I’ve been thinking a lot about Ring’s Super Bowl ad. You know the one. Lost dog, tearful owner, and then boom, the magic of AI-powered search finds the pup using neighborhood security cameras. Heartwarming, right? Except it immediately triggered something in my brain that I couldn’t shake: if this system can find a dog, it can obviously find a person.
And that’s exactly what everyone else thought too.
The backlash was swift and brutal. Sen. Ed Markey called it “dystopian.” Matt Nelson from weratedogs posted response videos. The conversation on social platforms actually peaked two days after the Super Bowl, which tells you something about how deeply this unsettled people. Within four days, Ring canceled its controversial partnership with Flock Safety, a company whose surveillance systems have been accessed by ICE.
But here’s what fascinates me as someone who works in tech: Ring’s founder Jamie Siminoff isn’t backing down from the core mission. In a recent Decoder interview, he was remarkably candid about wanting to use artificial intelligence to “eliminate crime.” Not reduce it. Eliminate it. He actually said he sees “a path where we can actually start to take down crime in a neighborhood to call it close to zero.”
The Mental Model That Should Scare You
Jamie’s analogy for how this would work is revealing. He describes a neighborhood where every house has dedicated security guards who know everything about you, your family, your patterns, your visitors. These guards have worked your house for 10-20 years. The neighborhood also has an HOA with private security. When something happens, like a lost dog, they all call each other and solve it immediately.
When the interviewer asked if that neighborhood might actually suck to live in, Jamie’s response was essentially: you must live in a safe neighborhood.
This is the classic Silicon Valley blind spot. The assumption that more data, more surveillance, more intelligence equals better outcomes. The belief that technology can solve social problems that are fundamentally about inequality, opportunity, and systemic issues.
I get the appeal of the vision. Who doesn’t want safer neighborhoods? But the path Jamie describes requires accepting a level of constant monitoring that feels fundamentally incompatible with privacy and civil liberties.
What AI Actually Enables Here
The technical reality is important to understand. Five years ago, Ring couldn’t have built Search Party. The AI systems to parse through massive amounts of video, identify objects, track movement patterns across multiple cameras, they weren’t mature enough or accessible enough.
Now they are.
Jamie talks about how motion detection was revolutionary when Ring started. You’d get an alert that something moved at your front door. That was magical. But with AI, he says, you shouldn’t get motion alerts. You should get semantic understanding. The system should tell you what’s there, whether it matters, when you should pay attention.
That’s the shift from dumb sensors to intelligent agents. And it’s a shift that changes everything about what these devices mean in our lives.
The technical architecture Jamie describes is actually quite elegant from a privacy perspective, at least on paper. Each house is its own node, controlled by the owner. Your video stays in your control. You opt in to sharing. There’s an audit trail. When a dog goes missing and the system thinks it spotted it near your house, you can choose to respond or ignore it.
But that architecture only holds if we trust the company running the platform. And if we trust that company’s relationships with law enforcement. And if we trust that the AI won’t be repurposed. And if we trust that the feature scope won’t expand.
The Flock Problem
This is where things got real. Ring announced a partnership with Flock Safety last October. Flock makes those solar-powered cameras you see on streetlights and in parking lots. They vacuum up massive amounts of data, license plates primarily, and make it searchable for law enforcement.
The problem is that Flock’s data has repeatedly found its way to ICE, the FBI, the Secret Service, and other federal agencies, often without warrants. Flock’s defense is technically true but deeply unsatisfying: they don’t work with ICE directly, they work with local police, and those local agencies share with ICE.
Ring said the integration never went live, that no customer videos were ever sent to Flock. But the mere announcement of the partnership revealed the trajectory. This is where Ring wanted to go. This is the vision.
And when pressed about connecting databases, about facial recognition, about the point where maybe you’ve gone too far, Jamie’s answers are careful but not reassuring. He talks about “Familiar Faces” which is just like searching your iPhone photos. He talks about anomaly detection. He insists they don’t need real-time facial recognition tracking to achieve the crime reduction goals.
But then he also talks about how AI allows them to tell you “when you should be trying to be part of something.” The system decides what’s worth your attention. The system learns patterns. The system connects data.
The Uncomfortable Truth About Video Evidence
Here’s where I have to complicate my own argument, because reality is messy. While we’re all rightfully concerned about Ring’s surveillance capabilities, we’re simultaneously watching regular people use their phones to record police and ICE, creating documentary evidence of civil rights violations.
Minnesota governor Tim Walz is literally telling people to hit record when they see ICE. The FBI just used footage from a Google Nest camera to help identify a kidnapper. Video evidence from citizen devices is becoming crucial for accountability.
The systems that enable Ring’s potentially dystopian surveillance future are the same systems that enable citizen journalism and police accountability. The guardrails are equally weak in both directions.
Jamie actually had a thoughtful answer when asked about authenticating video in an age of AI-generated fakes. Ring can provide a digital fingerprint, a chain of custody, proof that video came directly from a specific camera at a specific time and wasn’t tampered with. That’s genuinely valuable.
But it also means Ring becomes a central authority for truth. The video on Ring’s servers is real. Everything else is suspect. That’s a lot of power to hand to a company owned by Amazon.
What Developers Should Take From This
I think there are a few technical and ethical lessons here that matter for anyone building systems that collect data or make automated decisions.
First, the “it’s just like your iPhone” defense doesn’t work. Yes, Apple Photos does facial recognition. But it happens on-device, with my photos, that I took, of people I know. The model and the data never leave my phone. That’s architecturally different from cloud-based analysis of video captured by cameras watching public spaces, even if those cameras are mounted on private property.
Second, the opt-in model breaks down when there are network effects. If my neighbor opts in to sharing Ring footage, and I walk past their house, I’m in their footage. I never consented. The system captured me anyway. This is the fundamental problem with surveillance that watches shared spaces.
Third, mission statements matter more than feature promises. Ring says Search Party “isn’t capable” of finding people. Okay, but Ring’s stated mission is to eliminate crime through AI-powered video analysis. Do you really believe they’ll stop at dogs?
The technical capabilities exist. The partnerships exist, or existed, or will exist again. The business incentives exist. Once you’ve built the infrastructure for intelligent video search, the marginal cost of expanding its capabilities is low.
The Regulation We’re Not Going to Get
Jamie mentioned multiple times that government needs to step in, that we need regulations around evidentiary video, around chain of custody, around preventing tampering. He’s right about that.
But as he also noted, “right now, in 2026 America, I’m not sure we’re really going to be able to do that.”
That’s the most honest assessment of where we are. We have the technology. We have the business models. We have the use cases, both legitimate and concerning. What we don’t have is the regulatory framework, the legal precedents, or apparently the political will to draw clear lines.
So companies like Ring are drawing their own lines, responding to public pressure, making partnerships and then canceling them, building features and then promising they won’t expand them. It’s all very reactive and trust-based.
The problem with trust-based systems is they work great until they don’t.
I keep coming back to Jamie’s neighborhood analogy. He genuinely believes that a place with maximum surveillance, where “doing crime is not profitable,” where private security knows everything, is better than what exists in underserved communities today. He’s seen those communities. He’s been on ride-alongs. He believes in this mission.
But what he’s describing isn’t actually eliminating crime, it’s displacing it. If one neighborhood becomes impossible to operate in, criminals go elsewhere. Unless literally every neighborhood has Ring cameras, which is its own kind of dystopia. And even then, you’re just changing which crimes are possible, not eliminating crime as a social phenomenon.
The real question isn’t whether Ring can build these AI systems, it’s whether we want to live in the world where they exist at scale, where they’re connected, where they’re queried by law enforcement, where the default state is being watched and analyzed. Ring canceled its Flock partnership, but Search Party is still on by default, and you have to dig into settings to turn it off, and that video is still being uploaded to Amazon’s servers where its persistence and potential uses are outside your control.