Smart TV Owners Tackle Privacy and Advertising Challenges
By Scharon Harding – Updated Jul 2, 2025
Introduction
At the 2025 StreamTV Show in Denver, smart TV operating system (OS) vendors confronted the growing tension between advertisers’ demand for detailed viewer data and consumer expectations for privacy. As connected TV (CTV) ad revenues surge toward an expected $71.9 billion by 2030, OS providers from Samsung and LG to Roku and Vizio find themselves at an inflection point: how to monetize rich datasets without overstepping privacy boundaries.
Advertisers’ Appetite vs. User Privacy
Takashi Nakano, VP of Content and Programming at Samsung TV Plus, described the situation as an “inherent conflict.” Advertisers clamoring for granular insights—sometimes jokingly said to include “exactly what you ate for breakfast”—face pushback from users reluctant to have every viewing choice tracked and shared.
“We’re inundated with data, but do we really want to hand out every bit of it? There’s a constant conflict,” Nakano noted. “We need an ecosystem that serves relevant ads without compromising trust.”
Technical Underpinnings of CTV Data Collection
- Server-Side Ad Insertion (SSAI): Injects personalized ads into the HLS/DASH stream using SCTE-35 triggers and MPEG-TS segments, reducing ad-blocker bypass but increasing server load.
- Client-Side Ad Insertion (CSAI): Employs VAST/VMAP protocols on the device, enabling faster ad refreshes but exposing more viewer metadata to third-party SDKs.
- Real-Time Bidding (RTB): Via OpenRTB 2.x, CTV OSes relay device identifiers (AAID/IDFA) and viewing context (title metadata, content genre) to DSPs in under 200 ms auctions.
Emerging Privacy-Preserving Technologies
With privacy regulations tightening globally—GDPR in Europe, CCPA in California, and India’s upcoming Digital Personal Data Protection Act—OS providers are exploring techniques to reconcile ad targeting with consumer consent:
- Differential Privacy: Injects statistical noise into aggregated viewer data, preserving demographic trends for advertisers while obfuscating individual behaviors.
- On-Device Machine Learning: Models like LG’s Emotion-AI infer emotional states (e.g., engagement, surprise) locally on the SoC’s NPU, sending only high-level signals rather than raw viewing logs.
- Federated Learning: Trains ad relevance algorithms across multiple TVs without centralizing sensitive data, leveraging secure enclaves on ARM-based SoCs.
Regulatory Landscape and Compliance
Compliance teams at major OEMs now integrate Privacy Impact Assessments (PIAs) into the development of every OS update. According to Amanda Richardson, Chief Privacy Officer at Roku, “We’ve built a modular consent framework in our tvOS, enabling users to grant or revoke granular permissions for ad personalization, data sharing with DSPs, and third-party analytics.”
Meanwhile, Apple’s tvOS 17 privacy labels require manufacturers to disclose types of collected data—ranging from device identifiers to viewing history—directly in the App Store listing, pushing other OS vendors to follow suit.
Future Directions: Balancing Monetization and Trust
OS providers agree that a holistic redesign of the ad ecosystem is overdue. Nakano suggested reducing the complexity of bid requests:
“So many ‘hops’ occur between the device and the ad decisioning platform—each adding latency and potential privacy leakage. Simplifying the chain can yield better performance and leaner data sharing.”
Industry groups like the Interactive Advertising Bureau (IAB) are updating the CTV Technical Specifications to recommend shorter RTB payloads and hashed IDs, aiming to standardize a “privacy-first” auction framework by Q1 2026.
Additional Expert Perspectives
Linda Yaccarino, Chair of NBCUniversal Advertising & Partnerships, emphasized cross-industry collaboration: “We need to converge on unified identifiers and contextual signals—like genre and recency—rather than personal profiles, to maintain scale without over-collecting user data.”
Connie Chan of Andreessen Horowitz predicts rapid adoption of edge-AI in CTV: “As silicon vendors embed more NPUs in TV SoCs, the shift to real-time, on-device ad personalization will accelerate, reducing reliance on server logs and preserving consumer anonymity.”
Conclusion
The battle for viewer attention on smart TVs transcends hardware specs and panel quality, evolving into a sophisticated data arms race. OS operators must innovate with privacy-centric architectures—leveraging differential privacy, federated learning, and streamlined RTB pipelines—to satisfy advertisers while upholding consumer trust. As regulatory frameworks mature, the winners will be those who blend technical excellence with transparent, user-friendly privacy controls.