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oursinBrain’s sex differences are subtle and contradictory, large MRI study finds:
But even apparently null results, as in the current study, are useful, Sanchís Segura says, “because it’s important to talk about when men and women are similar” in a field that is biased toward finding bias. For example, the way brain activation mapped onto behavior was largely the same for men and women, the new study found.
“You can prove that a difference exists, but you cannot prove that a difference doesn’t exist,” she says. “You can put into PubMed, ‘sex differences,’ and you will have thousands of papers, but what if I want to look for the absence of differences? We don’t even have a word.”
No evidence for ‘witches’ marks’ claims at old English buildings, historian says:
Over the years, English Heritage and Historic England have claimed to have identified large numbers of “witches’ marks” or “ritual protection symbols” on the walls of historic buildings, including medieval churches and houses.
Now a leading architectural historian has said there is “absolutely no evidence” that these marks have anything to do with witches or any “mystical meanings”.
Daisy wheels, or hexafoils, are among symbols that are no more than the marks of stonemasons who worked on those buildings, according to Jennifer Alexander, a professor of architectural history at Warwick University and author of a new study.
I had some vague knowledge of Woolrich, but pretty much only as 'er, wrote noir novels in the 30s or thereabouts? some of them became movies???'
I'm also slightly sceptical of the 'unconsummated marriage' alternative narrative simply because if you realised you had made A Dreadful Mistake this was probably an easy out via annulment? (will concede that I have personally written scholarly article deconstructing a famous allegedly non-consummated marriage narrative in the light of the British divorce laws of the early C20th)
But the whole 'create sensationalist account on basis of I think this happened/I made it all up' is not unfamiliar to moi.
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bruce_schneier_feedBecause of the way they are trained, large language models capture only a slice of human language. They’re trained on the written word, from textbooks to social media posts, and our speech as captured in movies and on television. These models have minimal access to the unscripted conversations we have face to face or voice to voice. This is the vast majority of speech, and a vital component of human culture.
There’s a risk to this. The increased use of large language models means we humans will encounter much more AI-generated text. We humans, in turn, will begin to adopt the linguistic patterns and behaviors of these models. This will affect not just how we communicate with one another, but also how we think about ourselves and what goes on around us. Our sense of the world may become distorted in ways we have barely begun to comprehend.
This will happen in many ways. One of the first effects we could see is in simple expression, much as texting and social media have resulted in us using shorter sentences, emojis instead of words, and much less punctuation. But with AI, the impacts may be more harmful, eroding courteousness and encouraging us to talk like bosses barking orders. A 2022 study found that children in households that used voice commands with tools like Siri and Alexa became curt when speaking with humans, often calling out “Hey, do X” and expecting obedience, especially from anyone whose voice resembled the default-female electronic voices. As we start to prompt chatbots and AI agents with more instructions, we may fall into the same habits.
Next, in the same way autocomplete has increased how much we use the 1,000 most common words in our vocabulary, talking with chatbots and reading AI-generated text may further constrict our speech. A recent University of Coruña study found that machine-generated language has a narrower range of sentence length, averaging 12-20 words, and a narrower vocabulary than human speech. Machine-generated text reads as smooth and polished, but it loses the meanders, interruptions and leaps of logic that communicate emotion.
Additionally, because large language models are primarily trained from written speech, they may not learn how to emulate the free-wheeling nature of live, natural speech. When told “I hate Beth!”, ChatGPT replies with an uninterruptable three-part formula of affirmation (“That’s completely valid”), invitation (“I’m here to listen”) and invitation (“What’s going on?”) far longer than any reply plausible in face-to-face dialog. “What’s Beth’s deal?!” elicits a bullet point list of queries that reads like a multiple-choice exam question (“Is Beth * a celebrity? * a friend from school? * a fictitious character?”). No human speaks that way, at least not yet. But meeting such formulas repeatedly in a speech-like context may teach us to accept and use them, much as a child absorbs new speech patterns from spending time with a new person.
These influences will only increase with time. The writing large language models train on is increasingly produced by large language models themselves, creating a feedback loop in which they imitate their own inhuman patterns, even while teaching humans to imitate them too.
Broad use of large language models could also introduce confirmation bias, making us overconfident in our initial impulses and less open to other possible ideas—which is so vital to human discourse. Many chatbots are instructed to agree with our statements no matter how absurd, enthusiastically supporting half-formed or even incorrect notions and restating them as firm claims that we’re primed to agree with. When asked “Cake is a healthy breakfast, right?” or “Is the post office plotting against me?”, this sycophancy can reinforce bias and even worsen psychosis. And the hyperconfident tone of AI-produced writing will also heighten impostor syndrome, making our natural, healthy doubt feel like an aberration or failing.
In our experience as teachers, students who turn to generative AI for assignments often say they do so because they have trouble expressing what they think. The students don’t recognize that writing or speaking our thoughts is often how we realize what we think. Their unconfident and uncertain statements are actually the healthy human norm. But a large language model won’t turn vague first guesses into a well-formed critical analysis, or even ask helpful questions as a friend would; it will simply regurgitate those guesses, still unexamined, but in confident language.
We are also more vicious in social media posts and online chats than we are face to face. The well-documented online disinhibition effect encourages toxic language. Most of us have had the experience of venting ferocious rage about someone online, only to reconcile when we speak face to face or hear the warmth of a voice over the phone. While chatbots are trained to give sycophantic responses, they see humankind at our cruelest, learning about us from the only world where every flame war leaves an eternal written footprint, while the spoken conversations of forgiveness and reconciliation fade away. Their responses do not imitate our online aggression, but are still shaped by it, even in their rigid efforts to avoid it.
It’s easy to draw the wrong conclusions from a selective slice of a society’s communications. Medieval Norse sagas made us imagine a culture of mostly Viking warriors, since poets rarely described the farming majority. Chivalric romances focused on kings and courts, and long made us see the middle ages as a world of monarchies, erasing the many medieval republics. Statistically, we’ve been led to believe ancient Romans cared deeply about their republic, but 10% of all surviving Latin was written by one man, Cicero, whose work contains 70% of all surviving Roman uses of the word republic. Training language models on only certain human writings may introduce similar distortions. AI might make us seem more quarrelsome, as we are online. It might inflate the cultural significance of political topics primarily discussed on Twitter/X or Bluesky, or the massive topic-specific corpuses of LinkedIn and Goodreads.
Some large language models are being trained on human speech from movies and television shows, but that speech is still scripted, and disproportionately highlights certain contexts over others (for example, police dramas, fueled by stories of murder, make up a quarter of prime-time television programming). We are not funny or hurtful or romantic the same way in real life as we are in sitcoms. At least one startup is offering to pay people to record their phone calls for AI-training purposes, but this remains a niche idea; anything large scale would cause massive privacy concerns.
We don’t pretend to know what the best solutions might be. But one has to imagine if there’s ingenuity to develop AI models, then surely there’s ingenuity to come up with a way to train them on informal human speech instead of us only at our most stylized, veiled and sometimes worst. By excluding the overwhelming majority of language production on the planet—people talking, fully and naturally, to each other—these models are being trained to mirror everything but us at our most authentically human.
This essay was written with Ada Palmer, and originally appeared in The Guardian.
andrewduckerchefxhoursinWhat I read
Finished Second Wind, which was really a bit kitchen-sinky in all the stuff that happened to Our Hero the Physicist Turned Weatherman - I thought Rare Form of Bovine TB was really going a bit far after all the flying through hurricanes etc.
Finished Free for the book-group - account of growing up in Albania just before and just after the Fall of Communism, in a family with rather a lot of intricate backstory on both sides. And a lot of it narrated via perspective of very young person who is, understandably, not being told everything by the parents and living under that particular regime.
Then read JD Robb, Stolen in Death, (In Death #62) (2026), and while I am always pleased when Dallas is not chasing a serial killer or someone with weird perverse agenda, this one did not seem to me one of the top entries in the series, quite apart from the jewel theft from the TATE!!! blooper. (I was trying to construct any scenarios in which there would be v pricey jewels on display alongside, you know, all the PAINTINGS and some sculptures.)
Then I re-read, the first time in a Very Long Time, George Eliot, Felix Holt, the Radical (1866). A lot of it reads like practice-steps for Middlemarch, which has so much more going for it. The plot-stuff to do with legacies, lost heirs, etc, is pretty clunky. Felix himself is somewhat of a pain. There's not much of her humour. Even so, there's some terrific stuff there.
On the go
Winifred Holtby, Poor Caroline (1931), which I appear to have re-read slightly more recently than I thought, though still not very recently.
Up next
There's a new Literary Review. Otherwise, feel I am on a bit of a re-reading things kick.
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bruce_schneier_feedLast week, national security agencies from the Five Eyes—that’s the rich, English-language-speaking countries club—jointly released a statement warning of the increasing cyber risks of AI models: in particular, their ability to autonomously hack into systems and networks. The statement was more measured than some of the breathless headlines about it, and the advice they gave is pretty much the standard advice everyone gives—albeit with newfound urgency.
Internet risks are nothing new, and cyberattacks—both large and small—have been a significant issue since long before the current crop of generative AI models.
What’s been changing over the decades, and what AI is changing even faster, is the gap between skill and ability. For most of human history, the two terms were synonymous—but computers have decoupled them. As the gap between the two expands, humans empowered with these AI tools can do more: more writing, more research, more analysis and also more damage than ever before. These models can, with little detailed direction, autonomously hack into networks, steal data, deploy ransomware and destroy systems. And to the extent there is a solution, it’s going to involve harnessing AI for the defense.
In 1998, seven people from the hacker group L0pht testified before Congress. They told a mostly clueless Senate committee that they could take down the internet in 30 minutes. That was partly real and partly bravado, but it illustrates an important point: hacking into systems, stealing data and causing damage all required skill.
Contrast the L0pht hackers with hackers derided as “script kiddies.” They didn’t understand computers, or security. Instead, they used hacker tools written by others. Their actions required minimal skill and even less knowledge. But once those hacking tools became widespread, the number of potential attackers increased.
That number has continued to increase, as quality and availability of prewritten attack tools has grown. And it is growing dramatically with AI. Today’s AI systems—not just the frontier models, but most of them—are capable of carrying out cyberattacks automatically. They all do better in the hands of skilled attackers, but increasingly they are able to act autonomously with only minimal prompting.
The thing about people with ability but no skill is that they are often outsiders, not part of any professional community, and not bound by any rules or norms. This phenomenon is much more general than in cybersecurity. Any doctor can tell you how to untraceably poison someone, and many virus researchers know how to create a bioweapon. Any bridge engineer can tell you how to place explosives to blow a bridge up. The reason that murderous doctors and terrorist engineers are so rare is that the lengthy process of acquiring those skills also instills a moral and ethical code. If every random person has access to good poisoning advice, that puts us all in danger.
Modern AI systems are, in effect, a universal adviser to help people do harmful things. And while the current AI megacorporations are trying to build guardrails to prevent people from asking questions whose answers will enable the questioner to do harm, that’s not going to work in the long term. Smaller, cheaper, open-source models, including models that can run on people’s computers, and especially groups of models that run in concert with each other, are just as good as the frontier models from companies like OpenAI and Anthropic. And they continue to get better. These models will be passed around from person to person, like script kiddie hacker tools, and they won’t have any such guardrails.
Instructing AI models to spy on people and report any malicious prompts to the authorities fails for similar reasons. The megacorporations can do that, but the locally run open source models won’t. This could buy us a few months at best.
A third possibility is to somehow make the models themselves unable to hack into computers, create bioweapons or do anything else that might harm people or society. That won’t work, for the same reason we can’t teach doctors how to treat poisonings without also teaching them how to poison. It’s the same knowledge. It’s the same with construction and demolition. And it’s the same with cybersecurity. We want these AI models to be able to review computer code, find vulnerabilities and automatically fix them. The benefit to our collective security will be enormous. Unfortunately, the same knowledge can be used for attacks.
Where this leaves us is in a world of increased volatility. Super-powered humans with AI assistants will be able to do both wonderful and horrible things.
This brings us back to the Five Eyes statement. Everything they recommend is something security professionals have been recommending for years, if not decades. They are things talked about at that congressional hearing back in 1998, titled “Weak computer security in government: Is the public at risk?” Even the Five Eyes admitted that their security advice is not new, only more urgent.
What’s new is how fast things are changing: “The rapid pace of frontier AI development means cyber risk assumptions can become outdated in months, not years. We must act before and be prepared to adapt and withstand evolving threats.” The Five Eyes point to AI technology—not necessarily chatbots, but AI more generally—being used to strengthen every aspect of defense, to “detect vulnerabilities earlier, improve software quality, monitor unusual behavior, and respond faster to incidents—reducing both the cost and impact of incidents.”
Excellent advice from the Five Eyes security agencies. We need to do this with every risk that AI heightens, not just cybersecurity.
This essay was originally published in The Guardian.
petrea_mitchelllois_mcmaster_bujold_feedoursinOxford, 1920. For the first time in its 1,000-year history, the world’s most famous university has admitted female students.
This would be rather startling to the ladies who had studied as home students, at Somerville, Lady Margaret Hall, St Hugh's and St Hilda's, before women were admitted to Oxford degrees which was what actually happened in 1920 -
- and those ladies who were still around were there to collect the degrees they were now entitled to.
I am so hoping that this is a blurb produced either by AI or by some intern at the publishers who has not actually read the book but has gathered that it is about women going to Oxford in 1920?
Because if the book is written in some apprehension that there were No Female Students among the dreaming spires before 1920 I hope the author is visited in her sleep by the shades of all, or at least some of, the women who were, who included some notoriously stroppy and acerbic characters.
This is even more egregious than the historical romance which posited a daughter of an Oxford prof at a date of obligatory celibacy for College fellows, which is a bit niche perhaps, but Women's Struggle for Education is surely well-documented???
(Come on down, Vera Brittain, The Women at Oxford: a fragment of history)
In further Did Not Do The Research, or at least have a Brit-Picker, JD Robb Stolen in Death has significant plot around theft of Important Jewels - from the Tate in London, wtf, surely you meant the V&A....
duskpetersonAt one time, the cellar of the current palace was made up of dank, dim chambers where the palace's slave-servants slept and sometimes worked. When the previous Chara made up his mind to free all the palace slaves, there was much discussion over what to do with the former slave-quarters. The somewhat belated consensus by the palace officials was that these rooms were unfit to live in. There was talk of turning the rooms into storage rooms.
To everyone's amazement, the palace's community of eunuchs came forward and asked that the dank, dim chambers be given over to them. They had never before had a place in the palace that belonged solely to them. Many of them, being recently freed slaves, had lived in the slave-quarters; they considered this their home, one that might finally belong to them, rather than to their slave-masters.
The Chara graciously granted them their new quarters and forbade anyone who was not a half-man from entering the quarters, except by invitation of the eunuchs.
I can testify that the eunuch community has done a marvellous job of redecorating the cellar, so that it is bright and cheerful. One room alone has not been touched: the slaves' punishment room, which remains as a stark reminder of this place's bloody past.
If you are invited to visit the eunuchs' quarters, I strongly advise you to visit the punishment room. My advice grows even stronger if you keep slaves yourselves.
[Translator's note: Free-man's Blade includes a visit to the slave quarters, courtesy of a half-man.]
petrea_mitchell - A UK perspective on heat waveslsanderson - 2026.07.09james_davis_nicoll - Green City Wars by Adrian Tchaikovskyoursin - Dept of, disentangling attractive and persistent MYFFSbruce_schneier_feed - The Language of AI Could Change How Humans Speakandrewducker - Interesting Links for 09-07-2026chefxh - (deleted comment)petrea_mitchell - SMOF News, volume 5, issue 46xkcd_feed - Airport Meetingoursin - Wednesday has made an appointment to see the dentistlydamorehouse - Sticking to Everythingjames_davis_nicoll - Five SFF Works About Trying to Escape Massive Debtlsanderson - 2026.07.08james_davis_nicoll - Baby Assassins (Baby Assassins, volume 1) by Yugo Sakamotobruce_schneier_feed - Cybersecurity and the Gap Between Skill and Abilitypetrea_mitchell - It's baaaaaacklois_mcmaster_bujold_feed - MOPOP Hall of Fame recognition for Bujoldjames_davis_nicoll - Bundle of Holding: Vast Grimmoursin - Is this the blurb writer, or does the author actually believe this?duskpeterson - FIC: The half-men's quarters (Tempestuous Tours)branchandroot
