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For over fifteen years, the smart glasses industry has been chasing a hard technical problem: how do you fit a compelling digital experience into a normal-looking pair of glasses. We’re finally nearing the goal: Cameras, microphones and an AI language model turn glasses into a quiet, always-available assistant, and that idea is getting real traction.

But the leading product in the industry is unfortunately getting a new nickname this year.

The internet is amplifying the nickname: “Pervert Glasses”.

That term didn’t come from a rival. It came from users, and it’s sticking for a reason.

How We Got Here: Ray-Ban Meta Glasses

Reporting this year on Meta’s Ray-Ban line revealed two separate problems at once. The first was about what happens to footage after it’s recorded: outside data annotators reviewing training material reportedly saw people undressing, using the bathroom, and in other private moments, with automated face-blurring not always working.

The second was about what wearers do with the recording capability: reports of mostly male influencers using the glasses to film themselves approaching women without consent, turning the footage into content, and in some cases with alleged extortion attempts tied to the recordings.

See the articles in the sources section below for more on how this happened.

Neither of those failures has anything to do with waveguides, field of view, resolution or compute power. Both are about consent, data handling, and what the device allows a wearer to do to the people around them.

Meta is already doing damage control by banning Instagram users that are making creepy content.

This Instagram ban is a good first step but it doesn’t stop anyone from recording without consent and posting the content online on YouTube, TikTok or through other social media channels. It’s too little too late.

There are a few recent articles about this (see sources below).

Google / Samsung Galaxy Glasses

Let’s see how the upcoming Google / Samsung glasses address this issue. These Galaxy Glasses are scheduled for release this August and were officially announced a few days ago at Galaxy Unpacked, Samsung’s annual event. Warby Parker and Gentle Monster are behind the frame design and they are made in partnership with Google. Samsung’s website announcement and other articles published recently gives us a few clues as to how they work (see sources below).

The approach here is more of a companion device that connects to the Samsung Galaxy smartphone and smartwatch ecosystem. Android XR is the OS and Gemini is the AI used here via the partnership with Google. Will that allow more on device processing? Is there a different approach to consent? The only mention in the article is “Clear controls and safeguards support responsible and secure use…” without going into much detail. Are these just empty promises?

Based on the referenced articles, we see a few key differences vs. Meta:

A physical privacy toggle, not just a light. Samsung ships a physical switch on the frame arm that can disable the camera by feel, a hardware-level control that Meta’s Ray-Ban glasses don’t have. Meta relies on the LED alone; Samsung adds a mechanical off-switch a wearer can trigger without touching a screen.
Two LEDs instead of one. Per Google’s Android XR design documentation, the spec calls for one LED facing the wearer and a second, outward-facing LED specifically meant to signal bystanders when recording is active, described as a direct hardware response to the privacy scrutiny the category is already facing.
Tamper detection. Samsung’s version disables picture and video capture if a user covers or blocks the LED, and separately stops recording automatically if the glasses are removed and are no longer being worn.

Those are steps in the right direction. However, we don’t yet know how the recorded data will be handled nor is there a clear consent mechanism for recording a conversation.

Soon we’ll know if the Google / Samsung Galaxy glasses get a crude nickname of their own.

This Isn’t New. It’s Just Bigger.

Google Glass earned its own backlash over a decade ago. “Glasshole” became shorthand for the same underlying issue: a camera on someone’s face, and no way for the person interacting with the wearer to know if they’re being recorded. The difference this time is scale. Google Glass sold in the low hundreds of thousands, mostly to early adopters and app developers. Meta has sold the Gen 1 and Gen 2 Ray-Ban Meta Glasses and the new Meta Ray-Ban Display Glasses at real consumer volume (7 million in 2025 and much more projected this year). The same unresolved problem, at 30 times the audience, produces a much bigger reaction.

The industry has solved the hardware problem: normal-looking glasses that people will actually wear. It has yet to solve the trust problem that comes with putting a camera on someone’s face.

This Is Still Fixable if the Category Wants to Survive

It’s tempting to read all of this as proof that camera-equipped smart glasses are simply a bad idea. I don’t think that’s the right conclusion, and I don’t think it’s the conclusion most of the people criticizing are reaching either.

The complaints aren’t about AI glasses as a concept. They’re about specific choices: no visible or non-hackable recording indicator, no meaningful way for a bystander to know or object, and a data pipeline that’s routing sensitive footage to human reviewers without the subject’s knowledge.

Those are product and policy decisions, not laws of physics or new technology that’s maturing.

That means they’re fixable, and the companies that do it first get a real advantage.

What Actually Needs to Change

A few concrete things would move the needle, and none of them require new hardware technology or billions of dollars:

On-device processing wherever possible, so raw footage of someone’s living room, bathroom, or private conversation never has to leave the device to be useful.
Clear, public rules about what gets sent off-device for AI training, who reviews it, and how long it’s kept, published in plain language rather than buried in a terms-of-service update.
A real way for bystanders to opt-in, since the person being recorded never agreed to anything.

Here’s a concrete example of an AI managed Opt-in: The wearer says, out loud, “Hey, can I record this conversation?” directed at the person in front of them. The AI doesn’t start recording on the request alone, it listens for an actual affirmative response from a different voice than the wearer’s, and only then does recording begin, with that exchange itself logged on the device as a timestamped consent record. No consent captured, no recording. This moves the safeguard from a passive indicator a bystander might not notice or trust, to an active exchange both people have to participate in before anything happens.

Face blurring can work alongside this as a second layer: Applied at the point of capture rather than after the fact on a server (which is what failed in the Meta example). The processing happens on the glasses themselves, in real time, before any footage leaves the device. This has its own limits worth mentioning though. On-device blurring in real time is a genuine engineering challenge on a low-power wearable device, not a policy switch.

Together, the two mechanisms cover different gaps. Voice-based consent protects the person the wearer is actually speaking to. On-device face blurring is a backstop for everyone else in frame. No mechanism is completely unbeatable, but both are concrete, buildable examples, and a lot harder to hack than an LED.

We should take a page out of how some companies handled smart doorbells, cameras or dashcams.

These categories faced similar questions years ago and mostly settled on policies like local storage, visible recording states, and clear retention policies. The industry should learn from this.

Time is of the essence

The clock on this matters more than most leadership teams seem to realize. These are not just growing pains for a new category. Meta and the handful of other companies shipping camera-equipped glasses can absorb a bad news cycle. They have other products, other revenue lines, and enough scale to ride out a backlash. The suppliers behind them can’t.

We as component makers, optics manufacturers, and the collective supply chain have spent years and real capital betting on this category, often on the strength of a single customer’s volume commitments.

If trust erodes badly enough that regulators step in, retailers pull the product, or the category simply gets stigmatized the way Google Glass did:

It’s the suppliers who take the disproportionate hit, not the platform companies that caused the problem.

We don’t control the product policies, the data pipeline, or the marketing choices that created the backlash, but we’re the ones the least equipped to absorb the fallout.

The leaders at the top of this stack need to treat trust as urgent not just because it’s the right thing to do, but because the entire supply chain underneath them is exposed to a problem it didn’t create and can’t fix on its own. It’s also a good economic decision to address it sooner than later:

Once trust is gone, it’s expensive to rebuild.

Where This Leaves the Category

I still believe AI is the reason people will wear glasses every day, not augmented reality. The ORA-1 and ORA-2 glasses we built at Optinvent years ago taught me that the value was never the flashiest overlay, it was giving the right person the right information at the right moment. AI is the killer app for this category to go mainstream.

But a killer app doesn’t survive if users are embarrassed to wear the device, or if bystanders feel uncomfortable around them. “Glasshole” was survivable because the category was small, mostly made up of early adopters.

“Pervert Glasses” is a warning shot at real scale, and it’s arriving just as the technology is finally starting to go mainstream.

The optics industry spent fifteen years solving how to make AI glasses look like normal eyewear. The next fifteen months will decide whether the industry can make people trust what’s happening behind the lens.

This problem is solvable. It has to be solved, now, not just apologized for after the fact when it’s too late.

Sources

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