The recent lawsuits brought by Texas Attorney General Ken Paxton against multiple smart-TV manufacturers should reignite conversations about potential consumer surveillance by businesses. The cases allege that automated content recognition (ACR) technology embedded in smart TVs enabled manufacturers to monitor what consumers watched in real time, including content displayed through cable boxes and HDMI-connected devices, and monetize that data without meaningful notice or consent. Such data collection can lead to privacy invasion with potentially identifiable markers for consumers’ location as well. 

Obviously, no business would like its consumers to feel unsafe under potential surveillance threats. However, sometimes technologies or features embedded in the products can easily cross that line. What the Texas lawsuits highlight is that businesses need to prepare against the risks of unintentionally engaging in surveillance-like practices. 

How Surveillance Sneaks In 

Features designed for analytics, personalization, or monetization can quietly evolve into continuous monitoring of user behavior. Because these capabilities are frequently embedded, automated, or bundled with core functionality, businesses may fail to recognize when ordinary data collection begins to resemble surveillance. Here are some common risks that businesses might stumble upon: 

• Always-on or passive data collection: Technologies that run continuously in the background, without active user engagement, can create persistent visibility into consumer behavior over time. 
• Overbroad data capture. Collecting data beyond what is necessary to deliver a product or service, such as monitoring external devices or secondary interactions, increases the risk of surveillance-like outcomes. 
• Bundled or unclear consent. When consent for expansive data practices is tied to basic product use or buried in onboarding flows, users may not fully understand the scope of monitoring. 
• Third-party integrations and embedded tools. Vendors, SDKs, or embedded technologies may collect or infer data in ways the primary business does not fully control or anticipate. 
• Data reuse and monetization. Repurposing behavioral data for advertising, analytics, or resale can amplify privacy risks, particularly when users were not clearly informed. 

Privacy Without the Guesswork

Preventing surveillance-like practices is difficult for businesses to manage on their own. Data flows span multiple systems, teams, and vendors, and new features are often deployed faster than privacy reviews can keep up. As products evolve, data uses can drift from their original purpose, making it challenging to maintain visibility, consistency, and control. Without centralized oversight, even well-intentioned organizations can lose track of how consumer data is actually being collected and used. Here are some steps businesses can take: 

• Map and monitor data collection comprehensively. Businesses need clear visibility into what data is collected, how it flows across systems, and which features or integrations enable ongoing monitoring. 
• Limit collection to what is necessary. Applying data minimization principles helps reduce the risk that analytics or product features turn into continuous behavioral observation. 
• Separate essential functionality from optional data uses. Consumers should not be required to accept expansive monitoring to access core services. 
• Continuously assess embedded and third-party technologies. Regular reviews can uncover hidden or expanding data collection that may introduce surveillance risks. 
• Adopt scalable privacy management tools. Platforms like Truyo help centralize data privacy compliance, consent management, and risk assessments. Organizations consistently identify and mitigate surveillance-related concerns as products and regulations evolve. 

Avoiding Surveillance by Design 

The Texas smart-TV lawsuits serve as a reminder that, as automated data collection rises, the line between functionality and monitoring can blur quickly. For businesses, respecting privacy means proactively designing products and operations to avoid surveillance-like practices and not just reacting when regulators intervene. Organizations that invest in visibility, restraint, and scalable privacy governance will be better positioned to protect consumer trust and meet regulatory expectations in an increasingly scrutinized data environment.