Technology

Tech workers at The New York Times began to organize in 2018. The campaign to form a union originated in a conversation between two workers, Kathy Zhang and Goran Svorcan-Merola, and proceeded underground through 2019 and into 2020, moving cautiously from one person to the next. In the summer of 2020, however, amid the uprising following the police murder of George Floyd, the Times solicited and published an op-ed by Republican senator, Tom Cotton, calling for the deployment of the National Guard to suppress protestors in New York. A number of Black journalists risked their employment by speaking out publicly in protest. In solidarity, hundreds of employees from across many departments of the Times walked off the job.

The motion and solidarity generated by that action gave tech workers the momentum to go public with our union drive. We reached a majority of support in tech departments by the spring of 2021. It is difficult to imagine that we would have reached this stage in the absence of the walkout. It was an early lesson in the importance of both methodical, committed organizing and a willingness to shift course in moments of upsurge, without guarantees, a lesson only imperfectly remembered when we struck in 2024.

Despite Times management’s fierce anti-union campaign, we won union recognition in spring 2022, with a landslide 82 percent vote in favor. The more than 700 engineers, designers, data scientists and analysts, product managers, and project managers who make up our union include everyone who works on the Times’s website and mobile apps, digital products widely understood to be essential to the Times’s unique financial success among news companies.

In striking, we discovered the intransigence of management and new strength of our own. We reclaimed our values from our employer, and we learned how our power as workers is made: When we take action, we build capacity for action.

This year, the battle for song of the summer has been eclipsed by a much more complicated – some would even say disturbing – debate. That’s because we find ourselves asking not “What’s the song of the summer?” but rather “Is the song of the summer even real?”

Among the top contenders for the title is Fenix Flexin’s Rubberz, a single released in June that has ascended to No 58 on the Billboard Hot 100 and racked up more than 35m Spotify streams. It’s not the sort of fare Fenix usually cooks up. The artist is known for his trap music as part of the rap duo Shoreline Mafia, but Rubberz is a mildly noirish, 80s-inspired synth-pop track featuring a voice nothing like his. The song has drawn comparisons to Morrissey, but it more closely resembles Men at Work’s Down Under, or a Weird Al Yankovic parody of Men at Work. It’s pretty awful. But more importantly, it has an uncanny quality to it. It sounds off.

Almost immediately after it came out, skeptics accused Fenix of employing artificial intelligence to create the track, if not entirely at least partly. He and the song’s credited producer, Purps on the Beat, initially denied it, with Fenix insisting that he’d just used Auto-Tune and a phoney British accent. The kerfuffle culminated this month when indie DJ-producer Medasin posted a video that he said proved that Rubberz had been made using the free generative music tool Treblo.

Medasin then captured himself giving Treblo prompts to pump out his own track. Its sound and lyrics were eerily close to those of Rubberz. Fenix rejected Medasin’s claims, posting what he said were clips of the song’s stems, or its fundamental components, but then Medasin posted a rebuttal of him demonstrating how AI songs, too, can be broken down into stems. A few days later, Fenix finally admitted to using AI to make Rubberz, writing: “never said I didn’t use AI, i said it had nun to do w recording process.”

From xcancel:

The team behind uAssets, the filter lists used by uBlock Origin, says it will stop fixing ad-blocking issues on Facebook. They say Facebook keeps finding ways around new fixes, making the work increasingly difficult to sustain.

This won’t affect AdGuard’s Facebook filters. We maintain our own rules and will continue updating them.

There’s nothing to celebrate here. It shows how hard it is for small, often volunteer-run teams to keep up with tech giants — and how important their work is for everyone who wants more control over what they see online

uBlock Origin offers some AdGuard rule sets, so I don't know exactly what this means for existing uBO users.

A New Mexico judge yesterday ordered Meta to pay $567 million for a fund that would alleviate the “public nuisance” created by its social media services. The order to pay for youth mental health care is in addition to $375 million in civil penalties that a jury ordered Meta to pay earlier in the same case.

The appeal of Roku is that, whatever you happen to want to watch, there will almost certainly be a live channel for it. Just want to watch Little House on the Prairie? There’s a channel for it. Just want to watch Duck Dynasty? There’s a channel for that too. Purely want to watch nothing but local news from Wisconsin? Guess what: there’s a channel for that too.

But despite this wealth, a section of the population was still to see its needs fulfilled. What about people who hate plot and vision and the sight of people speaking convincing dialogue that synchronises perfectly with the movement of their lips? What about the people who just want to watch an unyielding torrent of eerily weightless nightmare fodder? Well, good news. Roku has finally caught up.

It was reported last week that Roku launched the Fairground AI Creator TV channel, the first free, all-AI streaming channel that pulls content from roughly 100 AI creators around the world. Early reactions were, to put it mildly, not great. The Verge compared it to eating from a trough, while Futurism called it “bottom-of-the-barrel slop”.

In truth, you will not watch Fairground AI Creator TV, and that’s sort of the point. This is television with vanishingly low production costs. Compare an hour of this cheap slop with, say, the tens of millions of dollars it takes to produce an episode of Stranger Things, and you’ll soon understand why executives might find the prospect irresistible. In this landscape you don’t need breakout hits, just enough stoned and curious students at 3am to turn a profit.

That said, I have actually just spent a few hours watching Fairground AI Creator TV, more out of self-hatred than anything else, and it would appear that the early reviews are right. On the plus side, the channel is evidence that artificial intelligence has come on in leaps and bounds over the last couple of years. Had this been attempted in 2023, we would have had a 24/7 feed of mutant Will Smith choking down handfuls of writhing spaghetti, and everyone would have vomited themselves dry. Generally speaking, what Fairground has to offer is much better.

However, it is still awful. Categorically, catastrophically awful. The channel doesn’t so much offer shows as a drifting dreamscape of bad ideas rendered as horribly as possible with no thought paid to scheduling. At one point on Wednesday, a shrill high-frequency anime gave way to a long and staid German-language short about Nazi bureaucracy. After that came a sort of Gladiator ripoff that had all the dynamism of an exhibit you’d see at the fourth-best museum on a poorly planned family holiday.

The first thing to know about Cyberselfish, the chillingly prescient 2000 book about Silicon Valley that its author, Paulina Borsook, says “ruined my life” and caused a 25-year-long “curse” to befall her, is that it’s very, very funny. Cyberselfish, which Borsook cannot stand to name and instead calls “TDB” (short for “that damn book”), is a classic, fish-out-of-water tale of a journalist investigating a strange land. Except, in her case, as a California native, it’s the work of a fish regarding an invasive species that suddenly befouled the tank she’d been swimming in her whole life.

Her observations from the murky milieu of the dawning tech world are as hilarious as they are depressing; early in the book, for instance, Borsook recounts what happened after she wrote a satirical guide for the website Suck.com on dating men in tech. (Do profess Ayn Rand fandom, “don’t tell him about your best friend, the urban planner, who uses HUD money to develop low-income housing.”) After the piece was published, emails cascaded into her inbox.

“Guys were positive that I had been writing about them,” Borsook wrote in Cyberselfish. “Or about someone they knew (I hadn’t written about anyone in particular). Guys wanted to meet me for coffee, as I was obviously their dream girl (it was a joke, guys, and no, thank you). At last! A woman who understands me! No, more modestly, I was just someone who had been paying attention.”

Borsook, an author and poet, began working in Silicon Valley in 1981, first as a technical writer for software companies. As she freelanced for various tech outlets and from her perch as a contributing writer to Wired in its earliest years, she began to piece together, as she put it in Cyberselfish, “a picture of an emergent social and political subculture, one that can seem dangerously naive and, at its worst, downright scary.”

Today, just a glance around will confirm that said subculture is no longer “emergent,” but horribly, frighteningly, society-destroyingly dominant. Fittingly, Cyberselfish will be reissued on September 15 by Tin House, an imprint of the independent publisher Zando. The three-decade plus history of the book traces back through a piece she wrote for this very magazine where she began to lay out its thesis. That essay, also titled “Cyberselfish,” ran in our July/August 1996 issue below a crystal clear subhed: “Silicon Valley, one of the country’s biggest recipients of government largesse, would like to bite the hand that feeds it.”

Youtube Description:

With billions pouring into AI based on its promises, Jon is joined by Cory Doctorow, author of “The Reverse Centaur's Guide to Life After AI,” to separate the hype from reality. Together, they examine how the AI industry relies on inflated expectations, question what AI can genuinely do and whether that even matters when selling a product, and explore how the technology is supercharging problems already embedded in our society, including surveillance, labor exploitation, and corporate consolidation. Plus, Jon answers listeners’ questions about 107 days until the midterms, the Fox Administration, Punch vs. Jimothy.

Meta was paying out-and-out neo-Nazis to post on Facebook, an investigation from Australia’s ABC News found.

These pages and individual creators posted content that appeared to be in clear violation of Facebook’s own hate speech policies. Nonetheless, they were able to earn money on their posts through the platform’s “Content Monetization” program — which is invitation-only.

One receiving payouts from Meta was Hugo Lennon, a known far-right agitator and white nationalist with ties to neo-Nazi groups. Lennon was taken away by police for hurling racial abuse at India’s prime minister Narendra Modi during his stay at a Melbourne hotel, and is believed to be one of the organizers behind an “anti-immigration” march on a sacred Indigenous site in the city last year.

Lennon, in other words, was a known quantity, and Meta should’ve been under no illusions about who they were paying to drive engagement on the platform. Still, the investigation found that he’s been receiving payments from Facebook since September 2025.

Meanwhile, the Facebook page for the Australian white supremacist site The Noticer has been making money through the revenue program since November 2025. Underscoring how much Meta has dropped the ball on this one, even X — owned by Elon Musk, who performed two suspiciously Sieg Heil-looking salutes back in 2025 — has banned The Noticer for violating its “hateful profile policy.”

cross-posted from: https://lemmy.dbzer0.com/post/73628131

The human brain has evolved to learn from specific instructors. When a child hears a gentle spoken word or a soothing lullaby from another person, when their cry is responded to, their brain lights up. Nurturing interactions, or what child-development experts call “serve and return” exchanges, help shape and strengthen the 1 million new neural connections taking place in a child’s brain every single second. Every time a child cries or serves up a bid for attention and receives a caregiver’s response, that back-and-forth helps build the circuits underlying their communication, learning, and emotional well-being. No other input, not even Johann Pachelbel’s Canon in D performed by the Berlin Philharmonic, is capable of activating the neural circuitry the way human interaction does.

Until now. Generative AI may be the first technology in history sophisticated enough to mimic the social interactions that build our brains. Research has demonstrated that infants as young as six months old respond physiologically to interactions with humanoid robots in ways that mirror their response to live humans; another, small-scale experimental study recently found that, after young children interacted with a chatbot, most of them for the first time, they asserted that the AI could perceive the world with humanlike senses and understand and learn as people do.

This technology is already showing up in children’s lives. The talking plush robot that purports to be a child’s best friend is obviously driven by AI, but many parents may not realize that their Amazon Echo recently received a software update that converts the Alexa voice assistant into a full-blown chatbot, using the same fundamental tech that fuels ChatGPT; toddlers asking for information about animals or a joke or a bedtime story may quickly find themselves in the habit of engaging socially with a large language model.

As a pediatric surgeon, researcher, and technologist who has spent decades studying how children’s brains develop, I am concerned about these technologies rolling out and being used by children in the home and at school before we have a full sense of their safety and what they do to young minds. And I am compelled to point out what we do know about human development: that human connection, in all of its imperfection, is foundational to brain development. It can’t be engineered or recovered later.

cross-posted from: https://lemmy.dbzer0.com/post/73569181

TL;DR: In the last year, the Wikimedia Foundation has fired several union organizers, including those that worked on the Community Tech team - a team dedicated to building features for the volunteer community that edits Wikipedia.

As the Wiki Workers Union tries to get the Wikimedia Foundation to recognize their union, it is worth remembering that this is not the first time that the Foundation has worked against the community.

Wikimedia Enterprise is a betrayal of the volunteer movement community of Wikipedia editors, as the Wikimedia Foundation is providing privileged access to big tech AI companies to the Wikipedia corpus - a body of work that the Foundation does not own.

Movement volunteer communities contributed to Wikipedia under copyleft licenses - licenses that work to ensure that the work remains free (as in speech). The big tech AI companies do not license derivative works under copyleft licenses and often do not even attribute where the works came from.

This means that volunteers are working for big tech for free, and the Wikimedia Foundation is selling privileged access to that free labor.

It is against that backdrop that the current unionization struggle unfolds.

Governments that deploy internet shutdowns to thwart protesters have struggled to clamp down on offline messaging apps. India’s recent response to Jack Dorsey’s Bitchat suggests that battle is entering a new phase.

Bitchat, launched by the Twitter co-founder in 2025, allows nearby phones to communicate over Bluetooth even when mobile networks or internet access are unavailable. Last month, the app had its biggest real-world test after authorities shut down internet access during student protests in New Delhi.

As protesters turned to Bitchat, the Indian government tried to block access to the app’s source code on GitHub, a Microsoft-owned platform that allows developers to create, store, manage, and share their code. In the past, the Indian government has blocked apps from official app stores due to various reasons, but digital rights advocates say this appears to be the first known attempt to geoblock an open-source software repository.

The episode highlights a growing challenge for governments.

Massachusetts has decided to lead the country on artificial intelligence. Over the past two years, the state has put a hundred million dollars into a new AI Hub, placed a ChatGPT assistant on the desks of forty thousand state employees, and directed every agency to work out what the technology can do for the public's business. The public is warier than its government: two thirds of Massachusetts voters tell pollsters they are more concerned than excited about artificial intelligence.1

Massachusetts has not extended its technology modernization to the offices with the most direct power over ordinary life in the Commonwealth: the eleven District Attorneys. The state elects one for each county or small group of counties, and each runs an independent office that answers, between elections, to no governor, no mayor, and no oversight board.2 Their Assistant District Attorneys (ADAs) decide every day who gets charged with a crime, who gets offered a way out of one, and who gets left alone.

All eleven District Attorneys' offices run on a shared database called DAMION, which holds the record of essentially every criminal case in the state and is roughly twenty-five years old.3 Even the offices that use it every day do not defend its age. The Massachusetts District Attorneys Association (MDAA), the nonprofit through which the eleven offices share funding and technology, describes DAMION in its request for proposals for a replacement as "implemented approximately 25 years ago" and "nearing its end of life." The State Auditor went further this past November, reporting that the case management system used by all eleven offices "is obsolete and… may soon no longer be supported by the software manufacturer."4 When DAMION came online in the early 2000s, most Americans with internet at home still connected through a screeching dial-up modem, and the iPhone was still years away.5 AOL shut down its dial-up service last fall, by which point about one American household in a thousand still used it. DAMION remains in daily use by every District Attorney in Massachusetts.

In a study published in the journal Judgment and Decision Making, 1,682 adults were asked to read one of six short stories, three of which were written by humans and three by ChatGPT. Each AI story had a similar theme to one of the human-authored works.

The team told participants whether their story was written by a human or AI, but this information was not always correct. The researchers then asked participants to rate how absorbing and engaging they found the story, and its quality.

Participants who read an AI-generated story rated it as more absorbing and of higher quality than those who read a story written by a human. However, participants gave higher ratings to stories they had been told were written by people.

Dr Deena Skolnick Weisberg, a senior author of the research from Villanova University in Pennsylvania, said: “AI systems can already generate short stories that are seen as being at least as good as – if not better than – human-written stories. We should update our views of AI’s abilities accordingly.”

However, Weisberg, who is herself a creative writer, said that did not mean writing should be left to AI, noting that novels produced by tech were probably going to be different from those written by humans.

“We may need to make room for AI-generated novels, and for AI/human co-written novels, but that doesn’t mean that there’s no longer space for us to appreciate the process of human creativity,” she said.

Claim: [Wikipedia's operators] has not hired a union-busting law firm.

A hedge fund worth $45 billion at its height sold nearly its entire stock portfolio to Citadel Securities last week. As recently as a month ago, the fund was up 439 percent on the year, according to an investor letter from its founder, 24-year-old former OpenAI employee Leopold Aschenbrenner. But its portfolio, aggressively invested in companies tied to the artificial intelligence industry, dropped 67 percent in July.

Hilariously, the fund was called Situational Awareness.

Last week, the tech-heavy Nasdaq saw its second correction of the year, named for a drop of at least 10 percent from its peak. SpaceX has lost the equivalent of the entire value of Tesla since its post-IPO high in June, and it’s still dropping. For whatever reason—the rise of cheaper and more flexible Chinese AI models, the recognition that U.S. AI companies simply aren’t generating enough revenue to justify skyrocketing capital expenditures, the general economic drag from Trump’s tariffs and wars, or the increasingly operatic financial maneuvers to keep the wheels moving—the shine is way off the AI rose for investors.

The problem is that the industry is bound so tightly with the stock market that a change in feeling from AI investors could be all it takes to generate a market-wide crash, as we’re seeing to some degree. In other words, if AI is propping up the economy, who is propping up AI?

The answer, extrapolating from a fascinating new paper about private credit and the life insurance industry, could be the U.S. taxpayer.

Private credit is private equity’s $3 trillion financing arm. They make largely unregulated, relatively high-risk, relatively complex and opaque loans, mostly to their own portfolio companies. Private credit is entangled, maybe more than the rest of Wall Street, in AI mania. For example, in the mid-2010s private equity bought up hundreds of software-as-a-service providers, and its private credit affiliates made thousands of loans to them, only to see these portfolio companies buckle recently as AI replicated their tasks.

With no background in coding, Faith Maeba, a psychology major, was reluctant when her mother first suggested she enroll in classes on artificial intelligence.

But the senior at Virginia Commonwealth University began to see it differently as she looked into graduate psychology programs that explore human behavior in the workplace, which is quickly being upended by machine learning. Maeba, 21, is now pursuing a minor in AI.

“It’s giving me an edge and standing out,” she said.

Hiring has cooled for entry-level software developers — work increasingly done by AI agents — and college enrollment in computer and information science programs has been declining. Yet at campuses across the country, many professors are finding themselves busier than ever teaching students from a range of majors about artificial intelligence.

Colleges are responding to changes in student demand, but they also recognize that new graduates — regardless of their field — are facing questions about their AI skills from potential employers.

“We have to democratize it,” said Peter Stone, the chair of computer science at the University of Texas at Austin, who recently developed an introductory course on AI essentials for noncomputer science majors.

“In the same way that everybody needs some degree of math, reading and writing, I think everybody needs a degree of AI literacy,” he said.