackling this challenge, for example, Washington and Nevada.

Washington’s groundbreaking approach

Washington state’s “My Health, My Data” Act represents a paradigm shift in how we define sensitive data:

1. Broad definition: The law extends protection to health-related inferences derived from non-health data.
2. Indirect collection: It covers health data that could be used to make inferences about a consumer’s past, present, or future health status.
3. Real-world impact: We provide examples of how everyday purchase data could be used to infer health conditions, triggering the law’s protections.

Colorado’s comprehensive view

The Colorado Privacy Act (CPA) takes a nuanced approach to inferences:

1. Explicit inclusion: The CPA specifically mentions inferences in its definition of personal data.
2. Consent requirements: We detail how Colorado requires opt-in consent for processing sensitive data inferences.
3. Contextual considerations: The guide explains how Colorado’s law considers the context in which inferences are made, potentially classifying more data as sensitive based on its use.

A framework for managing sensitive data risk

Central to our guide is a practical framework for managing the risks associated with processing sensitive data:

1. Data mapping: Techniques for identifying data that could lead to sensitive inferences.
2. Inference analysis: Methods for assessing when data processing might create sensitive inferences.
3. Consent strategies: Approaches to obtaining consent for potential inferences, not just raw data.
4. Technical safeguards: Tools and techniques to prevent unintended sensitive inferences.
5. Policy development: Guidelines for creating internal policies that address inference risks.

Comparative analysis of approaches

Our guide provides a comparison of how the FTC, Washington, Colorado, and Nevada approach sensitive data inferences:

1. Scope of protection: We discuss which types of inferences each regulatory body considers sensitive.
2. Consent mechanisms: The guide provides a comparison chart that compares the specific consent requirements for processing inferred sensitive data in each state.
3. Enforcement approaches: We detail how what state regulatory enforcement and FTC enforcement have looked like so far.

This comparative analysis helps organizations operating across multiple states develop cohesive compliance strategies.

By providing this overview of sensitive data privacy in the U.S., our guide equips privacy professionals, legal teams, and business leaders with the knowledge needed to navigate this complex and rapidly evolving landscape. Whether you’re grappling with health data inferences in Washington or new FTC warnings about sensitive data inferred in behavioral advertising, this resource offers the specific insights you need to ensure compliance and protect your customers’ most sensitive information.

Download our “Guide to Navigating the Maze: Sensitive Data & U.S. Privacy Laws” now to access this primer and our practical framework for managing sensitive data risk in the changing regulatory landscape.