What exactly caused the Baby Boom in the middle of the 20th century? CC-licensed photo by Erin Warren on Flickr.
There’s another post due at the Social Warming Substack at about 0845 UK time.
A selection of 10 links for you. Booming. I’m @charlesarthur on Twitter. On Mastodon: https://newsie.social/@charlesarthur. Observations and links welcome.
UK data watchdog to review period and fertility apps amid security concerns • The Guardian
Hibaq Farah:
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The UK data watchdog is to review period and fertility tracking apps after users expressed concerns over data security.
The Information Commissioner’s Office (ICO) announced the move after it commissioned research showing that half of women have concerns about how their data is used by the apps.
The poll of more than 1,150 women showed that a third of women have used apps to track their periods or fertility. Women said transparency over how their data was used and how secure it was were bigger concerns – at 59% and 57% of respondents respectively – than cost and ease of use when it came to choosing an app.
More than half of the people who use the apps also noticed an increase in baby or fertility-related adverts after signing up, with 17% finding the adverts distressing.
Emily Keaney, deputy commissioner of regulatory policy at the ICO, said the review intended to establish “both the good and the bad” of how the apps work.
She said: “These statistics suggest data security is a significant concern for women when it comes to choosing an app to track their periods or plan or prevent pregnancy. That’s not surprising, given the incredibly sensitive and personal information involved. Once we have more information, we will explore next steps, but we will not hesitate to take regulatory action to protect the public if necessary.”
The regulator will look into identifying potential harms and negative impacts on users. This includes confusing privacy policies that do not allow users to easily understand what they have consented to, whether the apps request and store unnecessary volumes of data and if users are receiving upsetting targeting advertising that they did not sign up to.
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Might also look at the app frameworks, since developers typically include third-party code that will do all sorts of intrusive things.
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‘Ritual mass murder’ report in Chapel St Leonards was yoga class • BBC News
Pritti Mistry:
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A yoga class was mistaken for a “ritual mass murder” scene after members of the public saw several people lying on the floor and reported it to police.
Five police cars descended on the North Sea Observatory in Chapel St Leonards, Lincolnshire, on Wednesday night.
Yoga teacher Millie Laws said she thought reports of her being a “mass murderer” were a “joke at first”.
Lincolnshire Police confirmed everyone was safe and well, and the call was made with “good intentions”.
The 22-year-old teacher said she was teaching seven students at the Seascape Cafe, which is inside the building, when she saw two dog walkers peering closely through the glass window during the Shavasana or relaxation stage of the class.
“They’re [students] laying down with blankets over them, their eyes are closed. It’s very dark in there. I just had candles and little tea lights lit the whole room, and I was just walking around playing my drum. I had a nice floaty top on with large bell sleeves,” she said. “A couple with some dogs just came up to the window and were having a look in, but they walked off really quickly and I didn’t think anything of it.”
Laws continued: “I didn’t know until after we left that these people phoned in saying that there was a mass murderer; they were wearing a robe and they were walking over all of the people, and it looked like some kind of ritual, and that the people on the floor were actually dead. I guess from the outside view it could look like that, because they’re all really still, very nice and relaxed.
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What. A. Story. Dog walkers do all the hard work of finding dead bodies: have you ever noticed how many “missing body found” reports stem from people walking their dog(s)? Now including when the bodies are not yet dead, apparently.
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ChatGPT fails in languages like Tamil and Bengali • Rest of World
Andrew Deck:
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Less than a year after launch, ChatGPT is being used all over the world, generating Amazon listings in China and call center scripts in the Philippines. But while ChatGPT thrives in English, Spanish, Japanese, and other dominant languages, it struggles to produce the same quality of text in languages like Bengali, Swahili, Urdu, and Thai — languages that have millions of speakers, but appear much less often online.
When Rest of World tested ChatGPT’s ability to respond in underrepresented languages, we found problems reaching far beyond translation errors, including fabricated words, illogical answers and, in some cases, complete nonsense.
Take Tigrinya, a language which has over 7 million speakers, with the vast majority located in Eritrea and the northern part of Ethiopia. Tigrinya shares a similar script to Amharic, a more dominant Ethiopian language, but there are significant differences between the two. When asked to list examples of African countries, ChatGPT mixed up Tigrinya and Amharic, adding characters that don’t exist in Tigrinya. It created an output to this simple question that is challenging to read for native speakers of both languages.
… Much has been made of the tendency of AI chatbots to “hallucinate” — shorthand for fabrications that chatbots state as facts. This problem is common with ChatGPT responses in low-resource languages. But in multiple instances, rather than generating fake numbers or other facts, Rest of World found that ChatGPT simply makes up words.
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This is one of those obvious-when-you-consider-it things, but that doesn’t make it any less bad. What it means is that the gap in usability of AI will grow wider between English and other languages.
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Apple stock hit by China worries ahead of iPhone 15 launch • Financial Times
Patrick McGee:
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Investor alarm that China may be cracking down on officials’ iPhone use has knocked $200bn off Apple’s market value, casting a shadow over next week’s launch of its latest smartphone.
Beijing’s reported curbs on government iPhones, alongside a resurgent Huawei, threaten to derail what should have been a moment of triumph for Apple: unseating Samsung at the top of the smartphone market.
Before the China turmoil, analysts had predicted that the launch of the iPhone 15 would put Apple within reach of becoming the world’s biggest smartphone maker by volume for the first time.
However, Apple’s shares have fallen by about 6% over the course of the past two days, as investors fretted about its fate in China, which makes up roughly a fifth of its revenue.
“A decade ago it seemed inconceivable that Apple could wrestle the top spot from Samsung but it could be that we’re on the cusp of that milestone,” said Ben Wood, analyst at CCS Insight. “They will be tantalisingly close but the Chinese market will play a pivotal role.”
Several reports surfaced this week suggesting that Beijing has ordered public officials in certain government departments not to use iPhones or other foreign devices for work.
Bank of America has estimated that China accounts for up to 50m iPhone sales annually and that such a ban could cost Apple 5-10m units a year.
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Nothing official from the Chinese government, of course.
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Understanding the Baby Boom • Works in Progress
Anvar Sarygulov & Phoebe Arslanagic-Wakefield:
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[In the 1930s] Despite the organised resistance of groups like Alliance nationale, at least some European demographers doubted whether falling birth rates were truly reversible, or even arrestable. In 1936 Dr Carr Saunders, an English biologist, eugenicist, and later Director of LSE, wrote:
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once the small voluntary family habit has gained a foothold, the size of the family is likely, if not certain, in time to become so small that the reproduction rate will fall below replacement rate, and that, when this happened, the restoration of a replacement rate proves to be an exceedingly difficult and obstinate problem.
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But even as Carr Saunders wrote those words, he was being proved wrong. Something was happening, in Europe and farther afield. Something we are still trying to understand today: the Baby Boom.
The Baby Boom was an unexpected change in direction from the century of falling fertility that had taken place in Europe and North America. Contrary to the popular belief that it was triggered by soldiers returning home from World War Two, the Boom in fact began in the mid-1930s. It was not simply an American or British phenomenon either. The demographic wave swept over Iceland, Poland, Sweden, France, the Netherlands, Austria, the Czech Republic, Canada, Norway, Switzerland, and Finland. Thousands of miles across the sea, it even happened in Australia and New Zealand.
And yet Carr Saunders’ doubt had been extremely well justified.
For wherever and whenever we have had data and since the Industrial Revolution – with the crucial exception of the Baby Boom – it has been a nearly iron law of fertility that higher incomes are associated with lower birth rates. A key mechanism for this is likely to be that rising living standards effectively increase the costs of having a child, from lost wages for working women to reduced time for increasingly accessible leisure activities.
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But that doesn’t explain the Baby Boom. This analysis does point to the multiple elements that probably do – with the Amish acting as a control group.
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Buzzy AI startup for generating 3D models used cheap human labour • 404 Media
Joseph Cox and Jason Koebler:
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An artificial intelligence company, whose founder Forbes included in a 30 Under 30 list recently, promises to use machine learning to convert clients’ 2D illustrations into 3D models. In reality the company, called Kaedim, uses human artists for “quality control.” According to two sources with knowledge of the process interviewed by 404 Media, at one point, Kaedim often used human artists to make the models. One of the sources said workers at one point produced the 3D design wholecloth themselves without the help of machine learning at all.
The news pulls back the curtain on a hyped startup and is an example of how AI companies can sometimes overstate the capabilities of their technology. Like other AI startups, Kaedim wants to use AI to do tedious labor that is currently being done by humans. In this case, 3D modeling, a time-consuming job that video game companies are already outsourcing to studios in countries like China.
…After the publication of this article, Kaedim rebranded its website to make it clearer that humans are involved in the company’s production of 3D images.
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Smart way to get that sweet, sweet VC money.
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With SBF, Gisele, and Michael Lewis at the peak of the crypto craze
Zeke Faux:
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when we sat down, Wu and a colleague bragged to me about a Zelda-like play-to-earn game on their blockchain that had attracted 40,000 users in less than a month. They said the game was teaching people about DeFi — decentralized finance, a way of trading without a central counterparty — and letting them earn high returns. It sounded a lot like Axie Infinity. I couldn’t believe they were pitching it with a straight face after Axie’s collapse. “You can get 10% in DeFi,” Wu said. “You can be a true freelancer. There are literally people who quit their jobs. It’s not magic. If you know what you’re doing here, you’re going to change your life.”
Michael Wagner, the founder of a space-themed crypto game called Star Atlas, even cited Axie Infinity as a proof of concept. Instead of colorful blobs and Smooth Love Potions, Star Atlas players had to buy spaceship NFTs to earn atlas tokens, and he told me he’d already sold nearly $200 million worth of them. But when I asked if I could try out the game, he said it didn’t exist yet. Even though he’d already sold the spaceships, he said it would be at least five years before the game was ready. “It’s very early stage,” he said. “We believe the game could bring in billions of users.”
Another crypto executive showed me a digital image of a sneaker that he’d bought for $8 and that he said was now worth more than $1 million. He told me that recently, all owners of these imaginary sneakers had been issued an image of a box, which was it self worth $30,000. When he opened the box, he found another pic ture of sneakers and another box, each of them valuable in their own right. “It’s this never-ending Ponzi scheme,” he said happily. “That’s what I call Ponzinomics.”
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And that always ends well, right? Taken from Faux’s new book “Number Go Up: Inside Crypto’s Wild Rise and Staggering Fall”, which sounds like a rollicking read.
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New Elon Musk biography offers fresh details about the billionaire’s Ukraine dilemma • CNN Politics
Sean Lyngaas:
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Elon Musk secretly ordered his engineers to turn off his company’s Starlink satellite communications network near the Crimean coast last year to disrupt a Ukrainian sneak attack on the Russian naval fleet, according to an excerpt adapted from Walter Isaacson’s new biography of the eccentric billionaire titled “Elon Musk.”
As Ukrainian submarine drones strapped with explosives approached the Russian fleet, they “lost connectivity and washed ashore harmlessly,” Isaacson writes.
Musk’s decision, which left Ukrainian officials begging him to turn the satellites back on, was driven by an acute fear that Russia would respond to a Ukrainian attack on Crimea with nuclear weapons, a fear driven home by Musk’s conversations with senior Russian officials, according to Isaacson, whose new book is set to be released by Simon & Schuster on September 12.
Musk’s concerns over a “mini-Pearl Harbor” as he put it, did not come to pass in Crimea. But the episode reveals the unique position Musk found himself in as the war in Ukraine unfolded. Whether intended or not, he had become a power broker US officials couldn’t ignore.
The new book from Isaacson, the author of acclaimed biographies of Steve Jobs and Albert Einstein, provides fresh insights into Musk and how his existential dread of sparking a wider war drove him to spurn Ukrainian requests for Starlink systems they could use to attack the Russians.
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Musk is an idiot. Why would Russia hit Crimea with nukes, when that’s territory that it views as its own? And you know that any effort by the US government to educate him about the strategic realities would be a waste of time. What a situation.
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Apple is reportedly spending ‘millions of dollars a day’ training AI • The Verge
Monica Chin:
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Apple is investing millions of dollars per day into artificial intelligence, according to a new report from The Information. The company is reportedly working on multiple AI models across several teams.
Apple’s unit that works on conversational AI is called “Foundational Models,” per The Information’s reporting. It has “around 16” members, including several former Google engineers. It’s helmed by John Giannandrea, Apple’s head of AI, who was hired in 2018 to help improve Siri. (Giannandrea has reportedly “expressed skepticism to colleagues about the potential usefulness of chatbots powered by AI language models.”)
Additional teams at Apple are also working on artificial intelligence, per The Information. A Visual Intelligence unit is developing an image generation model, and another group is researching “multimodal AI, which can recognize and produce images or video as well as text.”
These models could serve a variety of purposes. A chatbot is in the works that would “interact with customers who use AppleCare”; another would make it easier to automate multistep tasks with Siri.
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“Millions of dollars a day” sounds like someone got their calculator out on being told Apple is spending about a billion dollars on AI per year. (My guess. A billion per year is $3m; 2bn is $6m; and so on.) Given that Apple spends about $30bn per year on R+D, that isn’t actually a dramatic amount.
But look, anything that can improve Siri is going to be welcome.
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Will we ever be able to detect AI usage? • TechnoLlama
Andres Guadamuz:
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Why, you may ask, do we need to detect AI in the first place? The detection of AI use in everyday life is becoming increasingly important for a multitude of reasons. Firstly, transparency and trust are foundational to the relationship between technology and its users, as AI tools become more integrated into our daily routines, from personalised content recommendations to LLMs, it’s crucial for users to be aware of when and how these systems are making decisions on their behalf. Knowing when AI is at play can help individuals better understand the rationale behind certain outcomes, whether it’s a movie suggestion on a streaming platform or a financial advice from a robo-advisor.
Secondly, the ethical implications of AI are vast and varied. By detecting AI use, we can ensure that these systems are being employed in ways that align with societal values and norms, and with the user’s own acceptance of AI. For instance, in areas like hiring or lending, where decisions can have profound impacts on individuals’ lives, it’s essential to know if an AI is involved, potentially perpetuating biases or making uninformed decisions. Furthermore, as concerns about privacy and data security grow, being aware of AI’s presence can help individuals protect their personal information and avoid potential misuse. In essence, detecting AI use promotes accountability, ensuring that these powerful tools are used responsibly and ethically in our ever-evolving digital landscape.
Thirdly, if we’re going to continue using essays as means of assessment, we may need to find out for certain if AI is being used.
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I tried to think of a refutation of the importance of using essays as a means of assessment, but given that the point of an essay is to get people to show they can organise their thoughts and pick the important from the wrong or trivial, it’s hard to say that doesn’t matter in the world of work.
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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. |
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