Tech
Do Smart Monitors Track You? What Buyers Should Know
Smart monitors can collect usage data through built-in operating systems, apps, advertising services, and features such as automatic content recognition. But tracking varies by model, and not every internet-connected display collects the same information.
Before buying one, check what the specific monitor collects, whether tracking features can be disabled, and whether data may be shared with advertisers or other third parties.
Some smart monitors can send ACR-related data
Automatic content recognition, or ACR, identifies content appearing on a display. It can be used for recommendations, audience measurement, and advertising.
RTINGS included a Samsung Odyssey S32DG80 smart monitor in its smart-device tracking tests. With ACR consent enabled, researchers observed regular traffic to Samsung services associated with content recognition. Disabling the relevant setting stopped or sharply reduced that traffic.
The result confirms that ACR-related tracking can occur on a smart monitor, but it should not be generalized to every model.
Ars Technica reports that LG and Samsung smart monitors use the same broad operating-system families found on their smart TVs. The publication also found that privacy policies covering monitors from LG, Samsung, and Acer allow some collected information to be shared with advertisers.
A smart monitor can also run streaming services and other third-party apps without a PC attached. Those apps may have their own data-collection practices on top of anything the monitor platform collects.
Tracking can mean different things
ACR is not the same as recording conversations through a microphone.
A Google Assistant privacy case involved allegations that unintended voice activation caused private conversations to be recorded. ACR instead analyzes content appearing on a display.
Connected devices can process other sensitive information too. Amazon’s Ring facial-recognition feature identifies familiar visitors, for example. Buyers should therefore look at the specific type of data a device processes rather than treating all tracking as the same behavior.
What to check before buying a smart monitor
Treat a smart monitor as an internet-connected device, not just a screen. Before buying, check whether it:
- Uses ACR or another viewing-information feature.
- Enables tracking or personalized advertising during setup.
- Lets users disable those features later.
- Requires an account to access core functions.
- Runs third-party apps with separate privacy policies.
- Explains what information may be shared with advertisers.
Security matters alongside privacy. The US Cyber Trust Mark was created to help buyers evaluate security practices on eligible connected consumer devices, including information about software support and updates.
If you only need a display for a connected computer, a conventional monitor avoids the built-in app, account, and advertising layer of a smart model.
For a smart monitor, check the exact model’s privacy settings during setup and again after installation. The useful question is not simply whether smart monitors track users, but what the model collects and whether you can turn that collection off.
Also read: T-Mobile’s T-Life privacy settings demonstrate how data collection, advertising preferences, and opt-out controls can exist in separate parts of a connected service.
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Tech
Rivian’s CFO is leaving the company
Rivian’s chief financial officer Claire McDonough is resigning her position at the end of October, the company announced in a regulatory filing Thursday.
The company said McDonough is stepping down to “pursue a new opportunity and relocate to the East Coast to be closer to her family.” Rivian said her resignation is “not the result of any disagreement.” The company is already searching for a replacement, and vice president of finance Derek Mulvey will serve as interim CFO once McDonough leaves her post.
Her departure comes as Rivian takes on some of its biggest projects to date, including scaling up production and sales of its R2 SUV, which started shipping to customers this summer.
This story is developing…
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Tech
Bluesky adds an ‘algorithmic opt-out’ feature for those who don’t want to go viral
After adding support for longer videos just yesterday, open social network Bluesky on Thursday introduced a new algorithmic opt-out feature that allows users to stop their posts from appearing in the app’s main Discover feed.
That algorithmic feed can currently surface any post on Bluesky’s network, as posts on the network are public by default.
To be clear, this latest change isn’t a way to make posts private — Bluesky is still working on rolling out support for private data at the protocol level. Instead, the feature simply makes a user’s public posts less discoverable to people outside their existing personal network.
The company says it created the feature because not everyone using its social media site wants to go viral. Sometimes, people just want to post for their followers without having their words exposed to larger crowds.
To opt out of having posts shown in the Discover feed, users can toggle on a new option in the app’s Privacy and Security settings. The change can take up to an hour to fully take effect, the company says.

It’s also worth noting that Bluesky’s implementation of the feature extends beyond its own app.
Instead of just being a setting that applies only within Bluesky, the preference is recorded at the account level. That means the choice travels with the user, even if they’re posting from another app that is powered by the same underlying protocol that Bluesky uses, AT Proto.
However, while those other apps have access to this information, they still have to choose to whether to respect it.
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Tech
Buried in Meta’s $18B settlement is a legal pass on kids’ data
In addition to paying out up to $18 billion and adding child safety measures, Meta’s settlement agreement with attorneys general from 29 states includes an interesting provision: the states have agreed not to sue Meta under existing child safety laws over its retention and use of children’s data.
That permission is being granted for the limited purpose of training and testing Meta’s age-assurance model and includes guardrails, but it’s a curious policy decision to make in a case centered on child safety, and one that could be difficult to properly enforce.
As specified in the settlement agreement, Meta must develop, train, and begin testing a model designed to detect which users on Meta’s platforms are under the age of 13. This must be done within a year of the document’s effective date. (While the agreement doesn’t specify that the model has to be AI-based, Meta’s current age-detection tools are powered by AI technology.)
Under U.S. child safety law, COPPA (the Children’s Online Privacy Protection Act), typically requires that websites and apps limit the collection and retention of children’s personal information. Meta’s settlement agreement says that Meta shouldn’t need to violate COPPA to train or implement its age-assurance models. However, the agreement also says that the state AGs have agreed “fully, finally, and forever” not to bring any past, present or future COPPA claims — or claims under similar state laws — related to Meta’s use of children’s data.
The agreement makes clear that Meta can’t use data from users under age 13 for ad targeting, marketing, or algorithmic optimization.
Meta’s request for legal protection, and the state AGs’ willingness to grant it, isn’t unreasonable, says Philip N. Yannella, a partner at law firm Blank Rome and co-chair of its Privacy, Security & Data Protection practice. “These kinds of data minimization guardrails are pretty typical for privacy compliance: e.g., verifying compliance with deletion requests,” he said, though he noted a caveat: COPPA is a federal law primarily enforced by the FTC, not the states, so it’s unclear whether the FTC, which isn’t a party to this settlement, has separately agreed to the same compromise.
It can be difficult for companies to keep data technically and organizationally isolated from the rest of their systems. Yet Meta is being asked to do just that — to isolate its understanding of children’s behavior signals and other data and use it solely for detecting and removing under-13 users. Fortunately, an independent auditor will be involved in monitoring Meta’s compliance with the settlement so we don’t only have to rely on Meta’s word.
Policing this limitation could be complicated. The data could hypothetically feed into other Meta systems over time, or could raise questions over whether the data, signals, or insights derived from it are being used elsewhere within the company. What’s not clear from the agreement is what data Meta will retain for training the model, how much behavioral information that may include, or how long it will retain the data. We also don’t know how these models will change in the future as Meta meets the settlement’s terms.
Barring state AGs from raising COPPA or similar state-law claims over this use of children’s data in the future could complicate the legal avenues states can pursue if questions arise around how Meta is using the data.
That doesn’t prevent them from pursuing legal claims, notes Joshua Wurtzel, a partner at Schlam Stone & Dolan LLP. “If Meta uses the data outside those lines, the release and covenant not to sue don’t apply,” he said. But those legal disputes could still be complicated, since they’d hinge on whether Meta’s use of the data fell within the settlement’s terms.
Peter Jackson, a Data & IP attorney at Greenberg Glusker LLP, agrees, saying the carve-out here could “disincentivize future enforcement actions.”
“The Settlement Agreement’s age-assurance measures bear all the hallmarks of a heavy, and perhaps hasty, negotiation,” he says.
The decision also touches on a broader question that’s been coming up across the AI industry lately, especially as more AI agents are being developed to help consumers with various tasks. The systems often require significant access to users’ personal data to work well. Similarly, Meta may need deep insight into children’s use of social media use in order to identify which accounts belong to young people.
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