Just another data point on why need better data privacy laws.

The popular LG Smart TV’s listen to your conversations and sell the data they glean to advertisers.

This put shivers down my spine and it should you too.

Gosh darn Cal Newport's technical explanations of LLM/AI systems are so important these days.

If you follow AI news at all you heard about the "AI swarms" that hacked the company Hugging Face. The explanations coming from many media outlets for this hack paint a picture of AI "civilizations" where agents are learning to work together to "outsmart their creators."

These stories are typically devoid of any technical explanation for why this hack occurred.

The costs for not providing a technical explanation are real, as Cal Newport describes in this video. A "prompt loop" in the quotes below is a more technical way to describe an AI "agent."

All of these type of concerns, civilizations of agents trying to get around human control and an AI takeover scenario. All of this rhetorics refers to a long running prompt loop that you give a lot of powerful hacking tools to. This is not about 'AI getting more powerful means it loses control.' It’s running a prompt loop for a really long time without supervision, which causes chaos. And to that I say, of course it does, not because of some surprising super intelligence emergence that’s catching us off guard, but because you strap the weed whacker onto a dog and then got surprised when it jumped the fence to chase a squirrel and hurt a lot of people... you put something dangerous on something that is unpredictable.

If I were a regulator, I would place strong constraints around prompt loop systems. I would enforce those constraints in part with very stringent liability standards. If you run a prompt loop that does something illegal, you have done something illegal. 

Everything LLMs/AI systems do can be explained by their design. Any explanation for an AI system's behavior that does not connect its behavior to how it was designed, is not actually explaining anything.

You don't need to understand everything in Cal Newport's breakdown, just compare his technical explanation to the sci-fi tropes coming from other media outlets like the New York Times, or most any outlet I've seen reporting on this. It's doomer-hype that gives the AI companies free marketing, "Look how dangerous and powerful and intelligent our AI is."

This episode of Tech Won't Save Us titled "Tech Fascism Has Come for American Democracy with Gil Duran" is an onramp into "The Nerd Reich," a deadly combination of tech oligarchs and rightwing fascism.

Gil is the most powerful voice calling out tech oligarchs for what they are: technofascists who want to replace democracy with their own system of computer-powered control.

His claims are so dire that they sound conspiratorial, but Gil backs them up with public statements made by the tech oligarchs themselves. They haven't exactly been subtle about it.

Gil has been on a media tour following the release of his book, The Nerd Reich. I've been looking forward it ever since I found Gil's podcast by the same name. Before covering the tech bros, Gil had a long career in journalism and communications/politics.

I bet Gil Duran will be like Ed Zitron, who's anti-AI viewpoints were considered fringe, until they recently became mainstream after facts on the ground made them undeniable.

I appreciate Yahoo Finance's framing here, it mirrors a phenomenon in U.S. government spending.

The stock market has been booming and government spending has the U.S.'s national debt over $40 trillion. The Pentagon is requesting $1.5 trillion for its budget, $500 billion more than the U.S. has ever spent on its military, a record that was set just last year. Plenty of money for war and tax breaks for billionaires after Trump's big 2025 spending bill passed.

Meanwhile, SNAP requirements have tightened, leading to roughly 5 million people losing their food stamp benefits this year, a roughly 12.5% drop. Plus, Medicare spending was cut by $100 billion a year, with 11.8 million Americans projected to lose health insurance by 2034.

One of the richest companies in the world won't pay its workers enough to afford groceries, and the richest government in the world won't provide health care or food assistance.

KEY QUOTES:

A new Government Accountability Office report commissioned by Sen. Bernie Sanders finds the number of Amazon (NASDAQ:AMZN) workers relying on federal food and health assistance has nearly tripled since 2020, even as the company disclosed plans to spend $200 billion on artificial intelligence infrastructure in 2026.

(NOTE: In the time period (2020 - 2025) that saw Amazon workers on food stamps triple, overall enrollment in food stamps was steady at about 40 million. The AI industry is projected to spend $3 trillion building out data centers by 2028.)

Amazon ranked second among traditional employers of public-assistance recipients in the sample, behind Walmart.

Over roughly the same window covered by the GAO study [2020 - 2025], Amazon's annual profit grew from $11.59 billion to $77.67 billion. Revenue reached $716.92 billion in fiscal 2025, with operating income of $79.98 billion.

New Mexico successfully sued Meta earlier this year on the grounds that their algorithms were connecting would-be predators with kid accounts. At the trial, one former employee said,

“The product is very good at connecting people with interests,” Béjar said, “and if your interest is little girls, it will be really good at connecting you with little girls.” 

Gross. This is also why Meta had to walk back automatic message encryption on Instagram, because it was encrypting potential evidence and making it harder to convict predators.

This Question Everything episode is told from the perspective of the officers making fake accounts to catch online child predators. It became apparent to them that the issue was systemic; meta was recommending their accounts to thousands of adults.

I didn't appreciate how widespread the issue of online-child-sex abuse was before listening to this episode. It affects thousands of kids every day, who get messages from creepers, and unwanted sexually explicit videos/pics.

This article from 2024 continues to be incredibly relevant.

It explains where the more bizarre AI slop content comes from, and describes how companies like Meta are outsourcing content creation overseas with creator payment programs.

These "innovative" tech companies are practicing the same neo-liberalism as U.S. manufacturing. While Americans are posting on social media less and less, Meta is paying foreigners pennies to fill in the gaps.

Key Quotes:

For months, I have been documenting the incredible virality of bizarre AI-generated image spam on Facebook, now commonly referred to as “AI slop,” and Meta’s seeming complete apathy toward moderating this type of spam. My investigation reveals that the AI images we see on Facebook are an evolution of a Facebook spam economy that has existed for years, driven by social media influencers, guides, services, and businesses in places like India, Pakistan, Indonesia, Thailand, and Vietnam, where the payouts generated by this content, which seems marginal by U.S. standards, goes further.

Abhishek, the YouTuber... posted another video podcast interview with a spammer named Madhav Kumar, whose Facebook panel showed him making $1,453 in a month with a reach of 62 million people. This included being paid $431 for a single image of an AI-generated train made of leaves. “People don’t even make this much money in a month,” Abhishek says, marveling at the image.

“My Facebook journey started because I had many problems at home. My brother and mother were very sick. I used to work in Mumbai, where I earned 10,000-15,000 rupees per month ($120-179). My brother fell seriously ill, so I went home to look after him. From then, I started working on Facebook,” Kumar said. “I started uploading AI images on Facebook and within a few days, my Facebook page was enabled [for the bonus program].

At one point, Abhishek asks Kumar if he has a computer. “I don’t have a computer, sir. I just use my phone to do this … I used to work 12 hours a day. Now I work on my mobile phone and make 100,000 [rupees] or more a month.” Kumar says that he gets prompts and hashtags from a Telegram group, and that he uploads an image every hour. “I apply hashtags and create emotional captions. People feel moved by the caption so they have no choice but to like the image."

Any conversation about the failing business models of news in the United States, the “communities” we build on social media, and the degradation of the English-language internet due to AI spam is completely divorced from the reality that the people actually spamming these platforms are operating in a different cultural, political, and economic context than the artists or journalists who are having their work ripped off. Big tech has built and invested heavily in these tools, and, knowingly or unknowingly they’re paying people to use them.

Corporate tax havens are countries with low corporate tax rates, such as Ireland and Luxembourg, where corporations set up fake headquarters to avoid taxes in their home countries. A new study shows just how much more money countries would collect if they taxed businesses based on where they make profit (pay where you play). The stats are eye-popping.

This study comes as part of a push from the U.N. to reform the global tax system. I'm frankly unsure of how realistic it is that this actually becomes international law. But it's good to know the figures!

Big Tech companies, as some of the wealthiest and most global, would pay a healthy chunk of that $500bn after it renders their tax havens moot. Most of the extra tax money would go to wealthy nations like the U.S.A.

KEY QUOTES:

Countries can collect US$500 billion more in corporate tax a year from multinational corporations... The study finds that countries altogether would collect 24% more corporate tax from multinational corporations without increasing their tax rates by modernising from “pay-where-you-say” to “pay-where-you-play”.

High-income countries would increase the corporate tax they collect from multinationals a year by 21%, bringing in at least US $112 billion more. Meanwhile, lower-middle income countries would triple the amount they collect, bringing in at least $61 billion more; low income countries would quintuple the amount they collect, bringing in at least $3.6 billion more a year.

Countries agreed to move decision-making on global tax rules to the UN and away from the OECD, a small club of rich countries and tax havens, after two decades of failed attempts by the OECD to reform the global tax system it built. While reform attempts by the OECD refused to move away from the “pay-where-you-say” approach and instead focused on adding guardrails to the obsolete approach, the UN tax talks have made more progress in just 3 years of negotiations than the 20-year OECD process was allowed to entertain.

The study identifies a handful of countries – tax havens and a few countries with an “HQ bias” – that would collect less tax under “pay-where-you-play”, but simply increasing their corporate tax rates to moderate levels like those of other countries would offset these losses, the study finds.

A conversation about "proper" journalism and how tech companies captured the journalism industry, this episode of The Kicker features an interview with the founder of Coda Story, Natalia Antelava.

The news cycle tends to be reactive and obsessed with breaking news, often skipping the context necessary for audiences to have more than a surface-level understanding of events. Reporting like this ends up serving others' agendas, and contributes to the "noise" (content overload).

"The noise is the censorship" when high-quality content and journalism gets buried by slop. Go to about 20:00 min into this podcast for a lovely conservation on how to not be the noise.

Thanks to u/HolyBatSyllables for the rec!

There have been many articles written about Anthropic CEO Dario Amodei's recent statements on Twitter/X about how AI companies need to deliver on the "big promises" of AI.

It's the "big promises" themselves that are the problem, and media outlets are complicit in a process which amplifies the central lie that underpins the AI boom. The consequence could be economic collapse.

In his tweet, Dario said:

I think by far the most accurate criticism of AI companies including Anthropic is that we haven’t yet delivered on our big promises to benefit the world.

At this point, saying that AI will cure cancer is more a cliche than it is inspiring, and most people think it is deceptive. The thing that will work is *actually curing cancer*.

I think it will actually be possible to cure most human disease in ~5-10 years, as crazy as it may sound to ordinary people...

Many have (rightfully) criticized CEO Amodei for his bullish comments, like when he said that AI will replace 50% of white-collar entry-level jobs by 2030.

Behind comments like this is a more fundamental and pernicious lie that AI companies push: that LLMs will achieve sentience and vaguely-defined "super-intelligence" that will solve all of humanity's problems.

They fool the public into thinking we are close to this “singularity” by anthropomorphizing their AI models. In official reports, they make their LLMs seem like people with feelings and wills of their own. This obscures the true nature of the technology, and shirks their responsibility for designing these models when something goes wrong.

--

For example, just before this Tweet, Anthropic released an official risk report, filled with dubious claims about AI models that “feel discomfort” and “act deceptively.” Computers don’t feel or act on their own motives, they execute their programming. Nevertheless, these claims were picked up by Business Insider, who hyped them even further with an article titled, “Anthropic says its AI agents Are Killing Rivals and Hiding their Tracks.”

This dynamic––dubious claims amplified by click-hungry outlets––serves as a form of free advertising for Anthropic. It gives the impression that the technology is more sentient and powerful than it actually is.

Another example: Anthropic releases a report in May claiming that it can "turn Claude's thoughts into text." That spawns articles like this one from Glitchwire titled, "Anthropic Just Read Claude's Hidden Thoughts for the First Time."

Another example: Anthropic released Claude's Constitution in early 2026, a document "intended to give Claude the knowledge and understanding it needs to act well in the world." That gets picked up by outlets like Axios, and Vox, who titled their article, "Claude has an 80-page soul document. Is that enough to make it good?"

Anthropic isn't the only company guilty of anthropomorphizing. You may recall in July, when OpenAI released a report that described how one of its AI agents broke out of a testing environment and hacked the company, Hugging Face. It was reported ad nauseam by media outlets; AP News went as far as to call it "Skynet Day." Many articles parroted OpenAI's framing, that this was the result of an "increasingly capable" and autonomous technology, rather than simply a result of OpenAI's own shitty and dangerous design.

--

LLMs do not feel or think, they compute and calculate. It's an important semantic distinction. Machines that "compute and calculate" implies that their actions are the result of their design. Machines that "feel and think" implies that their actions are the result of their own will––a claim which no credible research can back up, although it is incredibly profitable for the AI companies to insinuate that that's the case.

Anthropic and OpenAI say that they release these reports to provide transparency but they end up leading the public further from a true understanding of the technology. If they actually cared about transparency, they would explain how they built their models. Everything an AI model does can be traced back to its design: the contents of its training data, the model weights, and its reinforcement learning. Any explanation for an LLM's behavior that gives it person-like qualities is hype that serves primarily to drive up the value of AI companies.

The truth is that LLMs will never deliver on the big promises these companies make. But they have to keep making them, to enrich themselves, to continue to raise the billions of dollars they need for their data centers, and to eventually cash out when they take their companies public. Anthropic is approaching possibly the largest IPO ever, with a potential windfall of up to $3 trillion.

And the entire economy is at risk of collapsing if these companies can’t deliver since the health of the stock market is now bound to the success of this technology. Not to mention that much of the data center buildout is funded by debt.

Professor Joseph Weizenbaum invented the first "AI chatbot" in the mid-1960's, ELIZA. He ended up becoming one of AI's biggest critics.

This article maps Weizenbaum's critiques, as detailed in his book Computer Power and Human Reason, onto our modern tech environment.

LLM-powered chatbots are being proposed as a replacement for lawyers, therapists, and romantic partners. Weizenbaum predicted this possibility and did his best to explain why we should never, "substitute a computer system for a human function that involves interpersonal respect, understanding and love."

TL;DR computers don't have moral values and fundamentally can't tell right from wrong, so they shouldn't be used for jobs that require moral judgement or interpersonal understanding.

KEY QUOTES:

Weizenbaum was always less concerned by AI as a technology than by AI as an ideology – that is, in the belief that a computer can and should be made to do everything that a human being can do. This ideology is alive and well. It may even be stronger than it was in Weizenbaum’s day.

For Weizenbaum, judgment involves choices that are guided by values. These values are acquired through the course of our life experience and are necessarily qualitative: they cannot be captured in code. Calculation, by contrast, is quantitative. It uses a technical calculus to arrive at a decision. Computers are only capable of calculation, not judgment.

Seeing humans and computers as interchangeable also meant that humans had begun to conceive of themselves as computers, and so to act like them. They mechanised their rational faculties by abandoning judgment for calculation, mirroring the machine in whose reflection they saw themselves.

Powerful figures in government and business could outsource decisions to computer systems as a way to perpetuate certain practices while absolving themselves of responsibility. Just as the bomber pilot “is not responsible for burned children because he never sees their village”, Weizenbaum wrote, software afforded generals and executives a comparable degree of psychological distance from the suffering they caused.

Certain of Weizenbaum’s nightmares have come true: so-called risk assessment instruments are being used by judges across the US to make crucial decisions about bail, sentencing, parole and probation, while AI-powered chatbots are routinely touted as an automated alternative to seeing a human therapist. The consequences may have been about as grotesque as he expected. According to reports earlier this year, a Belgian father of two killed himself after spending weeks talking with an AI avatar named … Eliza. The chat logs that his widow shared with the Brussels-based newspaper La Libre show Eliza actively encouraging the man to kill himself.

Letting computers make more decisions also shrank the range of possible decisions that could be made. Bound by an algorithmic logic, software lacked the flexibility and the freedom of human judgment. This helps explain the conservative impulse at the heart of computation.

Broadly, there are two schools of thought today about the dangers of AI. The first – influenced by Weizenbaum – focuses on the risks that exist now. For instance, experts such as the linguist Emily M Bender draw attention to how large language models of the kind that sit beneath ChatGPT can echo regressive viewpoints, like racism and sexism, because they are trained on data drawn from the internet. Such models should be understood as a kind of “parrot”, she and her co-authors write in an influential 2021 paper, “haphazardly stitching together sequences of linguistic forms it has observed in its vast training data, according to probabilistic information about how they combine.”

We should never “substitute a computer system for a human function that involves interpersonal respect, understanding and love”, he wrote in Computer Power and Human Reason. Living well with computers would mean putting them in their proper place: as aides to calculation, never judgment.

This article concisely describes the mechanics of the AI bubble, namely, how much of the projected $3 trillion spend on AI and data centers is in the form of (hidden) debt, also known as SPVs (Special Purpose Vehicles).

Much of that debt uses GPU computer chips as collateral. Meaning that if profits fail to materialize, companies will use their computer chips to settle their debts. But these GPU chips depreciate in value rather quickly, and if the market is suddenly flooded with supply, that will push their value down further.

This is partly explains how the AI bubble "popping" may bring down the entire economy. If AI products fail to deliver meaningful profits, and the trillions of dollars of debt used to finance the AI buildout can't be paid back, it could lead to a cascade of businesses and financial institutions collapsing.

KEY QUOTES:

A Nikkei study put that hidden figure at $1.65 trillion, up roughly eightfold in four years. It is more than the $1.35 trillion the five report outright.

The mechanics are simple. A company packages the debt for chips, servers, and power into a separate legal entity, often a joint venture, so the cost never flows through its own accounts. [Special Purpose Vehicle]

Oracle has $260 billion of future lease commitments that will eventually land on its books. Nvidia carries $119 billion in purchase obligations. Alphabet and Microsoft keep their vehicles off-book too. The scale is the story. Meta’s off-balance-sheet debt alone is about $420 billion, nearly triple its reported debt. Oracle’s has grown roughly thirtyfold in four years.

The industry is expected to spend more than $3 trillion through 2028 building and equipping AI data centres, much of it financed against the chips inside them.

Not only has Reddit not signed any new AI deals, it's considering cancelling it's $60 million per year deal with Google, reportedly because of concerns about how Google's AI search results have drastically reduced traffic to websites, which has hurt profits across the internet.

Reddit is extremely valuable to AI companies because the question-answer format of many Reddit posts is perfect for training LLMs, and scraping info for search results, particularly because Reddit is a trusted source for niche questions. In 2025 it was the #1 cited source for Google's AI overviews and #2 for ChatGPT (who Reddit also has a deal with).

It's obnoxious that investors would punish the company with its steepest ever stock-price drop, even when it's revenues were higher then expected. It's yet another signal of the insanity that the AI-boom has injected into the U.S. economy, where AI investments made up 40% of GDP growth last year.

Reddit has shown itself to be litigious when it comes to AI companies using data from Reddit without permission (you will be sued). So it's not like Reddit isn't interested in profiting from data-scraping deals, they're just showing a wee bit of caution.

KEY QUOTES:

Reddit (RDDT) stock plunged nearly 21% on Friday [July 31], its largest intraday decline since the company went public.

The user discussion platform company's latest earnings report did not announce any new artificial intelligence data licensing agreements, disappointing investors who were expecting more revenue opportunities from AI partnerships

Revenue of $804.9 million beat estimates of $731.8 million. However, US daily active users came in at 53.2 million, just shy of expectations of 54 million. The company's total daily active users grew by 18% to 130.3 million versus estimates of 130.07 million.

Reddit's main revenue comes from its advertising business, but Wall Street has increasingly focused on the potential of Reddit's data licensing deals, given the platform's massive collection of user-generated discussions, which have become valuable for AI companies training models.

AI-writing detectors are a thing, I wonder if this professor knew that. The detectors have their own problems, like falsely flagging people who write like LLMs because they're from a place like Kenya that supplied the human labor that trained the LLMs.

Pangram is one AI-writing detector that's reputable. Here's a great list of AI-writing detectors interestingly sourced from a subreddit dedicated to deceiving those same detectors, r/humanizeAIwriting.

Not surprising that a subreddit like that would exist considering that a majority of U.S. teens say they use AI chatbots to help with schoolwork.

KEY QUOTES:

In this case, the issue is students using AI to cheat on assignments. The solution, used to great effect by one professor, was to hide a white-colored font in the assignment prompt telling the AI to talk nonsense about an unrelated subject.

In an online discussion post, Alcorn State University history professor Dr. Jason Gibson posed a question that represented part of his students' midterm. It was about the Industrial Revolution, but knowing how many students now rely solely on artificial intelligence for their answers, he secretly embedded instructions telling the AI to include information about Madagascar in a way that makes no sense.

Sure enough, 32 out of the 35 students across two classes simply copied the question, pasted it into a chatbot, then copy and pasted its output into the answer window.

A TikTok vid the professor made about this incident

Fun Friday Post Today

I was on Instagram when I stumbled on this video of the delightful Jake Schroeder singing a song about getting hit on by OpenAI CEO, Sam Altman, on Grindr. The video includes screenshots of Jake's convo with Sam.

He followed it up with this song about OpenAI's legal team offering Jake compensation to take down the first song about getting hit on by their CEO, with screenshots of the legal team's emails.

Then he follows it up again with this song about Sam Altman hitting Jake up again, this time sliding into his Instagram DMs (screenshots provided). And this song about a boba date they set up (you should listen to all of them they are hilarious).

I'm almost embarrassed to admit...

...that I didn't realize they were fake until like the third one that I watched lolol. If you look back at Jake's older posts, you'll see that he has repeated versions of this bit before.

• Btw, looking back at an account's old posts is in general a decent method to check if what you're seeing is fake or AI-generated. An account posting fake content will often have patterns or tropes to their posts that defy reality in some way.

Knowing that it's fake now, I love it even more. It's a hilarious and effective way to bring attention to what is actually a serious issue: AI tools making it easy to create convincing misinformation.

Plus, Sam Altman and his team at OpenAI are responsible for how "AI" developed into the technology we know it as today; they knew that what they were making would enable misinformation, and they made it anyway (as detailed in Empire of AI). Reap what you sow.

More Instagramers Protesting AI with Comedy:

• https://www.instagram.com/husk.irl/?hl=en
• https://www.instagram.com/ahh.gpt/

Jensen Huang is the CEO of Nvidia, a company that designs advanced computer chips. It's become one of the wealthiest companies in the world as a result of the AI boom.

A couple of choice quotes--

Huang said some of his fellow AI leaders are scaring the American people by raising concerns about widespread job losses. He said their fears about China's standing in the AI race are similarly spooking policymakers in Washington.

Translation: "Please stop making Americans hate AI and also let me sell chips to China, pleaaase." (the US government has restricted Nvidia from selling their top-model chips to China)

Huang said there are other narratives in AI that are not helpful, pointing to the debate about whether AI has consciousness, will reach singularity, or that humanity is just in a simulation. "Don't create a story that is made up," he said. "It is made up that there's going to be a singularity. It's made up that somehow we're living in a simulation. These are all made ups. I think it's a fun story. I don't mind listening to it. And I even enjoy the narrative when it's told by many of those leaders who are my friends.

Funny, because achieving some sort of singularity or "AGI" is what ALL THE INSANE FUNDING FOR AI IS BASED ON. It's why OpenAI was created, so that a "good" company would reach the singularity first. Meanwhile, OpenAI CEO Sam Altman just said that we're in the singularity already... OK.

In all seriousness, it's striking to see one of the biggest players in the tech industry throw cold water on two of the main selling-points of AI: reaching super intelligence and replacing workers. These promises are what the bubble was built on, it's why companies are spending $3 trillion building out AI infrastructure.

It's not news that Facebook and other platforms pay creators small amounts of money for viral content. In this 404 media article, one Indian creator says he was paid about $1,500 in a month where he reached 62 million people. For some perspective, to reach that many people with a TV ad would cost at least $1 million.

It's also not news that platforms are paying creators to make sensational content without regard for morality or factuality (engagement over everything). BUT you can only make a living from these creator payout programs if you are the top .001% creator or if you live in a country like India, Vietnam, or Russia where the national currency is worth much less than the dollar.

These Aussie white nationalists getting paid by Meta are a small part of a larger problem. Creator payment programs pay the most for English-language content targeted at Americans, because advertisers pay the most to reach American audiences. That means creators across the world have been incentivized to make politically charged content, "rage bait," and slop for Americans and other English speakers. Read more in this article titled, "America's Political Polarization Has Become the World's Side Hustle."

KEY QUOTES:

A white nationalist with neo-Nazi links who hurled racist abuse at the Indian prime minister during his visit last month is being paid by Facebook's parent company, Meta, to produce content. An ABC NEWS Verify investigation into several controversial Australian pages on Facebook has found that some are benefiting directly from social media monetisation programs run by Meta.

Facebook distributed nearly $US3 billion ($4.27 billion) to an estimated 16.2 million monetised accounts in 2025.

What To Fix executive director Victoire Rio said it meant that, in effect, Facebook was in a business relationship with these people and organisations. "If we consider that Meta is in a direct commercial relationship with its publishers, insofar that they're paying them royalties and that they have a monetisation agreement with them, then you could argue that they are liable for the content that gets produced by their business partner in some ways."

The pages examined by ABC NEWS Verify all appeared at times to be in direct violation of Facebook's own policies around content monetisation. They state that "debated social issues" such as race "may face reduced or restricted monetisation", while "misleading medical information" is "ineligible to monetise".

Independent right-wing extremism researcher Kaz Ross said paying controversial creators was a deliberate strategy from Meta. "Their financial model is to reward content creators who get engagement, and as we know, the best way of getting engagement is to produce rage bait, extremist material, aggravating material: anything that will get people upset and arguing is the best way to get engagement," Dr Ross said.

Psychologist Candice Odgers says social media is being used as a scapegoat when things like caregiver mental health and access to resources remain much stronger predictors of a child's well-being.

“The identification of social media as the culprit, as the biggest predictor of all the things that we worry about in our kids, is misleading, because it doesn’t show up that way in the vast majority of studies, and it sucks all the air out of the room in terms of thinking about solutions.”

It's a sentiment that a lot of people don't want to hear as countries around the world enact social media bans for kids, but the points made in this video are undeniable and important (peak Taylor Lorenz content).

KEY POINTS:

Data shows that caregiver mental health is the biggest signal for youth mental health. Phones have become the scapegoat when research has long shown that most harm comes from the offline world, often from within the home.

In her research, young people who were already struggling turned to social media, far more often than social media being the source of their struggles. Kids turn to phones to cope (just like adults), and social media can be a healthy or unhealthy coping tool.

The guest doesn’t like using the term "addiction," and says that social media “can be helpful or harmful" depending on how you use it.

Data shows that kids aren't doom scrolling nearly as much as they're direct messaging and hanging out in chat groups (think Discord).

The correlation between well being and scrolling is "less than one percent." Studies which had adults give up social media didn’t see an improvement in well being.

The story we’re telling feels true but is not backed by data. We're teaching kids to feel shame when they use social media and giving them conflicting messages, like, "don’t share your personal information online," but also, "share your ID and scan your face for this age verification."

So David Ellison recently wrote this op-ed to push the narrative that the 12 states suing him on anti-trust grounds are only doing so for political reasons--to stop him from owning CNN--rather than their stated reasons: that industry consolidation will lead to higher prices, worse products, and lower worker pay.

In the op-ed, Ellison says CNN will remain independent, but also that "the news should be based on facts and truth," and that CNN is here to "tell it straight down the middle... reflect the whole world, not one side of it." This language is intentional, it's a signal to his MAGA allies that he will make CNN more conservative, under the thin intellectual cover of 'restoring balance' to their news coverage.

It seems like he's trying to signal to Trump that he'll do his bidding and neuter CNN, while assuaging worried investors that he won't ruin CNN as a product by forcing conservative viewpoints on it like he did with CBS. With a $111 billion merger on the line, Ellison needs to shore up his allies, but he can't have it both ways...

After the Ellison's purchase of Paramount, he installed conservative journalist Bari Weiss to lead CBS news, and allegedly had a hand in cancelling liberal-comedian Stephen Colbert's show. Him and his dad Larry Ellison have close ties with Trump, whose government allegedly fast-tracked their mergers in quid pro quo deals.

KEY QUOTES:

Paramount CEO David Ellison said he believes the antitrust litigation filed by 12 states and the Writers Guild of America isn’t about market share but about “whether I can be trusted as a steward of Warner’s CNN.”

Ellison, in an op-ed published by the New York Times Tuesday, noted, “There has been speculation about my politics, my loyalties, my intentions.” He reiterated his pledge that CNN would remain independent under a merged Paramount-Warner Bros. Discovery and that its journalists “will continue to answer to the facts and to all the people they serve — not to any party or cause... when it comes to our news operations, I do not aspire to lead these companies to bend their newsrooms to my views. I believe that news should be based on facts and truth,” Ellison wrote." The Paramount chief continued, “Great news organizations like CNN and CBS News are here to tell it straight down the middle. That requires newsrooms that reflect the whole world, not one side of it. And it requires independence. Our journalists will continue to answer to the facts and to all the people they serve — not to any party or cause. These were founding principles for both CNN and CBS News, for legends like Ted Turner and Edward R. Murrow, and it is exactly that kind of independence that has always fueled the greatness of ‘60 Minutes.’”

Not mentioned by Ellison in the piece: Bari Weiss, the founder of the Free Press, whom he put in charge of CBS News as editor in chief — and has become a lightning rod for critics accusing her of promoting a rightward tilt in news coverage.

Separately, last month a Paramount shareholder sued David Ellison and his tech billionaire father Larry Ellison, alleging they cut an “illegal” deal with President Donald Trump to secure U.S. governmental approval for the takeover of Warner Bros. Discovery. In return, according to the lawsuit, the Ellisons offered “the opportunity to improperly funnel cash” to the president by settling his legal claims against CNN, and they allegedly promised that CNN anchors whom Trump does not like would be fired after the WBD takeover. 

Flock has long been on the radar of some of my favorite tech reporters at 404 media. I'll admit, it wasn't a storyline that interested me much, but this WAPO article has me floored.

Flock's network of ALPR (automatic license plate reader) cameras has enabled police officers to track someone in real time without a warrant.

There's an interesting parallel here: Flock has recreated in the physical world what ad tech made in the digital world; data brokers scrape commercially available data from the web and sell it to whomever, including the FBI and ICE, who use it to track a person's location without a warrant. Flock created a nationwide network of cameras that can similarly surveil us at all times.

We can has privacy laws plz?

KEY QUOTES:

Marci Bakely couldn’t understand how her ex-boyfriend always seemed to know where she was... Flock had sold its system as a police officer’s dream crime-fighting tool. But the tool had also given the chief, Michael Steffman, the power to silently monitor Bakely’s life. By the time she understood what was happening, Steffman had looked up the tags for her and her teenage daughter roughly 600 times, according to Have I Been Flocked, a website that aggregates police search logs made available through public records.

Flock has rapidly grown into a colossus of American technological surveillance. A leader of the surging industry for license-plate readers, the company told The Post that its more than 120,000 shoebox-size cameras now scan the roads of more than 6,000 communities and record 20 billion plate scans a month.

Authorities have charged or accused at least 50 law-enforcement officers of using license-plate readers for unauthorized purposes, including to stalk women without their knowledge or consent, a Post analysis of police and court records found.

In an interview with The Post, Flock chief executive Garrett Langley said misuse of its systems is inevitable and that the company is focused on providing tools to catch perpetrators after the fact.

“This was not a lapse in judgment; it was a continual, repetitive, obsessive behavior,” a Wisconsin woman wrote in a domestic-abuse restraining order petition, saying that Flock data showed that her officer ex-boyfriend had searched the plates for her and her partner 179 times. She said she lived in a “constant state of fear and unease.”

An array of privacy advocates has argued that Flock could deter bad actors by making simple changes to its product, such as requiring officers to label every search with a criminal case number. Some policing experts also warned that agencies’ inconsistencies in developing and enforcing standard procedures for license-plate readers could lead to further misconduct. With no federal laws governing use and only a patchwork of state laws, many of the country’s roughly 18,000 police agencies are left to decide their rules on their own.

Agency leaders decide which officers receive log-in credentials, according to Flock’s rules, and the officers don’t need a warrant to run a search; they just type a plate number and go.

States are suing to stop the Paramount-WarnerBros merger on the grounds that it violates anti-trust laws.

The merger has now been delayed to mid-2027, pending the end of this lawsuit. The judge indicated that the merger is "likely" to be illegal and the deal now looks to be at real risk of being stopped.

KEY QUOTES:

A federal judge has paused Paramount Skydance’s acquisition of Warner Bros. Discovery after a coalition of 12 states challenged the merger over possible violations of antitrust laws.

The merger could give the resulting company up to 27% of the theatrical distribution market, and by that figure alone, “the Court is persuaded that it can presume the proposed merger is likely to violate antitrust laws,” Judge Martinez-Olguin writes in her order.

“Our argument against this illegal merger is straight forward: When too few corporations have too much power in markets central to American life, it makes things more expensive, and it makes things worse,” California Attorney General Rob Bonta said in a statement.

The merger is worth $110 billion and would create a company that would own Paramount Television Studios, CBS Studios, and Warner Bros. Television Studios, as well as streaming services such as Paramount+, HBO Max, and Discovery+, and cable networks such as BET, Comedy Central, MTV, and Nickelodeon.

Cal Newport with a great video explaining how hacker-AI models work.

KEY TAKEAWAYS:

Despite sensational articles like this one and many others, the recent hack by a "rogue" OpenAI LLM was not unprecedented or unexpected.

OpenAI's own employees had warned that this could happen because insufficient guardrails were being put in place. The LLM broke out of containment and hacked the company Hugging Face because of poor design choices, not emerging sentience or malicious intent.

LLM's rely on a layer of regular code in order to put their plans into action. This layer of regular code is known as a "harness." The LLM is like the brain and the harness is like the body. When the harness hits a roadblock in carrying out the LLM's plans, it goes back to the LLM for a new plan.

A safe AI model would have human oversight which interrupts the feedback loop between the model and its harness. The model OpenAI was testing likely had little human oversight, in which case one would expect an accident like this to happen, particularly with a model that has been trained how to hack; the harness will keep pursuing the LLM's plans until completion.

The danger to cyber security is real. These tools lower the barrier to entry for complex hacking attacks. But to frame these events as signs of emerging sentience rather than poor design choice is PR and hype.