TechBay.News

By Michael Phillips | TechBay.News

Texas law enforcement’s heavy investment in AI-driven surveillance software is drawing new scrutiny—not just for privacy implications, but for what it reveals about how governments adopt complex technology with limited transparency and weak performance metrics.

A January 13 investigation outlines how agencies across Texas have spent millions on Tangles, a platform that aggregates open-, deep-, and dark-web data and analyzes historical cellphone location information purchased from data brokers. The most contentious feature enables large-scale geofencing without a warrant, relying on commercially sourced data rather than telecom records.

A Procurement Story as Much as a Privacy Story

From a technology governance standpoint, the red flags are familiar:

• Opaque capabilities: Agencies struggle to explain precisely how the system is used.
• Unclear ROI: Officials concede the tool has rarely—if ever—been central to prosecutions.
• Vendor-driven expansion: Contracts ballooned from emergency purchases into multi-year, multi-million-dollar agreements.
• Limited auditability: Records requests are denied, and usage is rarely documented in court filings.

This mirrors broader problems in government tech adoption, where AI systems are procured faster than policies governing their use.

Data Brokers: The Weakest Link in the Stack

The platform’s reliance on commercial location data underscores a larger issue in the tech ecosystem: the largely unregulated data broker market. Location data harvested from everyday apps is sold, resold, and repurposed—creating powerful surveillance capabilities without the controls typically applied to government data collection.

From a systems perspective, this is not just a civil liberties concern. It is a data integrity, security, and governance problem.

Why Tech Policy Should Care

AI tools used by government are not neutral. They encode assumptions, create incentives, and shift power. When deployed without transparency, they increase institutional risk—legal, reputational, and financial.

Texas’s experience offers a cautionary tale for other states and agencies racing to adopt AI policing tools: innovation without governance is not modernization; it is technical debt at scale.

TechBayNews takeaway: the question is no longer whether governments will use AI, but whether they will build the guardrails before—not after—the systems are entrenched.