Privacy, Data Brokers, and Law Enforcement: How US Data Flows From Phones to Protests

Summary

In this Science Friday episode, host Flora Lichtman sits down with Laura Moy to unpack how our digital footprints—smartphones, license plates, social media—are gathered, sold, and potentially used by government agencies and private companies. The conversation covers the role of data brokers, facial recognition in the field, opt out limitations, and the state of privacy laws in the United States. Moy also shares her personal privacy practices and explains why she believes robust, society-wide policy changes are needed to protect vulnerable communities from surveillance and misuse.

• How everyday data is created and shared across multiple actors, including immigration enforcement.
• Why location data can be inferred even with location services turned off, via advertising networks and other pathways.
• The tension between state privacy laws and potential federal preemption, and the influence of advertisers on policy debates.
• Practical privacy strategies and the broader call for legislative solutions to privacy protections.

Overview

The podcast examines the current data privacy landscape in the United States, focusing on how private data is collected, bought, and used by government agencies and private entities. It features Laura Moy, an associate professor of law at Georgetown Law, who has testified before Congress on privacy laws and data broker practices. Moy argues that the US has a fragmented and evolving data ecosystem that enables rapid, cross-source data linking, which can be used for purposes ranging from targeting advertisements to enforcing immigration policies.

Data Ecosystem and the Reach of Private Data

The discussion emphasizes that virtually every modern activity generates data. Smartphones are active collectors of location, app usage, and communication metadata, while everyday infrastructure such as license plates and cameras creates location traces. Moy notes that even private actions on social media can yield insights to platforms and, ultimately, to the government. A central concern is data brokers who aggregate information from diverse sources, repackage it, and sell access to advertisers, marketers, or government clients. This creates a vast, interconnected data network that makes it feasible to assemble detailed portraits of individuals and their networks.

Facial Recognition and the Field

Moy describes facial recognition as a powerful, currently deployed technology by agencies like ICE. She highlights ICE's Mobile Fortify app as an example of mass identification in the field, while acknowledging its error-prone nature. The implication is that the government can deploy powerful analytics to identify people in real time, using data drawn from private and public sources alike.

How Data is Collected and Shared

The host and Moy trace the flow of data from mobile devices to data brokers and beyond. When people use their phones, they share information with their service providers, manufacturers, social media services, advertisers, and more. Moy stresses that location data can travel through less obvious channels, such as mobile advertising networks, which collect and repackage location information to target content or identify users for enforcement purposes.

Cross-Source Linkage and Palantir’s Role

A key point is the ability to link disparate data sources using platforms like Palantir, which can integrate data from advertising networks, location data brokers, driver’s license databases, and more. Moy explains how such integration enables rapid, scalable profiling and can be leveraged for law enforcement or deportation efforts. The example underscores the shift from siloed datasets to a connected data fabric that magnifies privacy risks for individuals and their close networks.

Laws, Policy, and the Federal Landscape

The conversation turns to privacy law, noting that Fourth Amendment protections exist but that comprehensive federal privacy legislation has not passed. Moy describes how state privacy laws have begun to emerge, but these may be undermined by federal preemption, and why many industry players push back against stronger privacy rules that would curtail access to location and other sensitive data. The discussion also covers the political economy of privacy, including how the advertising ecosystem values detailed personal data and how that shapes policy debates.

Personal Privacy Protocols and the Path Forward

Moy shares her personal privacy practices, including opting out of certain data-sharing and using encrypted communications (for example, Signal). She emphasizes that individual actions alone cannot solve the problem; rather, systemic privacy protections are needed. Moy argues for legislation and policy reforms to shield vulnerable populations, such as immigrant and mixed-status communities, who may be disproportionately affected by data-based surveillance.

Takeaways

The podcast leaves listeners with a clearer view of the data ecosystem, the limits of opt-out tactics, and the urgent need for stronger privacy protections. It highlights the tension between consumer privacy rights and the commercial incentives that drive data collection, and it calls for informed public engagement to push for meaningful privacy legislation.