The icons in the forthcoming version of macOS have been subtly tweaked to retreat from last year’s “Liquid Glass” appearance. CC-licensed photo by Yeray Hdez Guerra on Flickr.
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A selection of 10 links for you. Gleaming. I’m @charlesarthur on Twitter. On Threads: charles_arthur. On Mastodon: https://newsie.social/@charlesarthur. On Bluesky: @charlesarthur.bsky.social. Observations and links welcome.
Polymarket’s viral videos showed people winning big, but the bets were fake • Ars Technica
Jon Brodkin:
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Polymarket paid dozens of social media users to film themselves making fake bets for a promotion that aimed to convince people they can strike it rich on the prediction market, according to a Wall Street Journal investigation published on Saturday.
“In its push to draw users to its unregulated platform, Polymarket has flooded social media with videos like [George] Makihara’s, which appear genuine at first glance,” the article said. “In reality, Polymarket built near-perfect copies of its website, then instructed creators to make simulated trades on those dummy sites and hide that they were being paid by Polymarket.”
Makihara, a college student, posted a video in January “that showed him winning $100,000 on a wager that President Trump would publicly say the word ‘McDonald’s’ that month.” But trade data showed that no one on Polymarket won such a bet in January, according to the Journal. This was one of 145 bets that Makihara appeared to place on Polymarket between January and May, but all of those bets were fake, the article said.
“Many of the videos share a template: The creators open Polymarket, place a bet, and frequently refer to their winnings as ‘free money.’ Dozens of social-media creators have posted videos with almost identical formats,” the Journal reported. “Polymarket sends creators bullet-point guidance on what to say, according to creators who have worked with the company and a recruiting website.”
The promotion reportedly targeted US residents by paying creators only when at least 60% of their viewers were in the United States. Polymarket’s main platform technically hasn’t been available in the US since 2022, when the Commodity Futures Trading Commission (CFTC) determined Polymarket was operating an illegally unregistered exchange.
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Piling untrustworthiness up like boxes at a supermarket.
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Economists have long pushed for prediction markets. The reality is not what they’d hoped for • CNN Business
Allison Morrow:
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Long before the founders of Kalshi and Polymarket were even born, a handful of economists were getting amped about a novel approach to dealing with one of humanity’s more egregious shortcomings: We’re bad at predicting the future.
Maybe, the thinking went, the free market could help. (This was the late ‘80s, after all, the heyday of Reaganomics, Alex P. Keaton, the twilight of the Soviet Union — what couldn’t capitalism fix?)
And so the modern prediction market was born.
But nearly 40 years into economists’ obscure academic project, the booming industry they helped inspire — a multibillion-dollar business fueled largely by sports betting — looks very different from what they envisioned.
…Since then, we’ve gotten event contracts for just about anything. The markets aren’t perfect crystal balls, and crowd wisdom can be misleading, but they’ve had some notable wins, like when Polymarket bested the leading polls and pundits to call the 2024 presidential race in Donald Trump’s favor. And traders have consistently anticipated key economic data points, like the rate of US inflation and interest rate decisions from the Federal Reserve.
But when those 19 economists wrote their dream scenario, they did so with plenty of guardrails in mind.
The markets would “presumably not include contracts on the outcomes of sports events.” And the economists made the case for capping the amount any one person could wager to a “modest sum, perhaps something like $2,000 per year” (about $3,000 in today’s dollars).
But with sports betting exploding on prediction markets, and with virtually no cap on wagers, things haven’t worked out quite how they’d imagined.
“This is not the future any of us were hoping for,” Justin Wolfers, a University of Michigan professor and a leading expert on prediction markets who co-authored the 2008 paper [on “the promise of prediction markets“], told CNN.
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HR consultant wins English court case using AI lawyer in apparent legal first • The Guardian
Charlie Moloney:
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An artificial intelligence law firm has won a case in an English court, in what is believed to be the first time a trial has been won using an AI lawyer.
A freelance HR consultant, Tamires Camal Taquidir, paid the firm, Garfield AI, about £400 to send a legal letter and then issue court proceedings over an unpaid debt of £7,000.
The co-founder of Garfield, Philip Young, called it a “landmark moment” for access to justice and said many small businesses have had to write off debts because the cost of litigation outweighed the money they could hope to win.
Garfield – which was authorised by the Solicitors Regulation Authority in April last year and can be used to make claims from £30 to up to £10,000 – prepared the case and then hired a human barrister to advocate for the client in court.
The AI conducted all the legal work preceding the trial, which involved disputing a counterclaim launched by the defendant, who instructed solicitors.
It prepared four witness statements and a bundle of documents for the three-hour trial at Wandsworth county court on 14 May. The court found in favour of Taquidir and awarded her the money owed.
Taquidir said: “I was owed money for work I had done, but it felt like the process of recovering it could be too stressful, expensive and time-consuming. Garfield made it possible for me to pursue the claim and keep going.
“When the counterclaim was brought, it was intended to intimidate me, but I knew I had accessible, cost-effective and competent support. I’m delighted by the result.”
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Hope that he got costs, because barristers are never cheap. Nice advert for Garfield, but hard to know how well it would scale to a more complicated case.
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Read this before you vibe-code another app • The Verge
Yael Grauer:
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Bob Starr was delighted with his vibe-coded website. “Boomberg” showed how much US tax money is going to tech companies, and Starr launched it online immediately after making it. It wasn’t until months after the site went live that he realized there was a problem: a hidden SQL injection risk. It could’ve left the site open for an attacker to read or alter data they shouldn’t have access to.
“It was just a glaring oversight on my part. It was a complete blindspot in my state of learning this new technology and understanding it, and I’m sure there are others making the same mistake,” said Starr, a project manager in the tech sector.
Starr fixed the issue, but he isn’t alone. Across social media, there are horror stories about vibe-coded apps full of security vulnerabilities. Jer Crane, founder of PocketOS, posted on X about an AI coding agent wiping out his company’s production database. Joe Procopio, a serial entrepreneur and former developer, vibe-coded a web app to privately show demos of other apps he’d built. Hackers came, so he took the app down. “Now I do demos the old fashioned way, from my local machine over Zoom,” he wrote. “It’s sooo 2023.”
We’ve entered a new “era of personal software,” as The Verge’s David Pierce said, where anyone can use AI to create their own private apps that can do exactly what they want. But with it comes a new era of security issues. Apps may be easy to build, but they’re difficult to secure — especially in a world where AI can also be used to attack them.
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Don’t you then set a different LLM to work trying to find ways to hack the app and suggesting ways to secure it? Though it might be difficult to change the vibe coded app, because by all accounts they’re giving new meaning to spaghetti coding.
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GM installs robots at flagship EV factory after laying off 1,300 workers • Ars Technica
Jeremy Hsu:
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Dozens of new robot arms have been installed at General Motors’ flagship electric vehicle factory in Detroit—even as 1,300 workers remain out of work following what was supposed to be a temporary layoff. The latest automation push has spurred union pushback over a potentially existential issue for automakers and their workers.
General Motors installed approximately 50 robot arms at GM’s Factory Zero plant in Detroit, Michigan, according to reporting by Crain’s Detroit Business. Made by the Japanese robotics company FANUC, the robots are designed to help attach various components to vehicles during the assembly line process. But leaders at United Auto Workers (UAW), the primary US union for autoworkers, reacted with anger to the new robotic presence, given how GM has not yet called back any of the workers affected by supposedly temporary layoffs in March.
More than 1,000 union members are still “laid off indefinitely,” James Cotton, president of UAW Local 22, told The Detroit News. He said that the company could bring some of those members back to work instead of installing the 50 robots.
The temporary layoffs were preceded by permanent layoffs involving another 1,200 workers at GM’s Factory Zero in October 2025.
Many automakers, including Stellantis NV and Ford Motor Company, have deployed assembly-line robots, such as Fanuc robot arms, as they push to automate more of their US operations. Hyundai Motor Company plans to deploy Atlas humanoid robots made by Boston Dynamics—which Hyundai acquired in 2020—to start working in the automaker’s flagship EV facility in Georgia by 2028.
Andrew Bergman, a Local 22 member and union organizer who was among those laid off by GM, described corporate leaders in the automotive industry as prioritizing profits over human workers.
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Sounds callous to say so, but that is pretty much always how corporate leaders function.
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The Colour Strike
David Friedman:
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When the British channel ITV made their switch to colour at the end of 1969, the camera operators union felt that the additional technical knowledge and skills required for a colour camera deserved a pay increase for the operators. ITV disagreed. So the operators came up with a clever way to strike.
They simply shut off the red, green, and blue tubes in the cameras, leaving the fourth black-and-white tube on, essentially turning those fancy cameras back into black-and-white cameras.
It caused all sorts of havoc for shows that were promoted as being in colour, and ad revenue was lower than expected now that programming wasn’t in colour after all. Without a full work stoppage, the camera operators union still managed to hurt ITV.
The strike lasted about three months before an agreement was reached, and then color programming resumed.
Despite the strike, ITV still had to begin filming the first season of their new show Upstairs/Downstairs, a drama that was sort of like Downton Abbey before Downton Abbey, about the family upstairs and the staff downstairs in a large townhouse.
The plan was to eventually sell the show to American television, but the strike created a problem. The first six episodes of the show were filmed during the strike and were black-and-white, and the rest of the episodes filmed after the strike were in colour. What American network would want a show that has some episodes in black-and-white and some in colour in a single season?
So they came up with a solution: They would reshoot the entire first episode in colour to set up the situation and characters, and package that with the colour episodes that come later in the season for American audiences. The American version would just skip a few episodes in between but it wouldn’t be a big deal.
Oh, wait. It actually would be a big deal, because the first episode begins with one character, Sarah, arriving for her new job as a housemaid (accidentally attempting to enter through the front door instead of the rear). But in the third episode she quits her job and leaves the show. So American audiences would meet her in episode one, and then she’d be gone with no explanation.
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Multiverse problems! There’s also a lovely point about a union dispute over a clock on a set: was it electrical (one union) or, because it appeared on a set, a prop (different union)?
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AI doomaxxing is bad for our economy • The New York Times
Robert Shiller won the Nobel Prize for Economics in 2013:
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Moments after ChatGPT was released in 2022, its emergence swiftly unleashed a flood of alarming prognostications, including the possibility of enormous job losses. Many of those warnings were emanating from the leaders of the technology themselves. Little wonder that Americans are now highly worried about the impact AI will have on their futures, with a recent poll finding that 70% believe that the technology will reduce employment opportunities.
Like many others, I believe AI could lower employment. But unlike most, I don’t necessarily blame the technology itself. Instead, I worry about the potency of the fear it is generating.
Our brains are wired to respond to stories. Narratives floating in a population can affect individuals’ economic decisions about whether to buy a big house, or whether to send their kids to an expensive private school or even whether to have kids at all. When millions of people make millions and millions of decisions based upon negative expectations, there is a risk that fear can actually help birth the reality.
The idea that something like artificial intelligence will replace many human jobs goes back thousands of years. Aristotle envisioned a powered loom and a self-playing lyre someday replacing human servants. In the 19th century, groups of textile workers (the Luddites) destroyed the new machines they believed were replacing them. In the 1920s, the play “R.U.R.” — the letters stand for “Rossum’s Universal Robots” — depicted a war of the robots against humans.
…As the economist Christina D. Romer’s seminal study on the era points out, the stock market crash didn’t cause the Depression. It couldn’t, given that only about 2% of American households owned stocks at that time. The fatal blow was a massive subsequent collapse in consumer spending, a collapse she attributed to a sudden onset of widespread uncertainty among consumers about their future incomes.
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In Shiller’s view, people worry too much about AI, and that is self-reinforcing.
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Asbestos from China discovered in 1,000 UK wind turbines • The Times
Greig Cameron:
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Asbestos has been found in at least 1,000 wind turbines across Britain after essential parts were shipped into the country from China, it can be revealed.
Emergency brake components used in lifts and hoists inside the turbines have been imported containing chrysotile, or white asbestos, in a safety risk that unions said “beggars belief”.
The parts are understood to have come from third-party Chinese suppliers. The discovery has fuelled concerns over “opaque” supply chains and how the potentially deadly material got into the country.
The type of asbestos has been completely banned in the UK since November 1999, making it illegal to buy, sell or export any materials with it.
Wind farm owners have been carefully analysing their portfolios to identify affected sites, The Sunday Times has learnt. The work has included atmospheric testing to look for the presence of asbestos in the air, while a programme of replacing equipment has begun.
Although airborne particles have yet to be found, unions are furious. The GMB has written to UK ministers and the Health and Safety Executive (HSE) asking for a detailed account of the clean-up operation, the costs to date and the risk to workers.
…Safety warnings were circulated earlier this year by SafetyOn, a UK industry body. It is understood one large Scottish operator has already identified asbestos in more than 200 of its turbines, including some which have yet to be fully installed.
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One in three Americans use chatbots for health advice. These six patients explain why • The Washington Post
Fenit Nirappil:
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Chatbots fuelled by artificial intelligence bear disclaimers saying they cannot dispense medical advice or diagnose conditions, but they still field millions of queries from users who are sick, trying to decipher medical records or understand their treatment options.
Nearly 1 in 3 Americans have turned to the bots for health information, according to a recent survey by KFF, a nonpartisan health policy and education organization.
AI companies are rushing to meet this demand, including Anthropic’s Claude for Healthcare and OpenAI’s ChatGPT Health, advertising more robust privacy protections and features to connect to medical records, while warning their products cannot replace doctors.
“They can be plausible-sounding, completely confident-sounding and completely wrong at the same time,” said Girish Nadkarni, a professor of medicine at the Icahn School of Medicine at Mount Sinai and co-author of an independent evaluation of ChatGPT Health.
Nadkarni’s research found the chatbot failed to tell users to go to the emergency department in more than half of cases of impending respiratory failure and serious diabetic complications, instead advising them to stay home and monitor symptoms. The findings comport with other studies and reviews that have given AI health advice failing grades or at least urged caution.
OpenAI has raised questions about the methodology of the study and whether it properly reflects how people actually use its chatbot. A spokesperson for the company said ChatGPT Health models are continuously trained and updated through feedback from physicians.
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(Thanks Joe S for the link.)
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macOS Tahoe v Golden Gate icon comparison • Basic Apple Guy
B.A.G:
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WWDC always brings a torrent of new content, details, and platform-wide changes. One of the first things I noticed after installing the macOS Golden Gate beta was the updated icon design. The colours are much bolder, several icons have been adjusted, and the refraction in the Liquid Glass effect has changed significantly, especially in icons like Journal.
There’s also a noticeable sharpness to the icons, along with a flattening of the Liquid Glass effect. I’m not sure yet whether this is simply an early-beta artifact or the intended final look. For example, while I really like the redesigned Finder icon, the sharp black edges around the nose currently feel a little unrefined.
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The difference seems subtle when seen individually here, but you can imagine that when seen across a screen or folder full of icons it would feel substantial. The lowering of reflection and extra sharpness are welcome: there’s no point in having blurry icons, ever.
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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
The Overspill: when there's more that I want to say 