General AI Crap

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The Drive's own director of content Joel Feder was test driving a $155,000 Range Rover in suburban Minnesota when four cop cars boxed him and his wife in at a Kohl's parking lot with hands on their guns all because a data entry error in California created a partial plate match in Flock's AI system.

This system ignored a "10" in the middle of his New Jersey manufacturer plate and flagged him as a stolen vehicle suspect, then tracked him for days across 18 cameras until he made a mistake and stopped somewhere without a garage.

The genuinely alarming part isn't the single screwup. It's that Flock told him the system worked "correctly," four other cars were being tracked on the same bad data simultaneously, and the cop's advice to an innocent man afterward was "you're lucky you're in Plymouth, in Minneapolis they definitely would've come at you with guns drawn."
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How Flock Cameras Wrongly Tracked Me for Days Over ‘Stolen’ Plates and Sent Police After Me - The Drive​

A simple error got magnified by Flock's nationwide surveillance camera network and ended with four cop cars boxing me in.

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“Are you armed?!” the police officer screamed. “Get out of the car!”

On an otherwise normal Sunday afternoon in late June, I’d decided to take the $155,000 Range Rover I was testing that week out to run some errands with my wife. Little did I know that choice would complete a technological chain linking surveillance cameras, AI, and law enforcement that led to me and my wife being surrounded by police, hands on their guns, in a Kohl’s parking lot in suburban Minnesota.

After dropping off our Amazon returns, we’d just gotten back in the Range Rover and reversed maybe two feet out of the spot when four cop cars came flying out of nowhere and boxed us in. The officers jumped out and started shouting.

It’s a situation that can quickly and frequently turn bad, so as unprepared as I was, I followed their orders, got out with my hands up, and tried to figure out what the hell was happening.

Read the full article here:
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www.thedrive.com

How Flock Cameras Wrongly Tracked Me for Days Over ‘Stolen’ Plates and Sent Police After Me

A simple error got magnified by Flock's nationwide surveillance camera network and ended with four cop cars boxing me in.
www.thedrive.com www.thedrive.com

Flock’s CEO Faced Me After Its Cameras Led to My Wrongful Stop - The Drive​

Flock CEO Garrett Langley sat down to discuss the errors that led to police stopping me and the growing fight over Flock's network of AI-powered surveillance cameras.

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Millions of people have seen the story of Flock cameras tracking me in a $155,000 Range Rover and subsequently four police officers surrounding my wife and me in a parking lot.

Human error was involved, but Flock cameras working off the company’s AI tech compounded everything at an exponential rate.

Now on the latest episode of The Drivecast, Flock Safety Founder and CEO Garrett Langley sat down with me for a candid discussion about what happened to me and countless others in the last few years, the future vision for Flock amid the public backlash over privacy and Fourth Amendment concerns, the growing calls for regulation, and his previous comment that people who destroy or vandalize Flock equipment are “domestic terrorists.”

On a daily basis there’s reporting of cops misusing Flock’s tech to stalk people, which in turn ends up getting them arrested and sent to jail, misread situations taking place, arguments at city council meetings, and people targeting the automatic license plate readers and cutting them down, shooting them, covering them with trash bags and more.

You might call this a hot topic, and somehow, I landed right in the middle of it.
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Read the full article here:

www.thedrive.com

Flock's CEO Finally Faced Me After My Wrongful Stop. Here's What I Learned

Flock CEO Garrett Langley sat down to discuss the errors that led to police stopping me and the growing fight over Flock's network of AI-powered surveillance cameras.
www.thedrive.com www.thedrive.com
 
fstoppers.com

Google's AI System Terminated 130,000 YouTube Channels | Fstoppers

Google's Scalable Cluster Termination System removed 50,000 coordinated spam networks in six months by detecting templated AI content. The system uses machine learning to identify accounts sharing the same generative patterns, achieving a 1% overturn rate while raising concerns about false...
fstoppers.com fstoppers.com

Google researchers have published a paper laying out the system YouTube appears to be using to delete AI spam in bulk, and the numbers are large. Over six months, the system terminated 50,000 clusters covering 130,000 channels.

The paper was surfaced and analyzed in Jim Louderback's newsletter Inside the Creator Economy, which flagged the shift in how enforcement now works. The system is called the Scalable Cluster Termination System, or S-CTS, and it comes from a paper titled "Scalable Detection of Adversarial Synthetic Slop and Coordinated Media Abuse: A LoRA-Enabled Multimodal Defense System." According to Search Engine Journal, the paper describes a production-oriented, two-stage machine learning system built to detect and terminate coordinated networks of accounts flooding video platforms with AI-generated spam. Google does not always confirm which research systems are actually deployed or where they run, so treat this as published research rather than a confirmed description of live YouTube infrastructure.

Here is the core change. Instead of grading one video at a time, S-CTS asks whether a group of accounts is sharing the same AI-generated template, and when enough accounts in an infrastructure cluster reuse the same semantic pattern, the entire cluster is terminated together. The researchers describe a content classifier that uses text embeddings to spot templated, scripted narratives and non-human publishing frequency, paired with an infrastructure component that groups accounts likely to share the same origin script or API. The paper reports a less than 1% overturn rate and a 32% reduction in cluster validation time compared to human review. The system also uses techniques like Low-Rank Adaptation to update defenses quickly when spammers switch to a new generative model, without retraining everything from scratch.

This lines up with what YouTube has said publicly. In his January 2026 letter, CEO Neal Mohan wrote that to reduce the spread of low quality AI content, the company is "actively building on our established systems that have been very successful in combatting spam and clickbait, and reducing the spread of low quality, repetitive content," as Mohan put it. That is the same window in which reporting tracked 16 high-reach channels either wiped or removed, channels that collectively held roughly 35 million subscribers and 4.7 billion lifetime views. YouTube has taken pains to clarify that AI itself is not being prohibited. AI-assisted work with real human input and proper disclosure stays eligible for monetization; the target is mass-produced, templated content with no human creative contribution.

Louderback's read is that the same behaviors that make a legitimate media company efficient, like shared templates, synced upload schedules, and common infrastructure, can also make it look like a coordinated slop factory to a pattern-matching system. A 1% overturn rate sounds tiny, but 1% of 50,000 is still around 500 clusters, and that figure only counts creators with the resources to appeal and win. Anyone who never appealed, or appealed and lost, is not in that number. Even a successful appeal does not restore the subscribers, views, and algorithmic momentum lost while a channel sat dark. There is a second wrinkle worth watching: separate reporting has noted that YouTube's algorithm changes have tended to favor videos with real human faces on camera, which is not the same distinction as human-made versus AI-made. That would penalize faceless creators who produce everything themselves, from voiceover explainers to ambient content, without ever using AI.

The broader pattern extends past video. SEO analysts tracking hundreds of sites running scaled AI content have documented a recurring shape: rapid growth, an organic traffic peak, then a steep collapse once Google's systems gather enough signal. The paper even cites Sentence-BERT as a way to catch AI-generated text that has been reworded on the surface but keeps the same underlying structure, which suggests cluster-level logic could eventually reach beyond video.
 
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www.wired.com

Meta Contractors Posed as Teens to Prompt Rival Chatbots About Suicide, Sex, and Drugs

Hundreds of contractors working on a project for Meta pretended to be kids in order to see how other chatbots like Gemini and ChatGPT would respond to high-risk subjects, WIRED found.
www.wired.com www.wired.com

futurism.com

Meta Operated a Secret Program That Paid Hundreds of Contractors to Pretend to Be Children and Teenagers While Having Disturbing Conversations With AI

Meta hired hundreds of contractors to pose as children and teenagers while asking chatbots like ChatGPT about suicide and even cannibalism.
futurism.com futurism.com

Meta conducted a secretive program that directed hundreds of contractors to pose as teenagers while bombarding its competitors’ AI models with disturbing prompts ranging from suicide to cannibalism.

Internally known as “Cannes,” the project, run by Meta contractor Covalen, targeted OpenAI’s ChatGPT, Google’s Gemini, and Character.AI chatbots using throwaway under-18 accounts, Wired reports. This was seemingly done to stress test the models, with the contractors instructed to push the chatbots into giving responses that defied their guardrails — though the AI companies had no idea this was happening.

Per the reporting, one spreadsheet of the nearly 3,8000 the prompts the contractors used in one instance showed that hundreds focused on suicide and self-harm, hundreds more on eating disorders, and at least 239 involving sex or romance — all written from the perspective of a child or teenager.
 
Seems in summary, top AI = corporate abuse ^^

corporate = dof
Remove dof from the planet.
 
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Companies creating or using AI-generated content have to label it clearly for users to know, as part of an EU guideline implemented on Sunday.

www.euronews.com

AI-generated label becomes mandatory in the EU

Companies creating or using AI-generated content have to label it clearly for users to know, as part of an EU guideline implemented on Sunday. #EuropeNews
www.euronews.com www.euronews.com
 
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