
The unsolved mystery of shopping is how to create a sensible set of clothing sizes for women that they can rely on. CC-licensed photo by Artem Beliaikin on Flickr.
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A selection of 11 links for you. Sized up. I’m @charlesarthur on Twitter. On Threads: charles_arthur. On Mastodon: https://newsie.social/@charlesarthur. On Bluesky: @charlesarthur.bsky.social. Observations and links welcome.
The worst-case future for white-collar workers • The Atlantic
Annie Lowrey:
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the labour market for office workers is beginning to shift. Americans with a bachelor’s degree account for a quarter of the unemployed, a record. High-school graduates are finding jobs quicker than college graduates, an unprecedented trend. Occupations susceptible to AI automation have seen sharp spikes in joblessness. Businesses really are shrinking payroll and cutting costs as they deploy AI. In recent weeks, Baker McKenzie, a white-shoe law firm, axed 700 employees, Salesforce sacked hundreds of workers, and the auditing firm KPMG negotiated lower fees with its own auditor. Two CNBC reporters with no engineering experience “vibe-coded” a clone of Monday.com’s workflow-management platform in less than an hour. When they released their story, Monday.com’s stock tanked.
Maybe algorithm-driven changes will happen slowly, giving workers plenty of time to adjust. Maybe white-collar types have 12 to 18 months left. Maybe the AI-related job carnage will be contained to a sliver of the economy. Maybe we should be more worried about a stock-market bubble than an AI-driven labor revolution.
I don’t think anyone knows what will happen, or even what is happening now. AI technology is changing at an exponential pace, and changing the workforce in a thousand hard-to-parse ways. But if AI quickly eliminates white-collar work, the country is going to end up in something much stranger than a downturn, and something much harder to recover from too.
The United States is adept enough at handling the labor-market damage caused by recessions. Congress slashes taxes, writes stimulus checks, and fattens unemployment-insurance payouts. Washington amps up infrastructure spending and patches holes in the budgets of state and local governments. The Federal Reserve drops interest rates down to zero and purchases hundreds of billions of dollars of safe assets, making borrowing cheaper for families and encouraging businesses to invest. Demand increases, pushing the unemployment rate down and GDP up.
But if white-collar layoffs cause a downturn, Washington might not be able to restore hiring and lift consumer spending as it has done before.
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Today’s edition has a lot of stories like this. It’s hard to escape. But you need multiple viewpoints. (Gift link.)
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Sizing chaos: how women can’t find clothes • The Pudding
Amanda Sakuma and Jan Diehm:
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I remember once being that teen girl shopping in the women’s section for the first time. I took stacks upon stacks of jeans with me to the dressing room, searching in vain for that one pair that fit perfectly. Over 20 years later, my hunt for the ideal pair of jeans continues. But now as an adult, I’m stuck with the countless ways that women’s apparel is not made for the average person, like me.
Children’s clothing sizes are often tied to a kid’s age or stage of development. The idea is that as a young person grows older, her clothes will evolve with her. Youth styles tend to be boxy and oversized to allow room for kids to move and grow. By early adolescence, apparel for girls becomes more fitted. Junior’s styles have higher waistlines and less-pronounced curves compared to adult clothing lines. In short: clothes for tweens are made for tween bodies.
By the time most teenage girls can wear women’s clothes — around age 15 — their options are seemingly endless. But the evolution in clothing sizes that followed girls throughout childhood abruptly stops there.
This is the reality I find myself reckoning with today: women’s clothing — designed for adults — fits modern teen girls better.
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This has terrific graphics, and reminds me strongly of a post which – very annoyingly – I can’t recall or find (not via search engine, not via chatbot) which was written by a woman (name maybe included Green?), about British stores’ varying clothes sizes, and which I linked to here (so post-2014). If you can remember what it was, let us know!
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Microsoft’s new 10,000-year data storage medium: glass • Ars Technica
John Timmer:
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Archival storage poses lots of challenges. We want media that is extremely dense and stable for centuries or more, and, ideally, doesn’t consume any energy when not being accessed. Lots of ideas have floated around—even DNA has been considered—but one of the simplest is to etch data into glass. Many forms of glass are very physically and chemically stable, and it’s relatively easy to etch things into it.
There’s been a lot of preliminary work demonstrating different aspects of a glass-based storage system. But in Wednesday’s issue of Nature, Microsoft Research announced Project Silica, a working demonstration of a system that can read and write data into small slabs of glass with a density of over a Gigabit per cubic millimeter.
We tend to think of glass as fragile, prone to shattering, and capable of flowing downward over centuries, although the last claim is a myth. Glass is a category of material, and a variety of chemicals can form glasses. With the right starting chemical, it’s possible to make a glass that is, as the researchers put it, “thermally and chemically stable and is resistant to moisture ingress, temperature fluctuations and electromagnetic interference.” While it would still need to be handled in a way to minimize damage, glass provides the sort of stability we’d want for long-term storage.
Putting data into glass is as simple as etching it. But that’s been one of the challenges, as etching is typically a slow process. However, the development of femtosecond lasers—lasers that emit pulses that only last 10-15 seconds and can emit millions of them per second—can significantly cut down write times and allow etching to be focused on a very small area, increasing potential data density.
To read the data back, there are several options. We’ve already had great success using lasers to read data from optical disks, albeit slowly. But anything that can pick up the small features etched into the glass could conceivably work.
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Forget DeepSeek. Dying alone is China’s latest tech obsession • Bloomberg via The Japan Times
Catherine Thorbecke:
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This time last year, the hottest Chinese tech product was DeepSeek’s market-moving artificial intelligence model. In 2026, it’s something far simpler: an app for people worried about dying alone.
The bluntly named “Are You Dead?” platform rocketed to the top of the app-store charts in China before going viral globally. The interface is almost aggressively plain. Users, largely people living alone, tap to confirm they are still alive. Miss two days in a row and an emergency contact gets notified.
Besides its provocative moniker, there’s a reason the app went megaviral without spending a dime on advertising — and didn’t even have to pretend to be a buzzy new AI product. Its surge coincided with the nation’s birth rate plunging to its lowest on record, at a time when marriage figures are falling and divorces are ticking up.
While many assumed it was developed for elderly users seeking to hold on to their independence, it was actually created by a team of Gen-Z developers who said in interviews they were inspired by their own experiences of isolating urban life. One-person households are expected to swell to as many as 200 million in the country by 2030.
These demographic changes aren’t unique to modern China, but they’re definitely not the kind of publicity Beijing wants right now. The platform was quietly removed from Chinese app stores last week. In a culture where frank mentions of dying are seen as taboo and inauspicious, the creators also said on micro-blogging site Weibo that they were planning on rebranding. The new international name, “Demumu,” is a Labubu-fied riff on the word “death.” It didn’t catch on as expected and the developers are now crowdsourcing a new idea via social media.
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I guess a lifetime subscription would be a good model.
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Death of software? Nah • Learning By Shipping
Steven Sinofsky goes over previous technology waves – the PC, retail and the web, media and the internet – and points out how people predicted both complete disruption and complete vanishment for each in turn:
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In each of these examples you can be someone who was there and claim “told you so,” or you could be someone who placed all their bets on “whole new world,” or somewhere in between.
In reality, almost all the people that called for full disruption and a whole new world were wildly optimistic on the timeframe. The thing is, the world needs these people because the transition is not a straight path. It is not “this is what we know needs to be built and now build it.”
Instead, what is absolutely part of this whole arc are people who are certain we are less than five years away and are in a rush to build with absolute belief in where things are heading, and people who support them with their labor or dollars. They are more worried about having already missed his opportunity as Marc Andreessen has often said upon arriving in Silicon Valley in 1994. Their success is awesome. Their failure teaches the broad community lessons. That’s also why the network and community of SV was so key.
The people that are certain what is going on is forever away, or even worse never going to happen, well they are important too. Because the transition takes so long and is so unevenly distributed, having people focused on legacy is key. Without all those people working on mainframes at IBM we would never have had online travel or banking, because that whole industry runs on that iron.
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He then goes on to list what he thinks is going to happen, for which the point summaries are:
• There will be more software than ever before
• AI-enabled or AI-centric software is simply moving up the stack of what a product is
• New tools will be created with AI that do new things
• Domain experience will be wildly more important than it is today because every domain will become vastly more sophisticated than it is now
• Finally, it is absolutely true that some companies will not make it.
He also points out that he instructed an LLM to do “a light proofread only” but also “do not delete content or change meaning. Preserve the tone, rhythm and point of view.” And that “Any emdashes were in the original.”
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Zuckerberg grilled in landmark social media trial over teen mental health • The Guardian
Sanya Mansoor:
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The Meta CEO, Mark Zuckerberg, testified at a landmark trial of social media companies on Wednesday. Plaintiffs’ lawyers grilled Zuckerberg about internal complaints that not enough was being done to verify whether children under 13 were using the platform.
Zuckerberg claimed Meta had improved in identifying underage users but also said: “I always wish that we could have gotten there sooner.”
Zuckerberg also said some users lie about their age when joining Instagram and that the company removes those it identifies as underage, according to CNBC. The plaintiffs’ lawyers hit back at those claims: “You expect a nine-year-old to read all of the fine print? That’s your basis for swearing under oath that children under 13 are not allowed?” CNBC reported.
The Meta chief was flanked by people wearing the Meta Ray-Ban artificial intelligence glasses, and the judge in the courtroom threatened to hold anyone recording with the devices in contempt, CNBC reported.
…Lawyers for the plaintiffs, who argue that Meta intentionally designed its social media platforms to be addictive, questioned Zuckerberg about whether he knew of harms his company’s products could inflict on young people’s mental health. The plaintiffs have already made public internal documents they say prove their point.
This is the first time Zuckerberg has addressed concerns about child safety before a jury at trial. Tech companies have long relied on a federal law that shields them from liability for content posted by users, but the plaintiffs’ novel argument – which is focused on harmful design and not individual actors – has so far sidestepped this defence.
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Leaked email suggests Ring plans to expand ‘Search Party’ surveillance beyond dogs • 404 Media
Jason Koebler:
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Ring’s controversial, AI-powered “Search Party” feature isn’t intended to always be limited only to dogs, the company’s founder, Jamie Siminoff, told Ring employees in an internal email obtained by 404 Media.
In October, Ring launched Search Party, an on-by-default feature that links together Ring cameras in a neighborhood and uses AI to search for specific lost dogs, essentially creating a networked, automated surveillance system. The feature got some attention at the time, but faced extreme backlash after Ring and Siminoff promoted Search Party during a Super Bowl ad. 404 Media obtained an email that Siminoff sent to all Ring employees in early October, soon after the feature’s launch, which said the feature was introduced “first for finding dogs,” but that it or features like it would be expanded to “zero out crime in neighbourhoods.”
“This is by far the most innovation that we have launched in the history of Ring. And it is not only the quantity, but quality,” Siminoff wrote. “I believe that the foundation we created with Search Party, first for finding dogs, will end up becoming one of the most important pieces of tech and innovation to truly unlock the impact of our mission. You can now see a future where we are able to zero out crime in neighborhoods. So many things to do to get there but for the first time ever we have the chance to fully complete what we started.”
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I’d misunderstood the recent ructions where Ring disassociated from Flock to mean Search Party (for dogs) was over. But Ring wants to get in on the crime space that Flock has been shifting towards. Meanwhjile it has launched “Fire Watch”, using AI to warn about fires.
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The AI disruption has arrived, and it sure is fun • The New York Times
Paul Ford:
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Is the software I’m making for myself on my phone as good as handcrafted, bespoke code? No. But it’s immediate and cheap. And the quantities, measured in lines of text, are large. It might fail a company’s quality test, but it would meet every deadline. That is what makes A.I. coding such a shock to the system.
An axiom of programming is “real artists ship.” That was something Steve Jobs once said to remind his team that finishing and releasing a product matters more than endlessly refining it. Much of the software industry is organized around managing ship risk, and the possibility that a product never actually makes it out to the world. A good technology manager assumes that a product will never ship for launch, that every force is arrayed against it, and that the devil himself has cursed it — and then the manager works back from that.
Even if all these obstacles are surmounted, the software will ship late. Remember, Steve Jobs returned to Apple in 1997 only because Apple couldn’t ship a new version of its operating system, so they bought his company, NeXT. And the direct descendant of NeXT’s software is what’s running on Macs and iPhones in 2026. In software, dramatic change is to be avoided at all costs. The risk is just too high.
Except … what if, going forward, it’s not? What if software suddenly wanted to ship? What if all of that immense bureaucracy, the endless processes, the mind-boggling range of costs that you need to make the computer compute, just goes poof? That doesn’t mean that the software will be good. But most software today is not good. It simply means that products could go to market very quickly.
And for lots of users, that’s going to be fine. People don’t judge A.I. code the same way they judge slop articles or glazed videos. They’re not looking for the human connection of art. They’re looking to achieve a goal. Code just has to work.
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AI taxonomy: an operational framework for precision in AI discourse
Narain Jashanmal:
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“AI” has become semantically meaningless. The term now encompasses everything from a regression model to an autonomous robot, creating confusion in strategic discussions, partner conversations, and product positioning. This taxonomy provides a functional framework based on what the AI actually does, not what technique it uses.
The Framework in One Sentence: We use Analytical AI to decide, Semantic AI to understand and remember, Generative AI to create, Agentic AI to act, Perceptive AI to sense, and Physical AI to move.
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This is certainly a useful addition.
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Preserving the web is not the problem. Losing it is • Techdirt
Mark Graham is the director of the Wayback Machine at the Internet Archive:
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Recent reporting by Nieman Lab describes how some major news organizations—including The Guardian, The New York Times, and Reddit—are limiting or blocking access to their content in the Internet Archive’s Wayback Machine. As stated in the article, these organizations are blocking access largely out of concern that generative AI companies are using the Wayback Machine as a backdoor for large-scale scraping.
These concerns are understandable, but unfounded. The Wayback Machine is not intended to be a backdoor for large-scale commercial scraping and, like others on the web today, we expend significant time and effort working to prevent such abuse. Whatever legitimate concerns people may have about generative AI, libraries are not the problem, and blocking access to web archives is not the solution; doing so risks serious harm to the public record.
The Internet Archive, a 501(c)(3) nonprofit public charity and a federal depository library, has been building its archive of the world wide web since 1996. Today, the Wayback Machine provides access to thirty years’ worth of web history and culture. It has become an essential resource for journalists, researchers, courts, and the public.
For three decades the Wayback Machine has peacefully coexisted with the development of the web, including the websites mentioned in the article. Our mission is simple: to preserve knowledge and make it accessible for research, accountability, and historical understanding.
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You’d expect that Graham’s article would, given how it’s describing concerns at those media organisations, offer reassurance that no, there’s absolutely no accommodation for AI scrapers. What you get is this:
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The Wayback Machine is built for human readers. We use rate limiting, filtering, and monitoring to prevent abusive access, and we watch for and actively respond to new scraping patterns as they emerge.
We acknowledge that systems can always be improved. We are actively working with publishers on technical solutions to strengthen our systems and address legitimate concerns without erasing the historical record.
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Which sounds rather like “yes, we are getting scraped, but we’re trying to stop it.”
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Goldman Sachs taps Anthropic’s Claude to automate accounting • CNBC
Hugh Son:
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Goldman Sachs has been working with the artificial intelligence startup Anthropic to create AI agents to automate a growing number of roles within the bank, the firm’s tech chief told CNBC exclusively.
The bank has for the past six months been working with embedded Anthropic engineers to co-develop autonomous agents in at least two specific areas: accounting for trades and transactions, and client vetting and onboarding, according to Marco Argenti, Goldman’s chief information officer.
The firm is “in the early stages” of developing agents based on Anthropic’s Claude model that will collapse the amount of time these essential functions take, Argenti said. He expects to launch the agents “soon,” though he declined to provide a specific date.
“Think of it as a digital co-worker for many of the professions within the firm that are scaled, are complex and very process intensive,” he said.
Goldman Sachs CEO David Solomon said in October that his bank was embarking on a multiyear plan to reorganize itself around generative AI, the technology that has made waves since the arrival of OpenAI’s ChatGPT in late 2022. Even as investment banks like Goldman are experiencing surging revenue from trading and advisory activities, it will seek to “constrain headcount growth” amid the overhaul, Solomon said.
The news from Goldman comes as model updates from Anthropic, co-founded by a former OpenAI executive, have sparked a sharp sell-off among software firms and their credit providers as investors wager on who the winners and losers from the AI trade will be.
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This ought to trigger a lot of discussion. The pessimistic view: AI is going to wipe out the jobs! The optimistic view: the arrival of the spreadsheet didn’t get rid of accountants; in fact it made it possible for there to be more accountants reporting results more quickly and people forecasting financial outcomes. Who knows where this is going to land?
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| • Why do social networks drive us a little mad? • Why does angry content seem to dominate what we see? • How much of a role do algorithms play in affecting what we see and do online? • What can we do about it? • Did Facebook have any inkling of what was coming in Myanmar in 2016? Read Social Warming, my latest book, and find answers – and more. |
Errata, corrigenda and ai no corrida: none notified








