The surveillance infrastructure tracking American drivers has grown far more sophisticated than most people realize. What began as simple plate-logging technology has evolved into AI systems capable of identifying faces, flagging unusual travel patterns and building detailed movement profiles — all without the knowledge of the people being watched. Companies such as Flock Safety now operate in communities across 49 states, and their data is accessible to thousands of law enforcement agencies, including federal immigration enforcement, according to civil liberties groups. State legislatures are among the few institutions actively writing rules around how these systems can be used, and what those rules say (or don’t say) have real consequences for your privacy on the road.

That raises a large question: What are the best privacy protection laws? I wanted to provide more details for anyone wondering what to support or what their state is currently doing. One challenge is that every state is different, and there’s no clear guide on what privacy laws work and which have flaws.

I spoke to Chad Marlow, senior policy counsel and lead for the American Civil Liberties Union’s surveillance work, to find the best examples. These laws are making the biggest difference in our privacy. 

“Collective action, rather than individual action, is required,” Marlow told me. “I would caution that while Flock is the most problematic ALPR company in America, there are many other ALPR companies, like Axon and Motorola, that present serious privacy risks, so switching from Flock to Axon/Motorola ALPRs at best may constitute minimal harm reduction, but it is far from a solution.”

Which of today’s laws are a better solution? This is a “throw everything against the wall and see what sticks” situation. Let’s talk about what’s sticking. 

The best laws on the books for limiting new surveillance technology

Current privacy laws focus on two recent capabilities of local law enforcement: ALPRs, or automatic license plate readers, that can identify and track cars, and drone surveillance equipped with AI cameras. Security companies, such as Flock, are also starting to offer more traditional cameras that can provide live views and track people from the ground.

With AI features like Flock’s “Freeform” technology that let police enter any type of search they like to see what cameras bring up, these are powerful tools, and new legislation is required to address them. Let’s go over several categories of laws that make a difference. 

Laws restricting the use of AI detection features

Some of the broadest laws tackle what AI cameras are allowed to do at all. These laws don’t specifically target ALPR cams or drones, but they do limit the searches that police and commercial entities can make. 

Illinois has long been the best example of these privacy laws with its BIPA, or Biometric Information Privacy Act that protects personal ID like fingerprints and facial data, and requires written consent if a company wants to use them. 

That law is so far-reaching that certain camera features like Google Nest’s Familiar Faces technology is completely blocked in Illinois, along with some of Flock’s recognition features. Cities can pass similar legislation, too: Travel to Portland, Oregon and you’ll find that certain facial recognition features won’t work there, either. 

The one issue with laws like these is that they don’t include license plate and vehicle data, at least not yet. That information, which is closely tied to your name and address, needs to be protected by additional legislation or added onto existing biometric laws. So far, the former is more common: California is the only state I’ve noticed that now includes ALPR data as “personal information” for its privacy laws. 

Laws that ban what details police cameras can see

States are also passing new types of laws that allow the use of ALPR cameras, but ban those cameras from being able to record and pass along personal information, or at least make that information confidential in some way — including Florida and New Hampshire. 

These laws can ban cameras from seeing details like the people inside a car, for example, limiting them only to a license plate. Companies like Flock advertise the ability of their cameras to notice other descriptive details above a vehicle such as bumper stickers or roof racks, so laws like these can hamper the use of such AI detection. 

In a related note, states may add stricter authorization steps for police cameras. For example, rules that require the police chief to sign off on any search using ALPRs make it less likely that the data is misused when collected.

Laws that limit the use of ALPRs to certain police activities

A number of states have created laws that allow the use of license plate and AI cameras, but only for specific purposes, such as ongoing investigations involving a murder or kidnapping. Some states have very strict limits on how these cameras can be used, while others have much broader descriptions. 

Laws like these keep ALPR cameras out of the hands of businesses, HOAs and similar organizations, who would otherwise be able to contract with companies like Flock Safety. They may also block cameras from being used in certain areas, such as on public highways. 

Laws requiring that any data collected by cameras be deleted within a certain timeframe

One of the most effective surveillance laws for protecting privacy is the requirement to delete any footage caught by these cameras unless its actively being used in a confirmed investigation. That means police can’t make unauthorized searches or share that data with outside organizations after a certain time.

Laws like these also prevent police departments from creating long-term files about people they want to keep an eye on and note their routines and behaviors. As Marlow said, “The idea of keeping a location dossier on every single person just in case one of us turns out to be a criminal is just about the most un-American approach to privacy I can imagine.”

New Hampshire has the most stringent laws here, requiring the collected data to be deleted within 3 minutes if not used, a far shorter timeline than most, but one the ACLU agrees with.

“For states that want a little more time to see if captured ALPR data is relevant to an ongoing investigation, keeping the data for a few days is sufficient,” Marlow told me. “Some states, like Washington and Virginia, recently adopted 21-day limits, which is the very outermost acceptable limit.” Marlow warned that the longer police keep this data, the easier it is to build patterns of life “that can eviscerate individual privacy.” 

I’ve also seen states with laws that require ALPR data deleted after several years, but at that point it’s largely useless, as the data could easily be compiled and moved to other platforms by then. 

Laws banning police from sharing data outside of the state

States like Virginia and Illinois have passed laws making it illegal to share any ALPR or related data outside the state, including with federal agencies. These laws are typically targeted at the Department of Homeland Security and ICE, which (along with the FBI and other agencies) have been known to request data from local police Flock cameras or be granted backdoor access to Flock search systems. 

Laws that keep data from going out of state prevent that — as long as there are ways to track data transmission and enforce the law — which is difficult. “Ideally, no data should be shared outside the collecting agency without a warrant,” Marlow said, “But some states have chosen to prohibit data sharing outside of the state, which is better than nothing, and does limit some risks.”

States like Minnesota have also added requirements to make ALPR searches public so that citizens can check what searches the police have made, an important step for accountability that’s still rare for this technology.

Laws requiring state approval and office certifications for any ALPR camera

There’s another option to manage these high-powered cameras — subject them to an approval process by the state before contracts and installation. The tricky part is that approval process can look completely different depending on the state. 

In Texas, for example, a license is required but these seem relatively easy to obtain — although not everyone has followed that law. 

Vermont, however, enacted a series of laws to create a lengthy approval process to ensure ALPR cameras could only be used in certain circumstances and that the data was tightly controlled. This approval process was so thorough that local organizations decided to pass altogether: By 2025, no law enforcement agency in the state was using ALPR cams.

Laws requiring warrants before launching surveillance drones

In the past year, I’ve seen a new concern on the rise in neighborhoods in addition to ALPR cameras. There are now surveillance drones equipped with cams that can recognize vehicles or human features (beards, hats, shirt colors and so on) and follow people automatically. Those have required a further set of laws to address. 

States including Alaska, Idaho, Utah and Texas have laws specifically requiring a warrant before drones are used for surveillance. Technically, this should prevent the use of Flock’s automatic drone launches for things like gunshot detection or 911 calls, but local law enforcement appears to have found ways around these laws due to exemptions and other loopholes.

It’s worth noting my state nearly nuked its drone warrant requirements with new legislation in 2025, which ultimately failed to pass, a reminder that the rules are always up for change.

Keep an eye on the legislation in your state

New laws are subject to frequent challenges, including companies such as Flock or local police departments outright ignoring them. That requires extensive legal action to address and a buildup of case law that can take years, not mention methods of investigation and enforcement by the state that may not currently exist. 

Proposed legislation can also be subject to many changes, even if it’s likely to be passed, so the details can shift. That means if you want to see specific bans or privacy requirements in your state, you should track ongoing legislation as it passes through approval stages, and continue to contact your senators and representatives.

If you’re not sure what’s in a law, it’s important to read it carefully or find analysis by a legal expert to learn more. Many lesser laws I didn’t include on this list have lots of carveouts, exceptions and latitude in how surveillance cameras can be used, rendering them fangless for privacy purposes.

But that’s not all you can do. I’ve also seen the rise of advocacy initiatives like The Plate Project from the Institute of Justice that you can join, contribute to or just read up on to do more. And don’t forget about the local level — voicing concerns at a city council forum could help limit surveillance contracts before they even begin. 

For more information, check out if your landlord can watch you with a security camera, and if it’s legal to record audio and video in your own home. 

BNP Paribas, Deutsche Bank and JPMorgan have the mandate. Maturities run from three years to 25 years.

The trade follows Alphabet’s record Swiss issuance in February and Amazon’s $37bn dollar deal in March, and is the latest demonstration that hyperscalers are now multi-currency borrowers.

Amazon is preparing its first-ever Swiss franc bond issuance, Bloomberg reported on Monday, in a six-tranche deal that stretches across three-, five-, seven-, ten-, fifteen- and twenty-five-year maturities.

BNP Paribas, Deutsche Bank, and JPMorgan have been mandated to run the books. Amazon has not yet disclosed the size of the trade; pricing is expected later this week.

The trade is the most visible sign yet that the largest US hyperscalers have crossed a threshold in their funding strategy. A US dollar bond programme is no longer sufficient on its own.

The capital required to fund AI infrastructure has become large enough that Big Tech treasurers are now actively diversifying into euros, sterling, and Swiss francs, often within the same multi-currency programme, to broaden their investor base and to capture pockets of demand that the US market alone cannot satisfy at acceptable rates.

Amazon’s path into the Swiss market follows a well-trodden one. Alphabet sold more than CHF 2.75bn (roughly $3.6bn) across five maturities in February as part of a multi-currency drive that included sterling, euro, and a rare 100-year US dollar bond.

That Swiss tranche was the biggest-ever corporate bond sale in the Swiss market. Caterpillar and Thermo Fisher Scientific have both used the same market in the past eighteen months.

What Amazon adds to that list is scale: with roughly $200bn of capex planned for 2026 according to CEO Andy Jassy’s recent comments, the company’s incremental funding requirement runs to multiple tens of billions per year.

Six tranches across the Swiss curve is consistent with a treasurer trying to lock in long-duration capacity rather than to fund a specific project.

On 10 March, Amazon raised about $37bn across eleven tranches in the US bond market. That trade was followed shortly afterwards by a EUR 14.5bn deal split across multiple tenors.

The combined dollar-and-euro raise was, at the time, the largest single funding event in the company’s history. Demand on the dollar trade was reported to have run roughly four times the size sold.

Pricing on the long end came inside Treasury yields by margins that would have been inconceivable for the company a decade ago.

The Swiss franc issuance now extends that pattern into a third currency and a market structure where issuance costs typically run materially below dollar equivalents for similarly-rated borrowers.

The arithmetic behind the issuance is straightforward. Amazon Web Services is growing AI-related revenue at the high end of the hyperscaler range, but the capex required to support that growth is sufficiently lumpy that the company has chosen to pre-fund a significant share through long-duration debt rather than to draw down cash reserves.

That choice is being made simultaneously by Alphabet, Microsoft, Meta and Oracle. Combined hyperscaler debt issuance ran past $121bn in 2025 and is on pace to top that figure by mid-2026; the $650bn of combined Big Tech AI capex now planned for 2026 is the operating-budget number that explains the funding-side urgency.

Investor reception of these trades has been consistently strong. The four largest US hyperscalers all retain credit ratings in the AA range, which gives them access to the deepest pools of institutional fixed-income demand at margins that no private-market financing structure can match.

The largest 2025 trades were oversubscribed by margins that would have looked unusual in any other sector; Amazon’s March dollar trade ran roughly 4x covered.

The Swiss franc market is smaller in absolute terms (the all-currency corporate market clears around CHF 60-70bn a year by Refinitiv tracking), but the rate environment, with Swiss yields running materially below US dollar and euro equivalents, makes it commercially attractive for issuers whose absolute funding needs can be split across currencies.

The currency-strategy logic is genuinely diversification rather than yield optimisation. A multi-currency programme reduces dependence on any single investor base, gives a treasurer flexibility about which tranches to access in periods of regional volatility, and lengthens the average maturity profile by tapping markets where long-duration demand is particularly deep.

Amazon’s choice of a 25-year tranche at the long end of this Swiss deal is consistent with that strategy. Three, five, seven and ten-year tranches give the company belly-of-curve flexibility.

The fifteen and twenty-five-year pieces match insurance and pension demand that is harder to source in equivalent size in dollars.

The wider question, which the cleaner trades of the past three months have made more rather than less acute, is how long the supportive funding environment lasts.

Hyperscaler bond issuance has been running at a pace that even bullish analysts had not modelled at the start of 2025. Morgan Stanley and JPMorgan have estimated that the sector may need to issue as much as $1.5 trillion of additional debt over the coming several years to fund the AI build-out at planned pace.

That figure assumes capex continues to grow on its current trajectory; if AI revenue growth lags those expectations, the credit metrics underpinning the AA ratings could come under more scrutiny.

The cash-generation strength behind Alphabet’s market-cap rise is part of the story that has kept the credit picture intact so far, but it depends on operating cash flow continuing to scale with the build.

Amazon’s specific position remains comfortable. The company generated approximately $100bn of free cash flow in fiscal 2025 against group capex of about $80bn, with the gap funded from existing cash reserves and incremental debt.

AWS’s operating margins have stayed above 30%, the highest in the segment. The credit spread on Amazon’s recent dollar issuance was in line with that of higher-rated peers, and the Swiss franc trade is expected to price comfortably inside the broader US dollar curve.

That Alphabet’s earlier $10bn bond sale, then the company’s largest and cheapest, was, in its time, considered the standard-setting hyperscaler funding event.

Amazon’s current programme is, in dollar terms, several multiples of that size and is unlikely to be the largest such trade for very long.

What the Swiss issuance does not yet answer is whether AI revenue scaling will eventually justify the issuance pace.

Amazon’s bond investors are taking the company’s AWS-plus-retail combined cash-flow profile as collateral for the AI build, not the AI revenue itself, which remains too early in its monetisation curve to support credit metrics on a standalone basis.

That is the same bet Alphabet, Microsoft, and Meta are asking their bond books to take. The premise has worked through 2025 and into 2026.

Whether it works through to the back half of the decade depends on what AWS, Google Cloud, and the various large-language-model product lines deliver in revenue over the same window.

For now, the Swiss tranche prices when it prices, and Amazon adds a fourth jurisdiction to a treasury programme that increasingly looks more like that of a sovereign issuer than a corporate one.

The company has yet to issue in yen. On the current trajectory, that is a question of when rather than whether.

The New York Times is betting that the Wordle craze isn’t over yet. On Monday, the Times announced that it would be turning the hit mobile word game into a televised game show on NBC.

“Today” show anchor Savannah Guthrie will host the affair, while The Times and “The Tonight Show” host Jimmy Fallon will both serve as production partners. Guthrie and Fallon announced the news on the 8:00 AM broadcast of the “Today” show on Monday, where they shared that the game show had been in development for the past two-and-a-half years.

The show, which will begin airing on NBC next year, is being described as “fast-paced” and a “great family game.” That sounds a bit different from the mobile game, which often requires long periods of thought where users work through the possible choices.

This will be the first time that The Times has collaborated with a TV broadcaster for an entertainment-based program, representing yet another shift in the media company’s pivot to build a sustainable digital subscription business as print revenue continues to decline.

Wordle began its life as a popular online word puzzle game after being released in October 2021 by Josh Wardle, a software engineer in Brooklyn. In January of the following year, The NYT acquired the title for its growing games business, almost immediately bringing “tens of millions” of new users to the New York Times. As of last year, NYT Games says that users played more than 11 billion puzzles across all its games over the course of the year, up from 8 billion in 2023.

NBC will start shooting episodes of the game show this summer and is currently looking for contestants.

Robert Walters’ report explores how Ireland’s professionals are managing increasing yet unrecognised workloads.

According to research from Robert Walters, Irish professionals are reporting an increase in work as a result of a growing ‘shadow workload’, consisting of the invisible, non-core tasks employees often undertake alongside their main responsibilities and activities. 

Six out of 10 Irish participants in Robert Walters’ study said that in the last year, the remit of their work has expanded, without being officially recognised, acknowledged or accompanied by additional pay or career progression.  

In response, professionals are finding themselves in a position where they are now working longer hours (53pc of respondents). Nearly one in five said that they often have to delegate tasks where possible. Only 16pc of those who contributed their data have even spoken to their employer about the sudden spike in workload. 

Commenting on the announcement, Suzanne Feeney, the country manager at Robert Walters Ireland, said, “Many Irish organisations are navigating a tougher operating environment right now, facing cost pressures, greater competition for top talent and the need to deliver more with fewer resources.”

Flaming out

In the workplace, when the level of work increases it is often accompanied by burnout, fatigue and general dissatisfaction. The report found that to manage added responsibilities, employers are now turning to AI tools as a means of creating more time. 37pc of Irish workers admitted to using AI tools to handle tasks they typically wouldn’t be able to manage. 

More than two in five participants (42pc) explained that burnout at work is a frequent occurrence, while a further 35pc reported it as being an intermittent experience. 

“Taking on new responsibilities can be valuable for both individuals and organisations, particularly when it supports growth and capability building,” said Andrew Powell, the chief commercial officer at Robert Walters.

“But if that effort isn’t recognised or managed effectively, it can lead to fatigue and diminishing returns, impacting everything from decision-making to overall productivity.”

Powell advised employers and leaders to keep an eye on how work is being distributed and whether employees are under increasing levels of pressure.  

He said, “Addressing workload creep requires having greater visibility of where pressure is building and responding with the right mix of solutions, whether that’s redistributing work, investing in the right tools or bringing in temporary expertise where needed.

“Ultimately, organisations that strike the right balance between efficiency and sustainable workloads will be better positioned to maintain long term performance.”

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AirPods started as the wireless earbuds people bought for music, calls, podcasts, and ignoring strangers on the subway with commitment. Apple’s next move could make them a lot harder to ignore.

According to reporting from Bloomberg’s Mark Gurman, Apple is testing a future version of AirPods with built-in low-resolution cameras designed for AI features, not traditional photo or video capture. The goal, reportedly, is to let AirPods gather visual information about the user’s surroundings and feed that context into Siri or other Apple Intelligence features. In other words, this is less “AirPods become a GoPro for your ears” and more “Apple wants its earbuds to understand what you are looking at.” 

The reported prototypes are said to be in design validation testing, a late development stage before production validation, with Bloomberg describing the design and feature set as close to final. Apple has not announced the product, confirmed a release date, or posted anything about camera-equipped AirPods on its own website, so this remains a reported product in testing rather than an official launch.

That distinction matters, especially when the words AirPods, cameras, and AI appear in the same sentence and everyone starts acting like Cupertino just invented surveillance earrings. 

What makes this interesting is not that Apple might add cameras to earbuds. It is what those cameras would be for. If the reporting is accurate, future AirPods could become another sensor layer in Apple’s wearable ecosystem, working alongside the iPhone, Apple Watch, Vision Pro, and eventually whatever comes next in smart glasses. Music would still be part of the story, but the bigger play is contextual AI: earbuds that can listen, sense, and help Apple’s software understand the world around the user without requiring a headset on your face.

AI Sensing, Not Ear Photography

The reported goal is not to turn AirPods into a tiny camera rig for people who think society has not suffered enough. The cameras would reportedly be used primarily as sensors, giving Apple’s earbuds a better understanding of the user’s surroundings and helping support more advanced AI-driven features.

That could include the ability to read and interpret elements of the user’s environment, provide more useful contextual awareness through Apple Intelligence, support spatial computing experiences, and improve gesture or motion recognition.

The important distinction is that these would not be cameras in the traditional “take a photo and post it” sense, even if still-image capture were technically possible.

The Real Play Is Device Coordination

The more interesting angle is not what the cameras see, but how Apple might use that information across its devices and AI platform.

AirPods already sit in a privileged position: they are worn close to the head, always connected, and used in moments when pulling out an iPhone is inconvenient or socially awkward. Add visual sensing to that equation, and Apple gains another input point for hands-free interaction.

That could make future AirPods useful for things like confirming where a user is facing, helping Siri respond with better situational context, or improving control methods that do not require tapping a screen. The earbuds become less of a standalone product and more of a quiet relay between the user and Apple’s larger hardware stack.

The iPhone would still do the heavy lifting, because of course it would. At this point, the iPhone is less a phone and more the overworked manager at an Apple Store on launch day. But the value of camera-equipped AirPods would come from feeding it better real-world context, not replacing it.

That is where this rumor starts to make sense. Apple may not be trying to reinvent the earbud. It may be trying to make AirPods another control surface for the next phase of computing.

Apple TV May Be Next in Apple’s AI Hardware Push

The AirPods rumor is not the only sign that Apple may be trying to move AI deeper into its hardware lineup. A next-generation Apple TV box is also reportedly in development, with a newer chip designed to support more advanced Apple Intelligence and Siri features.

The expected upgrades are said to include better Siri interaction, improved video processing, stronger connectivity, and enhanced audio support. A built-in camera has also been reported, although that would likely be aimed at FaceTime, gesture control, user recognition, or smart home interaction rather than turning the Apple TV into a living-room security camera with better branding.

The catch, predictably, is Siri. Reports suggest the new Apple TV has been pushed back because Apple’s upgraded AI version of Siri still is not ready for prime time. That matters because a more capable Siri would be central to the whole pitch. Without it, Apple just has a faster streaming box with a camera, and that is not exactly a revolution. That is a Zoom meeting with better Dolby Vision.

The Bottom Line 

The important distinction is that Apple has confirmed none of this. There is no official AirPods-with-cameras announcement, no new Apple TV box announcement, no Apple TV Pro branding, and no published Apple release date for either product. For now, these are reported developments, not finished products.

What appears credible is the direction of travel. Bloomberg’s Mark Gurman reports that Apple’s camera-equipped AirPods have reached an advanced testing stage, with low-resolution cameras designed to feed visual context to Siri and Apple’s AI systems rather than function like traditional cameras. The Verge, Macworld, and others have also covered the Bloomberg reporting, while Geeky Gadgets has summarized separate Apple TV 4K rumors involving a faster chip, Apple Intelligence, smarter Siri, and possible timing delays. 

The rumor side is just as important. A built-in camera for Apple TV, “Apple TV Pro” branding, final specs, pricing, and launch timing remain unconfirmed. Reports around a delayed 2026 Apple TV upgrade also point back to the same central issue: Apple needs the next version of Siri to be smarter before these products make sense. Without that, this becomes expensive hardware waiting for the software to stop eating paste in the corner.

Why does it matter? Because Apple may be moving beyond passive devices and toward products that see, hear, process, and react with more context. That could make AirPods and Apple TV more useful for accessibility, smart home control, spatial computing, FaceTime, gesture control, entertainment, and hands-free AI interaction. It also raises obvious privacy questions, because putting cameras into earbuds or a living room streaming box is not exactly a small psychological hurdle.

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Lemme tell you sumthin’ about The Punisher: it’s about time he received top billing in a project set in the Marvel Cinematic Universe (MCU) — and that time is now.

Indeed, The Punisher: One Last Kill will see Jon Bernthal’s anti-hero take center stage in a new Marvel TV Special. Thankfully, we don’t have much longer to wait for its arrival, either, because it’ll make its Disney+ debut later this week.

Although there’s no denying that the Apple Watch very much led the charge across the smartwatch industry for a good while there, in 2026 Wear OS watches are as good as they’ve ever been, boasting several features that’ll leave even Apple users feeling jealous. If you’re an Android user and are curious to know what the best Wear OS watches are right now, then we’re here to help.

One of the key things that really works in Wear OS’s favour right now is that unlike the Apple Watch which, on average, presents you with three choices each generation, you have an absurd amount of choice here. You have companies like TicWatch that have been Wear OS stalwarts for years, alongside more recent converts like OnePlus and Samsung, but then you also have Google.

The Android maker finally getting into the wearable space and effectively showing its confidence in its wrist-based platform was the game-changer that Wear OS needed. The Pixel Watch series now serves as a great example of what’s possible with Wear OS, much in the same way as the best Pixel phones with stock Android. Since the first Pixel Watch, we’ve only seen companies build upon that concept with more features, showing that innovation in this space is very much alive and well.

The only key thing to know is that, unlike how it used to be before Google shifted everything forward from Wear OS 3 onwards, these smartwatches do not work with iPhone. If you are tempted by any of the smartwatches we’ve highlighted here then you’ll need to have one of the best Android phones in tow.

With more Wear OS watches hitting the scene every year, this list is in a constant state of flux so it’s always worth checking back to see how our rankings have changed. If you’re focused purely on tracking your running performance then you may be better set with one of the best Garmin watches or the best fitness trackers. Alternatively, anyone who doesn’t want to go beyond a certain budget can find cost-effective picks in our guide to the best cheap smartwatches.

Best Wear OS Smarwatch at a glance

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