Picture your computer keeping a diary — the kind kids used to keep logging their daily activities, or the kind travelers, merchants, and nobles kept centuries before that. Here’s what it might look like.

Thursday, September 10.

• 8:00 AM. User read the news on cnn.com and bbc.co.uk (Safari).
• 8:10 AM. User replied to John Kaufman’s email about delivery dates, then sent the same question to the logistics team (Gmail).
• 8:20 AM. User checked his to-do list, reviewed recent updates, and planned out the day’s priorities (Todo).

We’re not exaggerating. This is exactly what your Mac’s new diary looks like. It’s a set of text files that any app on your computer can read — as can anyone sitting at the keyboard. The feature responsible is called Computer History, and it was released by OpenAI in mid-August. At the moment, it only works in the ChatGPT app for Mac, requires a Pro subscription or higher, and is disabled by default. According to its developers, the idea behind History is to let the AI assistant quickly get up to speed on your work context, so it can answer even vague requests, like “send a reminder to whoever I was emailing about last week’s deliveries”. Of course, that convenience comes at a price, ranging from your data being processed on OpenAI’s servers, to the risk of it leaking off your Mac — whether to a nosy family member or straight into the hands of cybercriminals.

How ChatGPT Computer History works

If this sounds a lot like Microsoft’s similar Recall feature, or Chronicle, which OpenAI itself announced earlier, that’s no coincidence. Both were built with the same goal in mind, just using different methods. Having watched Recall turn into the PR disaster it was, the team behind Computer History decided against constantly taking and analyzing screenshots. Instead, ChatGPT relies on macOS’s Accessibility features to read the text on your screen and track your actions: mouse clicks, text typed into fields, switching between apps, and the like. All of this gets stored as a stream of raw activity data inside the ChatGPT container (app group), which only the ChatGPT app itself, or other apps you’ve specifically given permission, can access. In tests run by digital forensics researchers, just two hours of normal computer use generated around 3500 of these logged events.

That raw data remains on your computer for up to 48 hours. During this time, the ChatGPT app periodically runs hidden chat sessions behind the scenes, where it asks the AI to summarize related events into a single recap. Essentially diary entries, these summaries get saved as plain text files in a folder that any app on your Mac can open: ~/.codex/memories/extensions/skysight/.

When you chat with the assistant, or when certain automated features kick in, these notes can be pulled into the conversation for more context-aware responses. OpenAI is especially keen on pointing out that the assistant can spot patterns in your workflows and offer to automate them, creating what it calls “skills” that replicate your actions for you.

Once a summary is ready, the raw activity data behind it is deleted. OpenAI says it won’t keep those hidden background chats or use them to train its AI, except where required by law. The diary-style summaries that get pulled into your conversations, though, are stored on OpenAI’s servers under the exact same rules as your regular chats and the assistant’s memory, so your preexisting privacy settings will apply to them too.

What Computer History can see, and what you can turn off

Since the whole feature runs on accessibility tools, ChatGPT only picks up what your operating system is already willing to share with those tools. That includes window titles, blocks of text, image captions in your browser, text you’re typing into a field as you type it, and the names of interface elements you click on. Watching a video? The AI can’t see the video itself, but it can read the window title, the site name, and the video description. Browsing photos? It sees file and folder names, not the actual images. Audio is never recorded or saved in any situation. All that gets logged from a video call is the meeting window title, unless the call itself has live captions turned on. Password fields that are masked (shown as dots) aren’t read at all and, according to OpenAI, private browsing windows are never scanned.

One thing that sets this apart from Microsoft Recall is the clearly spelled out step-by-step procedure the user needs to go through to turn it on. Computer History never activates itself. You have to navigate to the settings menu, then Integrations → Computer History and turn it on manually after reading through the warnings and explanations. You’ll also need access to the agent’s memory enabled for the feature to work. From there, you choose which apps and websites you want it to track, and confirm a series of macOS permission prompts.

For companies using a business subscription, this requires approval at two levels: an administrator first has to enable Computer History for the whole organization, and then each employee has to turn it on individually.

At any point, you can go to Computer History → Permissions and either list specific apps and sites to exclude from tracking, or, conversely, set ChatGPT to only watch a limited list you choose (Include only these apps, Include only these websites).

To see what your own computer’s diary looks like, check Computer History → History. From there, you can delete individual entries or disable the tracking of specific apps directly from the list.

The risks of using ChatGPT Computer History

We covered the risks of centralized storage of someone’s entire activity in our earlier piece on Microsoft Recall, and most of what we said there applies to ChatGPT Computer History.

• You might assume your chats and emails are private, protected by passwords and encryption. But a copy of the most important parts of those conversations is sitting in plain text files that anyone with access to your computer, and plenty of other apps, can open.
• The people you’re messaging have no idea this extra copy exists. If they’ve turned on, say, a self-destructing chat feature, but the messaging app’s window itself isn’t marked as private, that precaution does nothing to protect them.
• Even if you trust OpenAI completely and take its privacy promises at face value, your data can still be stolen directly off your computer by an infostealer. Mac-targeting infostealers have exploded over the past two years, so this isn’t a hypothetical risk. And the people who write this type of malware move fast, quickly updating it to grab whatever new type of data looks promising. OpenAI’s files are a boon for them: everything you’ve done, already summarized by AI into something easy to read. While there are no passwords or credit card numbers in there, the available details are likely enough to craft a convincing targeted urgent email from the boss.
• And if a nosy coworker or family member gets their hands on your computer, reading through the diary of your work and life would take them all of five minutes.

Computer History: turn it off, or just configure it?

We’d recommend limiting or fully disabling Computer History if your work involves sensitive information. This especially applies to doctors, lawyers, and anyone else bound by professional confidentiality, or handling personal or medical data. The same goes for anyone living with an overly controlling family member, or working in an office with nosy coworkers.

If none of that applies to you and you’d like to try out how useful the AI’s search and auto-generated skills actually are, here’s how to set things up safely.

• Lock down your Mac’s login. Turn off auto-login, and set your Mac to require a password immediately after the screensaver kicks in or it wakes from sleep. Use a strong password along with Touch ID, and make sure FileVault disk encryption is turned on.
• Set up your exclusions. Manually add every messaging app you use for private conversations, along with any finance apps or sites, and anywhere else you keep sensitive information, to Computer History’s exclusion list.
• Check in regularly. At least a couple of times a week, visit Computer History settings to see which apps and sites it’s been tracking. This helps you catch and remove any sources of private information you forgot to exclude earlier.

No matter how you configure Computer History, the two most common ways your data could end up in the wrong hands — on any Mac — are a macOS infostealer snatching it directly from your computer, and typing your information into a fake website. To guard against both, make sure you’re running full-featured security software on your Mac, such as Kaspersky Premium for macOS.

AI can create privacy risks you might never think to look for. You can read about more of them in our other posts:

• Attacks on Gemini: the possibilities are endless
• Why AI agents need an iron curtain
• Knives, kinks, and shooters: what AI toys are really saying to kids
• AI and the new reality of sextortion

And if you’d like to know how to turn off AI features that activate on your computer or smartphone without your knowledge, check out our guide, Unplugged: how to disable AI on your computer and smartphone.

Flock Safety’s cameras are automated license plate readers (ALPRs) designed to help police find stolen cars or wanted suspects.

A joint investigation by 404 Media and WIRED, based on data recovered from a physically removed Flock camera, found that its on-device software explicitly detects people as well as vehicles, bicycles, and license plates.

Separately, Washington DC’s police union says the Metropolitan Police Department used Flock data to track officers under Internal Affairs investigation without their knowledge.

Together, these reports illustrate a privacy problem: A network built to record the movements of vehicles can readily be used to follow almost anyone.

The latest reporting adds an important technical detail to that debate.

What Flock cameras collect

A group of hackers reportedly removed a Flock camera from a roadway, copied its storage, and recovered an encryption key stored on the device. That allowed them to unlock videos of thousands of vehicle detections despite Flock’s claim that its devices are protected by on-device encryption. Flock said it could not assess the claims without more detail.

The recovered camera files reportedly contained software models that detect people, even though public discussion of Flock has usually focused on cars and license plates. The researchers found no evidence that face-recognition features were actively used. Reassuring, but it should not be mistaken for a clean privacy bill of health.

Even without facial recognition, a system that records repeated sightings can potentially reveal sensitive patterns of movement, including where someone lives, works, worships, seeks healthcare, attends protests, visits family, or spends time with other people. When a person is matched to a vehicle, vehicle-based tracking can become person-based tracking in practice.

As an example of how widely the data can be shared, WIRED found that records from the city of Alpharetta, Georgia:

“were accessible to more than 2,000 agencies, including police departments, colleges, airports, and, inexplicably, the Office of Inspector General for the federal General Services Administration.”

Targeted tracking of people

The Washington DC dispute shows what happens when the power to follow people is turned inward.

The DC Police Union says it learned in July that MPD’s Internal Affairs investigators had used Flock license-plate-reader data to track sworn officers under investigation without their knowledge. The union filed a complaint and asked the department to stop, arguing that MPD lacked adequate controls for a system with such extensive surveillance capabilities.

MPD defended the use, saying its position is that the use of license-plate-reader data in the misconduct investigation was appropriate. It said the labor dispute is headed to arbitration.

If police officers themselves are concerned that the system can be used to monitor them without transparent rules, the public should ask an obvious follow-up question: What prevents the same tools from being used to follow residents, employees, journalists, activists, former partners, or other people with no meaningful ability to challenge the search?

Even when Flock wants privacy to meet surveillance halfway, its measures do not eliminate the underlying civil-liberties issue.

The recovered camera software and the DC dispute make the same point from different directions. Flock’s network is not merely a collection of roadside plate readers. It is a distributed system for recording movement, identifying patterns, and making those records available for search.

Meaningful safeguards should include:

• Public approval before cameras are deployed, with clear maps showing their locations and stated purposes.
• Strict limits on collection, retention, searches, and cross-jurisdictional sharing.
• A requirement for documented investigative justification before a search, with elevated approval for sensitive investigations.
• Independently reviewable audit logs, regular public transparency reports, and meaningful penalties for misuse.
• Clear bans on searches related to protected activity, immigration enforcement where local law forbids cooperation, abortion-related investigations, political surveillance, and personal purposes.
• Independent security assessments covering the cameras, cloud services, identity controls, key management, and third-party integrations.
• Automatic deletion that cannot be overridden merely because data could someday be useful.

Privacy cannot depend on authorized users always following rules, vendors configuring every setting correctly, or abuses being discovered the hard way. The first safeguard should be limiting the system’s ability to build a searchable record of ordinary people’s lives at all.

---

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Malwarebytes Privacy VPN encrypts your connection and never logs what you do, so the next story you read doesn’t have to feel personal. Try it free → 

Flock Safety’s cameras are automated license plate readers (ALPRs) designed to help police find stolen cars or wanted suspects.

A joint investigation by 404 Media and WIRED, based on data recovered from a physically removed Flock camera, found that its on-device software explicitly detects people as well as vehicles, bicycles, and license plates.

Separately, Washington DC’s police union says the Metropolitan Police Department used Flock data to track officers under Internal Affairs investigation without their knowledge.

Together, these reports illustrate a privacy problem: A network built to record the movements of vehicles can readily be used to follow almost anyone.

The latest reporting adds an important technical detail to that debate.

What Flock cameras collect

A group of hackers reportedly removed a Flock camera from a roadway, copied its storage, and recovered an encryption key stored on the device. That allowed them to unlock videos of thousands of vehicle detections despite Flock’s claim that its devices are protected by on-device encryption. Flock said it could not assess the claims without more detail.

The recovered camera files reportedly contained software models that detect people, even though public discussion of Flock has usually focused on cars and license plates. The researchers found no evidence that face-recognition features were actively used. Reassuring, but it should not be mistaken for a clean privacy bill of health.

Even without facial recognition, a system that records repeated sightings can potentially reveal sensitive patterns of movement, including where someone lives, works, worships, seeks healthcare, attends protests, visits family, or spends time with other people. When a person is matched to a vehicle, vehicle-based tracking can become person-based tracking in practice.

As an example of how widely the data can be shared, WIRED found that records from the city of Alpharetta, Georgia:

“were accessible to more than 2,000 agencies, including police departments, colleges, airports, and, inexplicably, the Office of Inspector General for the federal General Services Administration.”

Targeted tracking of people

The Washington DC dispute shows what happens when the power to follow people is turned inward.

The DC Police Union says it learned in July that MPD’s Internal Affairs investigators had used Flock license-plate-reader data to track sworn officers under investigation without their knowledge. The union filed a complaint and asked the department to stop, arguing that MPD lacked adequate controls for a system with such extensive surveillance capabilities.

MPD defended the use, saying its position is that the use of license-plate-reader data in the misconduct investigation was appropriate. It said the labor dispute is headed to arbitration.

If police officers themselves are concerned that the system can be used to monitor them without transparent rules, the public should ask an obvious follow-up question: What prevents the same tools from being used to follow residents, employees, journalists, activists, former partners, or other people with no meaningful ability to challenge the search?

Even when Flock wants privacy to meet surveillance halfway, its measures do not eliminate the underlying civil-liberties issue.

The recovered camera software and the DC dispute make the same point from different directions. Flock’s network is not merely a collection of roadside plate readers. It is a distributed system for recording movement, identifying patterns, and making those records available for search.

Meaningful safeguards should include:

• Public approval before cameras are deployed, with clear maps showing their locations and stated purposes.
• Strict limits on collection, retention, searches, and cross-jurisdictional sharing.
• A requirement for documented investigative justification before a search, with elevated approval for sensitive investigations.
• Independently reviewable audit logs, regular public transparency reports, and meaningful penalties for misuse.
• Clear bans on searches related to protected activity, immigration enforcement where local law forbids cooperation, abortion-related investigations, political surveillance, and personal purposes.
• Independent security assessments covering the cameras, cloud services, identity controls, key management, and third-party integrations.
• Automatic deletion that cannot be overridden merely because data could someday be useful.

Privacy cannot depend on authorized users always following rules, vendors configuring every setting correctly, or abuses being discovered the hard way. The first safeguard should be limiting the system’s ability to build a searchable record of ordinary people’s lives at all.

---

Browse like no one’s watching. 

Malwarebytes Privacy VPN encrypts your connection and never logs what you do, so the next story you read doesn’t have to feel personal. Try it free → 

The Manhattan District Attorney’s Office has seized the domains of 12 deepfake websites in what it called the largest known seizure of celebrity deepfake sites in history.

The sites, which marketed themselves as deepfake pornography platforms, hosted AI-generated videos of over 1,200 people, including those in the public eye, ranging from politicians to actors, musicians, and social justice advocates. At least one allowed users to create their own deepfakes by grafting real faces and bodies onto sexual imagery.

The term non-consensual intimate imagery (NCII) is increasingly used instead of pornography when the person depicted has not given permission. Deepfake NCII is growing, due in part to the ease with which it can be created. It only takes one photo to generate it, as we discussed on the Lock and Code podcast in June.

MrDeepFakes was previously the largest site for this kind of content. Its operators shut it down in May 2025, citing data loss. An Australian man who posted explicit deepfakes to the site was arrested, fined for contempt of court, and charged with publishing obscene material.

But other deepfake NCII sites continue to compete for attention online.

Deepfake technology can cause real harm when misused, and its effects continue to spread. Manhattan District Attorney Alvin Bragg warned that domestic abusers are threatening to release deepfake NCII depicting their victims. The FBI has also warned that sextortion attackers are using AI to turn social media photos of minors into sexually explicit images.

Legal action is growing

Law enforcement has been working hard to stem the flood of deepfake NCII sites. In June, the Department of Justice and the Department of Homeland Security seized two domains hosting hundreds of thousands of forged images and videos. San Francisco City Attorney David Chiu’s office also sued 16 deepfake sites in August 2024, managing to get ten of them taken offline or made inaccessible in California. New York state also passed legislation prohibiting the distribution of intimate deepfake images and videos in 2023.

At the federal level, the TAKE IT DOWN Act, enacted in May 2025, made certain intentional publication of NCII, including sexual deepfakes, a federal crime.

Seizing a deepfake site stops the immediate distribution of its content, but operators can migrate quickly to other infrastructure. A report from the Institute for Strategic Dialogue (ISD) found that the deepfake ecosystem is made of many parts, from AI tool providers through to hosting companies and cryptocurrency payment processors. It called for a multi-sector collaboration to stop the production and spread of this material.

Bragg’s office said it will continue monitoring the seized websites to stop them reappearing under different domains.

What can you do?

If someone creates or threatens to share intimate deepfakes of you, save the evidence and report it to the police. Do not pay someone who threatens to publish the images, as payment does not guarantee that the threats will stop.

Bragg’s office said many of the victims it approached did not realize that action could be taken. It urged anyone affected by the seized websites to contact its Cyber Crime Bureau at 212-335-9600.

You can learn more in the Malwarebytes guide to deepfakes. UN Women also provides useful resources for people affected by AI-powered abuse.

---

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Malwarebytes Identity Theft Protection catches suspicious activity before it becomes a problem.

The Manhattan District Attorney’s Office has seized the domains of 12 deepfake websites in what it called the largest known seizure of celebrity deepfake sites in history.

The sites, which marketed themselves as deepfake pornography platforms, hosted AI-generated videos of over 1,200 people, including those in the public eye, ranging from politicians to actors, musicians, and social justice advocates. At least one allowed users to create their own deepfakes by grafting real faces and bodies onto sexual imagery.

The term non-consensual intimate imagery (NCII) is increasingly used instead of pornography when the person depicted has not given permission. Deepfake NCII is growing, due in part to the ease with which it can be created. It only takes one photo to generate it, as we discussed on the Lock and Code podcast in June.

MrDeepFakes was previously the largest site for this kind of content. Its operators shut it down in May 2025, citing data loss. An Australian man who posted explicit deepfakes to the site was arrested, fined for contempt of court, and charged with publishing obscene material.

But other deepfake NCII sites continue to compete for attention online.

Deepfake technology can cause real harm when misused, and its effects continue to spread. Manhattan District Attorney Alvin Bragg warned that domestic abusers are threatening to release deepfake NCII depicting their victims. The FBI has also warned that sextortion attackers are using AI to turn social media photos of minors into sexually explicit images.

Legal action is growing

Law enforcement has been working hard to stem the flood of deepfake NCII sites. In June, the Department of Justice and the Department of Homeland Security seized two domains hosting hundreds of thousands of forged images and videos. San Francisco City Attorney David Chiu’s office also sued 16 deepfake sites in August 2024, managing to get ten of them taken offline or made inaccessible in California. New York state also passed legislation prohibiting the distribution of intimate deepfake images and videos in 2023.

At the federal level, the TAKE IT DOWN Act, enacted in May 2025, made certain intentional publication of NCII, including sexual deepfakes, a federal crime.

Seizing a deepfake site stops the immediate distribution of its content, but operators can migrate quickly to other infrastructure. A report from the Institute for Strategic Dialogue (ISD) found that the deepfake ecosystem is made of many parts, from AI tool providers through to hosting companies and cryptocurrency payment processors. It called for a multi-sector collaboration to stop the production and spread of this material.

Bragg’s office said it will continue monitoring the seized websites to stop them reappearing under different domains.

What can you do?

If someone creates or threatens to share intimate deepfakes of you, save the evidence and report it to the police. Do not pay someone who threatens to publish the images, as payment does not guarantee that the threats will stop.

Bragg’s office said many of the victims it approached did not realize that action could be taken. It urged anyone affected by the seized websites to contact its Cyber Crime Bureau at 212-335-9600.

You can learn more in the Malwarebytes guide to deepfakes. UN Women also provides useful resources for people affected by AI-powered abuse.

---

Scammers don’t need to hack you. They just need you to click once. 

Malwarebytes Identity Theft Protection catches suspicious activity before it becomes a problem.

If you’re still OK with posting pictures of your kids on social media, take a minute to hear from mother of two Kalie Robins. At the start of September, she did something that hundreds of thousands of parents do every day. She posted a video of her young daughter on Facebook.

Under the video of Robins and her daughter singing in a car, Facebook’s Meta AI system displayed a suggested question: “Who is the child passenger?”

Robins was shocked that Facebook would ask this question about a minor, so curiosity prompted her to click it. That’s when a flood of automated stalker-type behavior began.

In Instagram post, an enraged Robins described what happened:

“It starts pulling completely separate information for each of my kids.”

That included names, birth dates, and videos of them.

The site also pulled up a picture of her newborn daughter that Robins’ mother had posted on Facebook years ago, along with a long-deleted picture that Robins said had once been in her own account.

Things got weirder. The site then presented another question: “Where does Kalie Robins live?”

An increasingly outraged Robins clicked that question. She described the results:

“[Facebook] started digging through completely unrelated sh*t from years of my life.”

It dug through old posts that hinted at where she had lived in the past and newer posts that connected her to her current home. It finished by attempting to pinpoint her location.

Robins complained:

“I didn’t ask Facebook to build a profile of my family.”

She expressed shock that Facebook would piece together snippets of personal information from historical posts and package them into a detailed profile for other users.

You can watch Kalie Robins’ Instagram video here:

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Meta’s response

Meta launched Meta AI in April 2024 and has since built it into Facebook, Instagram, WhatsApp, and Messenger. It operates across Facebook, Instagram, and WhatsApp. The assistant can answer questions, generate images, and help users create or retrieve information.

Meta admitted in a statement to the Verge:

“The feature never should have prompted the individual with questions like that.”

The company said the feature had “missed the mark” and that it had fixed the issue that caused Meta AI to suggest questions about personal topics.

In a classic “yes, but” non-apology, a Meta spokesperson also pointed out that the AI only surfaced information drawn from posts the person asking could already access. Although that doesn’t seem to explain why it reportedly surfaced a photo she had deleted years ago.

A pattern of Meta AI failures

Meta AI hasn’t always respected privacy. In June last year, we reported that users were publicly sharing conversations, often without realizing it. A separate bug we reported the following month could have allowed people to view other users’ private Meta AI chats by simply guessing their IDs. Late last year, Meta also started targeting people with ads based on their Meta AI conversations.

What can users do?

Parents get understandably irate when they discover just how much sites like Facebook can learn about their kids. While Robins regularly posted pictures and videos of her children, she had no idea that the service could aggregate information from years of posts to profile them. She’s not alone.

So what can people do about it? Perhaps the better question is: What should people not do? The clearest answer is not to post identifiable pictures of your kids (or other people’s) on social media. Not just to stop them being tracked in a privacy hellscape, but also to reduce the risk of even darker outcomes.

Robins described what she planned to do next:

“I’m done. I’m removing any identifiable pictures and videos of our kids.”

She added that she’ll ask her friends to do the same because, if they don’t, Facebook would still be able to harvest her children’s pictures from their accounts and use them in the profiles it builds.

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If you’re still OK with posting pictures of your kids on social media, take a minute to hear from mother of two Kalie Robins. At the start of September, she did something that hundreds of thousands of parents do every day. She posted a video of her young daughter on Facebook.

Under the video of Robins and her daughter singing in a car, Facebook’s Meta AI system displayed a suggested question: “Who is the child passenger?”

Robins was shocked that Facebook would ask this question about a minor, so curiosity prompted her to click it. That’s when a flood of automated stalker-type behavior began.

In Instagram post, an enraged Robins described what happened:

“It starts pulling completely separate information for each of my kids.”

That included names, birth dates, and videos of them.

The site also pulled up a picture of her newborn daughter that Robins’ mother had posted on Facebook years ago, along with a long-deleted picture that Robins said had once been in her own account.

Things got weirder. The site then presented another question: “Where does Kalie Robins live?”

An increasingly outraged Robins clicked that question. She described the results:

“[Facebook] started digging through completely unrelated sh*t from years of my life.”

It dug through old posts that hinted at where she had lived in the past and newer posts that connected her to her current home. It finished by attempting to pinpoint her location.

Robins complained:

“I didn’t ask Facebook to build a profile of my family.”

She expressed shock that Facebook would piece together snippets of personal information from historical posts and package them into a detailed profile for other users.

You can watch Kalie Robins’ Instagram video here:

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Meta’s response

Meta launched Meta AI in April 2024 and has since built it into Facebook, Instagram, WhatsApp, and Messenger. It operates across Facebook, Instagram, and WhatsApp. The assistant can answer questions, generate images, and help users create or retrieve information.

Meta admitted in a statement to the Verge:

“The feature never should have prompted the individual with questions like that.”

The company said the feature had “missed the mark” and that it had fixed the issue that caused Meta AI to suggest questions about personal topics.

In a classic “yes, but” non-apology, a Meta spokesperson also pointed out that the AI only surfaced information drawn from posts the person asking could already access. Although that doesn’t seem to explain why it reportedly surfaced a photo she had deleted years ago.

A pattern of Meta AI failures

Meta AI hasn’t always respected privacy. In June last year, we reported that users were publicly sharing conversations, often without realizing it. A separate bug we reported the following month could have allowed people to view other users’ private Meta AI chats by simply guessing their IDs. Late last year, Meta also started targeting people with ads based on their Meta AI conversations.

What can users do?

Parents get understandably irate when they discover just how much sites like Facebook can learn about their kids. While Robins regularly posted pictures and videos of her children, she had no idea that the service could aggregate information from years of posts to profile them. She’s not alone.

So what can people do about it? Perhaps the better question is: What should people not do? The clearest answer is not to post identifiable pictures of your kids (or other people’s) on social media. Not just to stop them being tracked in a privacy hellscape, but also to reduce the risk of even darker outcomes.

Robins described what she planned to do next:

“I’m done. I’m removing any identifiable pictures and videos of our kids.”

She added that she’ll ask her friends to do the same because, if they don’t, Facebook would still be able to harvest her children’s pictures from their accounts and use them in the profiles it builds.

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