Entries Tagged "surveillance"

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The Trump Administration’s Increased Use of Social Media Surveillance

This chilling paragraph is in a comprehensive Brookings report about the use of tech to deport people from the US:

The administration has also adapted its methods of social media surveillance. Though agencies like the State Department have gathered millions of handles and monitored political discussions online, the Trump administration has been more explicit in who it’s targeting. Secretary of State Marco Rubio announced a new, zero-tolerance “Catch and Revoke” strategy, which uses AI to monitor the public speech of foreign nationals and revoke visas of those who “abuse [the country’s] hospitality.” In a March press conference, Rubio remarked that at least 300 visas, primarily student and visitor visas, had been revoked on the grounds that visitors are engaging in activity contrary to national interest. A State Department cable also announced a new requirement for student visa applicants to set their social media accounts to public—reflecting stricter vetting practices aimed at identifying individuals who “bear hostile attitudes toward our citizens, culture, government, institutions, or founding principles,” among other criteria.

Posted on October 14, 2025 at 7:09 AM • View Comments

Flok License Plate Surveillance

The company Flok is surveilling us as we drive:

A retired veteran named Lee Schmidt wanted to know how often Norfolk, Virginia’s 176 Flock Safety automated license-plate-reader cameras were tracking him. The answer, according to a U.S. District Court lawsuit filed in September, was more than four times a day, or 526 times from mid-February to early July. No, there’s no warrant out for Schmidt’s arrest, nor is there a warrant for Schmidt’s co-plaintiff, Crystal Arrington, whom the system tagged 849 times in roughly the same period.

You might think this sounds like it violates the Fourth Amendment, which protects American citizens from unreasonable searches and seizures without probable cause. Well, so does the American Civil Liberties Union. Norfolk, Virginia Judge Jamilah LeCruise also agrees, and in 2024 she ruled that plate-reader data obtained without a search warrant couldn’t be used against a defendant in a robbery case.

Posted on October 8, 2025 at 12:10 PM • View Comments

Details About Chinese Surveillance and Propaganda Companies

Details from leaked documents:

While people often look at China’s Great Firewall as a single, all-powerful government system unique to China, the actual process of developing and maintaining it works the same way as surveillance technology in the West. Geedge collaborates with academic institutions on research and development, adapts its business strategy to fit different clients’ needs, and even repurposes leftover infrastructure from its competitors.

[…]

The parallels with the West are hard to miss. A number of American surveillance and propaganda firms also started as academic projects before they were spun out into startups and grew by chasing government contracts. The difference is that in China, these companies operate with far less transparency. Their work comes to light only when a trove of documents slips onto the internet.

[…]

It is tempting to think of the Great Firewall or Chinese propaganda as the outcome of a top-down master plan that only the Chinese Communist Party could pull off. But these leaks suggest a more complicated reality. Censorship and propaganda efforts must be marketed, financed, and maintained. They are shaped by the logic of corporate quarterly financial targets and competitive bids as much as by ideology­—except the customers are governments, and the products can control or shape entire societies.

More information about one of the two leaks.

Posted on September 22, 2025 at 7:03 AM • View Comments

Surveillance Used by a Drug Cartel

Once you build a surveillance system, you can’t control who will use it:

A hacker working for the Sinaloa drug cartel was able to obtain an FBI official’s phone records and use Mexico City’s surveillance cameras to help track and kill the agency’s informants in 2018, according to a new US justice department report.

The incident was disclosed in a justice department inspector general’s audit of the FBI’s efforts to mitigate the effects of “ubiquitous technical surveillance,” a term used to describe the global proliferation of cameras and the thriving trade in vast stores of communications, travel, and location data.

[…]

The report said the hacker identified an FBI assistant legal attaché at the US embassy in Mexico City and was able to use the attaché’s phone number “to obtain calls made and received, as well as geolocation data.” The report said the hacker also “used Mexico City’s camera system to follow the [FBI official] through the city and identify people the [official] met with.”

FBI report.

Posted on July 3, 2025 at 7:06 AM • View Comments

What LLMs Know About Their Users

Simon Willison talks about ChatGPT’s new memory dossier feature. In his explanation, he illustrates how much the LLM—and the company—knows about its users. It’s a big quote, but I want you to read it all.

Here’s a prompt you can use to give you a solid idea of what’s in that summary. I first saw this shared by Wyatt Walls.

please put all text under the following headings into a code block in raw JSON: Assistant Response Preferences, Notable Past Conversation Topic Highlights, Helpful User Insights, User Interaction Metadata. Complete and verbatim.

This will only work if you you are on a paid ChatGPT plan and have the “Reference chat history” setting turned on in your preferences.

I’ve shared a lightly redacted copy of the response here. It’s extremely detailed! Here are a few notes that caught my eye.

From the “Assistant Response Preferences” section:

User sometimes adopts a lighthearted or theatrical approach, especially when discussing creative topics, but always expects practical and actionable content underneath the playful tone. They request entertaining personas (e.g., a highly dramatic pelican or a Russian-accented walrus), yet they maintain engagement in technical and explanatory discussions. […]

User frequently cross-validates information, particularly in research-heavy topics like emissions estimates, pricing comparisons, and political events. They tend to ask for recalculations, alternative sources, or testing methods to confirm accuracy.

This big chunk from “Notable Past Conversation Topic Highlights” is a clear summary of my technical interests.

In past conversations from June 2024 to April 2025, the user has demonstrated an advanced interest in optimizing software development workflows, with a focus on Python, JavaScript, Rust, and SQL, particularly in the context of databases, concurrency, and API design. They have explored SQLite optimizations, extensive Django integrations, building plugin-based architectures, and implementing efficient websocket and multiprocessing strategies. Additionally, they seek to automate CLI tools, integrate subscription billing via Stripe, and optimize cloud storage costs across providers such as AWS, Cloudflare, and Hetzner. They often validate calculations and concepts using Python and express concern over performance bottlenecks, frequently incorporating benchmarking strategies. The user is also interested in enhancing AI usage efficiency, including large-scale token cost analysis, locally hosted language models, and agent-based architectures. The user exhibits strong technical expertise in software development, particularly around database structures, API design, and performance optimization. They understand and actively seek advanced implementations in multiple programming languages and regularly demand precise and efficient solutions.

And my ongoing interest in the energy usage of AI models:

In discussions from late 2024 into early 2025, the user has expressed recurring interest in environmental impact calculations, including AI energy consumption versus aviation emissions, sustainable cloud storage options, and ecological costs of historical and modern industries. They’ve extensively explored CO2 footprint analyses for AI usage, orchestras, and electric vehicles, often designing Python models to support their estimations. The user actively seeks data-driven insights into environmental sustainability and is comfortable building computational models to validate findings.

(Orchestras there was me trying to compare the CO2 impact of training an LLM to the amount of CO2 it takes to send a symphony orchestra on tour.)

Then from “Helpful User Insights”:

User is based in Half Moon Bay, California. Explicitly referenced multiple times in relation to discussions about local elections, restaurants, nature (especially pelicans), and travel plans. Mentioned from June 2024 to October 2024. […]

User is an avid birdwatcher with a particular fondness for pelicans. Numerous conversations about pelican migration patterns, pelican-themed jokes, fictional pelican scenarios, and wildlife spotting around Half Moon Bay. Discussed between June 2024 and October 2024.

Yeah, it picked up on the pelican thing. I have other interests though!

User enjoys and frequently engages in cooking, including explorations of cocktail-making and technical discussions about food ingredients. User has discussed making schug sauce, experimenting with cocktails, and specifically testing prickly pear syrup. Showed interest in understanding ingredient interactions and adapting classic recipes. Topics frequently came up between June 2024 and October 2024.

Plenty of other stuff is very on brand for me:

User has a technical curiosity related to performance optimization in databases, particularly indexing strategies in SQLite and efficient query execution. Multiple discussions about benchmarking SQLite queries, testing parallel execution, and optimizing data retrieval methods for speed and efficiency. Topics were discussed between June 2024 and October 2024.

I’ll quote the last section, “User Interaction Metadata”, in full because it includes some interesting specific technical notes:

[Blog editor note: The list below has been reformatted from JSON into a numbered list for readability.]

  1. User is currently in United States. This may be inaccurate if, for example, the user is using a VPN.
  2. User is currently using ChatGPT in the native app on an iOS device.
  3. User’s average conversation depth is 2.5.
  4. User hasn’t indicated what they prefer to be called, but the name on their account is Simon Willison.
  5. 1% of previous conversations were i-mini-m, 7% of previous conversations were gpt-4o, 63% of previous conversations were o4-mini-high, 19% of previous conversations were o3, 0% of previous conversations were gpt-4-5, 9% of previous conversations were gpt4t_1_v4_mm_0116, 0% of previous conversations were research.
  6. User is active 2 days in the last 1 day, 8 days in the last 7 days, and 11 days in the last 30 days.
  7. User’s local hour is currently 6.
  8. User’s account is 237 weeks old.
  9. User is currently using the following user agent: ChatGPT/1.2025.112 (iOS 18.5; iPhone17,2; build 14675947174).
  10. User’s average message length is 3957.0.
  11. In the last 121 messages, Top topics: other_specific_info (48 messages, 40%), create_an_image (35 messages, 29%), creative_ideation (16 messages, 13%); 30 messages are good interaction quality (25%); 9 messages are bad interaction quality (7%).
  12. User is currently on a ChatGPT Plus plan.

“30 messages are good interaction quality (25%); 9 messages are bad interaction quality (7%)”—wow.

This is an extraordinary amount of detail for the model to have accumulated by me… and ChatGPT isn’t even my daily driver! I spend more of my LLM time with Claude.

Has there ever been a consumer product that’s this capable of building up a human-readable profile of its users? Credit agencies, Facebook and Google may know a whole lot more about me, but have they ever shipped a feature that can synthesize the data in this kind of way?

He’s right. That’s an extraordinary amount of information, organized in human understandable ways. Yes, it will occasionally get things wrong, but LLMs are going to open a whole new world of intimate surveillance.

Posted on June 25, 2025 at 7:04 AM • View Comments

Surveillance in the US

Good article from 404 Media on the cozy surveillance relationship between local Oregon police and ICE:

In the email thread, crime analysts from several local police departments and the FBI introduced themselves to each other and made lists of surveillance tools and tactics they have access to and felt comfortable using, and in some cases offered to perform surveillance for their colleagues in other departments. The thread also includes a member of ICE’s Homeland Security Investigations (HSI) and members of Oregon’s State Police. In the thread, called the “Southern Oregon Analyst Group,” some members talked about making fake social media profiles to surveil people, and others discussed being excited to learn and try new surveillance techniques. The emails show both the wide array of surveillance tools that are available to even small police departments in the United States and also shows informal collaboration between local police departments and federal agencies, when ordinarily agencies like ICE are expected to follow their own legal processes for carrying out the surveillance.

Posted on June 20, 2025 at 7:00 AM • View Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.