Two events recently have made me think about the last 55 years in a different way. The first was the last Birmingham Science Fiction Group meeting, which we had dedicated to a 55 year anniversary celebration for the group (the 50th anniversary having been pandemicked). We had a cake, illustrated by David Hardy’s Stratus Hotel, and we showed a film of interviews from members across the years, again featuring some of David Hardy‘s artwork, with stories about guest speakers from Asimov to Frank Herbert to Iain Banks to Jack Cohen and very frank recollections from our current honorary president, Alastair Reynolds. If you want to see the film, you need to join the Group, which you can easily do by emailing us at contact@brumsfgroup.org.uk. Seeing some of the original organisers talking about some of these meetings like they had just happened made me reflect on how we often attribute significance to things after the event and tend to downplay things happening around us now. Things are both never as good or important as they used to be and, of course, as we prove to ourselves over and over again, they also are.
The other event was a visit with my brother and his wife to where we used to live, in the officers’ married quarters of an RAF station in Yorkshire, 55 years ago, when I was eight. Just standing on this patch of grass, with a field of wheat still growing the other side of the fence (to the right), I got a very strong sense of another way of getting from there to here. Obviously there was the one I had taken, with countless house moves, school moves, marriages, careers, children, holidays, illnesses and death and grief and so much joy and laughter in the very fortunate and privileged life I have lived.
But what if I had just stood here and the 55 years had just sped past me instead. My Liverpool football kit would have been a bit tight, with the number seven sewn on the back by my Mum (actually that might have been the following year, when the full magnificence of Kevin Keegan had become apparent). Or, much more spookily, if the eight-year-old just found themselves on the same patch of grass 55 years later in a Wells’ The Time Machine kind of way. It all suddenly felt just as possible and plausible, as if the 55 year old football-and-everything-else pitch was still there within touching distance somehow.
The thing is, I could understand the world of 1971, once I had been reminded of a few things no doubt. A world of cash (just decimalised so no shillings and old pence), phones fixed to houses and telephone boxes, smaller cars filled with leaded petrol, three channels on the black and white TV. I had just driven up there in a car with bodywork comprising mostly plastics, with no spare tyre and no wallet. Just a device known as a mobile which can not only make calls, but send and receive text messages, carry out all my financial transactions and navigate me to my brother’s house. My eight-year-old self would recognise very little about this world beyond the patch of grass he stood on and the field beyond the fence where he had parachuted his mother’s childhood teddy bear.
And this is the terrifying thing about life: we are all that eight-year-old facing the incomprehensible future, and so much of what we spend our time doing is trying to deal with that fear and lack of understanding with often meaningless structures and practices and customs to ward off the sense of being totally out of control. Trump is scary because he appears to have taken a lot of the guard rails off the path we are on, with little sense that he understands what he is doing. AI is scary because it is putting its foot on the accelerator before we have a clear idea of where we are going. Climate change is scary because we no longer look like we are headed where we thought we were.
And we try and stick some grit in the wheels to slow down the disruption to our own little bit of the world, whether to our sense of ourselves, or to how we think life should be lived. And sure we need to question whether we need to change things which are working perfectly well, but often the driver for resisting change is fear of what we don’t know is coming and finding familiar things irresistibly reassuring.
And when we realise that it is not just us with our, certainly in my case, fairly small and unimportant lives (although obviously very important to us!), but also the people who seem to be shaping the world around us that feel these insecurities and uncertainties, the possibility of working together to make it easier to adapt to the very weird future that is coming suddenly doesn’t seem so outlandish after all.
I think this – what we resist, what we create and what we could nurture in the face of this terrifying future – is what I am going to be writing about for the rest of this year, as we all rattle on down the road in the back of someone’s van.
What We Can Know by Ian McEwan is a difficult book to categorise. Some might call it “cli-fi”, as it sets itself in a future significantly altered by human actions and the landscape’s response to those. The Sunday Times appears to think that it might have created a new genre entirely. I think it is best seen as an Oxford novel, even if many of Oxford’s landmarks are submerged for large parts of it. Radiohead even gets a mention. As the petty snobberies and clandestine affairs of academics play out on the much-changed landscape of 2119, earnest academics Tom Metcalfe and Rose Church explore the petty snobberies and clandestine affairs of 2014 and the quest for the long-lost poem from that year. “A Corona for Vivien” certainly feels like a poem which belongs in a past of barn conversions and dinner parties.
For these academics, The Derangement – which is how they refer to the developing crisis mindset between 2015 and 2030 – is just a backdrop to what they regard as the important drama of their lives. It is followed by the first of several climate wars in 2036 involving nuclear weapons, ironically causing a cooling before the Inundation of 2042 causes the deaths of 200 million, with the UK’s population halving and life needing to be eked out on a cluster of small radioactive islands.
I set this out because the book, while occasionally referring to the eeriness of things, carries on with the work obsessions and love lives of its characters pretty much regardless. If What We Can Know is to be believed, academia carries on much as before, with lectures and seminars and essay marking, despite all of this. For humanities departments currently under the cosh despite the absence so far of a nuclear war, this may seem unlikely.
My grumpiness about all this may be partly due to the fact that I am writing this during a series of record breaking heatwaves and unbudgeable heat domes, but I feel like I have had to make more accommodations to the climate – cancellation of plans, a whole new routine at home with the single aim of keeping the thermometer from moving up any further – than McEwan’s characters seem to be doing in their post-not-quite-apocalyptic lives. Whereas one visit to the swimming pool last month was reduced to bobbing about in water along with a couple of dozen others in a manner reminiscent of the wet bulb event at the start of Kim Stanley Robinson’s The Ministry for the Future, McEwan’s only concession to a future world that can still apparently support an academic entirely focused on a 105 year old poem which has never been seen since, seems to be that journeys anywhere are now more difficult and dangerous.
And yet Tom then travels to Snowdonia (where the Bodleian is now housed) fairly easily. And he and Rose then travel to the flooded valleys of the Cotswolds to attempt to retrieve the poem. The only difficult journey described is once they get on to the target island and have to navigate through thick vegetation without satnav (GPS is no more) or even rudimentary hiking skills between the two of them. At one point we are told the internet is on the way out and at another that there is a National Artificial Intelligence which remembers everything you have ever told it.
This book seems as complicit in the “crisis of realism in fiction” as McEwan, via Rose, accuses everything else written between 2015 and 2030 of being. However it is an entertaining Oxford novel, with tense conversations in parked cars and breathtaking egomaniacs everywhere you look.
What we can’t know is what Tom and Rose will make of it in 100 years’ time.
As I discussed in How Not To Be A Reverse-Centaur (Cory Doctorow defines a reverse-centaur as “a machine that is assisted by a human being, who is expected to work at the machine’s pace”) our actuarial education system needs to change. This has been true for some time, but the development of AI systems has both demonstrated why more clearly and accelerated the timeframes over which action is needed. As I said in December last year:
A large part of the education of the future will need to be about equipping us all to understand what we now have access to and when and how to access it. We will all have different things we are interested in, or end up involved with and needing to be educated about. It will be up to each of us to decide which things are worth the difficulty of learning, but to make those decisions we will need education that can support the development of judgement.
For education institutions, the question will be what is not worth the difficulty of learning? Credentialising based on now relatively meaningless assessment methods will not cut it. This is where the confrontation with employers and politicians is likely to come. Essential skills and their related knowledge will be better developed and assessed via more open-ended project work and online assessment of it to check understanding. These will need to become the norm, with written examinations becoming less and less prevalent. Not because of fear of cheating and plagiarism, but because an outcome which can be replicated that easily by AI is not worth assessing in the first place.
Suppose you were to ask someone who had never seen our academic system that, in order to assess whether someone else we wanted them to employ in their organisation would do a good job for them, we would:
Award marks for what has been written in answer to academic questions about what the students can remember unaided about the content of their lecture courses and reading lists with a biro on a pad of paper perched precariously on a tiny wooden table surrounded by hundreds of other similar scribblers, for a set period of time as minders wandered the floors like Victorian factory owners.
These marks would be based on marking criteria they would never see.
We would then get together in a secret huddle for a couple of months to mark all these scripts, check them and “moderate” them to check they were in line with the previous years’ exercises.
Then out would come the answer (like the Answer of 42 to the Ultimate Question of Life, the Universe and Everything in Douglas Adams’ The Hitchhikers Guide To The Galaxy).
Imagine another world where the kinds of things employers routinely do when trying to decide whether to take on someone as a new member of their organisation are routinely part of their assessments at university, eg:
Watch them operating in groups working on a task.
Ask them to describe how they would go about tackling a particular problem.
Get them to show they understand the implications of a piece of work they have carried out and can explain what assumptions it is based on and can justify them.
With assessments of performance which are not opaque academic exercises but descriptions of performance made as the tasks are being carried out evidenced by video if necessary. In other words, transparent enough to whoever might want to work with these students next to eliminate the gap between their credentials and and their actual actionable skills, knowledge and experience.
Assessing in this way will be highly demanding, for both the students and the assessors, but it means the final assessment is done with the student present and, with careful probing from the assessors, who will obviously need to have done a close reading of the project work beforehand, confidence will be high about the abilities demonstrated by the process. And it removes the need for all the time currently spent on the Victorian factory owner process – imagine what could be done if the whole of May, June and July wasn’t spent marking scripts!
A move like this will significantly change what is taught. There will be no point presenting lots of information in ways which make retention easier for students (the so-called bookwork” questions currently in most exams). This makes sense when you think about how much of the content of your courses is accessible to you now, even on a vocational course like actuarial science, as opposed to skills developed. Instead the focus will be more on conversations with students for the purpose of developing their understanding of a meaty topic and the problems to be solved within it. Explorations of these will form the projects students will be spending most of their time working on. Checking understanding and making sure students are working within frameworks they understand and can talk about will be the main teaching activity, with opportunities to practise these throughout the year. In other words, showing the ability to apply what they have understood and demonstrate the ability to reflect, make judgements and show higher levels of understanding as a result. An ability they can then apply to new problems and situations.
And notice something else about how these alternative credentials are generated? They are all social activities: from operating in groups, to presenting a piece of work to a group of assessors. Even the project work is developed through group sessions alongside individual work. If you want to develop people who can spot the gaps between models and reality you need to do it in groups, where people can test their perspectives against each other.
Compare this to the current solitary exam preparation, peppered with “revision” lectures, exam sitting and exam marking processes which comprise the predominant activities in universities between March and July each year. We are currently being funneled into an ever more solitary professional practice around LLMs. It has become quite accepted for people to do all of their thinking on a subject closeted with perhaps one, two or three LLMs but no other people and then share their analysis with an expectation that other people should read the output. Developing the skills to do these analyses will obviously be necessary, but they will never be the most important skills people learn.
Treating each other like walking databases is never going to make you new friends or influence people. However the skills you develop via an alternative more social education will.
There are examples of this approach already happening, with employers involved in the design of assessments in some cases and universities using the flexibility they have to restructure and redesign courses. But the dominant assessment system of formal exams is keeping much of this activity at the margins at the moment.
If it were to become the dominant assessment, it would also mean that larger areas of the curriculum could be examined, as the focus would not be on retention of large bodies of content but the ability to use the content to solve problems. So, perhaps, after a first year levelling up students’ ability and experience of mathematics and statistics, year 2 would have an actuarial statistics module (currently CS1/CS2) and an actuarial mathematics module (currently CM1/CM2), both dissertation based and vivaed. Then in the third year they would tackle an economics module and a business modules (currently CB1 and CB3). Perhaps in the final year of a four year MAct they would tackle a modelling and communication module (CP2/CP3) and either CP1 actuarial practice module would be offered or a professional skills module.
This would be more of a driving test style of assessment, with students working with supervisors on the comments from assessors on the original dissertations and presentations until they were up to the required standard. Students unable to make the standard after an additional year would be offered a move to a non-accredited course. The current funding model for higher education will need to change: loading students with £10,000 more debt every time they add to the nation’s skills bank with another year wrestling with these difficult skills to master was never a clever strategy, but this structure would make it even clearer how self defeating it is. If economists are accepting that the labour market no longer allocates resources effectively and are considering either a universal basic income or universal basic services, then logically university funding should follow suit.
The implications for the actuarial profession will be even more challenging. I question whether the Institute and Faculty of Actuaries will continue to consider it worth the effort and expense of reconfiguring their entire approach to exam setting, syllabus maintenance, marking, online proctoring, etc for subjects routinely taught throughout the university system for a a variety of purposes, ie the current core principles subjects of mathematics, statistics and business studies.
Whether they retain their own capacity to assess the core practice subjects is a more open question (CP1 Actuarial Practice, I imagine, will be seen as sufficiently specialist to keep in house, with perhaps a few universities, as now, accredited to run courses which can earn this qualification, however CP2 Modelling and CP3 Communications are not nearly as specialised now as they seemed when they were first introduced). I would also move the new core economics module recommended by the IFoA Economics Review Group I chaired in 2022 to replace the current CB2 module into the core practice section, as it would be more of a critical thinking module about the economic ideas necessary to underpin good actuarial work than the technical how-to subjects in core principles.
The specialist stage of the SP and SA subjects and the whole continuing education and additional certification options I would confidently expect the profession to retain, review and adapt as needed to reflect new challenges in members’ working lives. However, if CP1 is all that is needed post graduation to get to Chartered Actuary and CP1, two SP subjects and a SA subject gets you to Fellow, then suddenly time to qualification becomes much more predictable for students and their employers alike.
The risks to employers of taking on students would therefore be reduced, but also the rewards to taking them on will be much more transparent. The students we will be developing will have collapsed the gap between their credentials and their actual actionable skills, knowledge and experience. They will have:
Great team working skills;
Very highly developed presentation skills, both in writing and speech;
Strong IT skills and comfort working with data; and
Clarity about why they are in an organisation and a drive to use their skills to solve problems.
Epistemic rigour. They will be more likely to spot when a system or model is over-confident given the evidence, after an intense experience of interrogating models and evaluating evidence in their courses.
Synthesis. They will be able to integrate different perspectives into an overall understanding, through dissertation development, defending a position, understanding weaknesses in a position and adjusting accordingly.
Judgement. They will have been asked to make many judgements in their work and had to defend them in discussions with their supervisors and fellow students. Unconvincing opinions, not backed by evidence, will not pass muster.
Cognitive sovereignty. Students will have to take their own stand on their work, after all of the challenge and argument. Independence of thought is the hard-earned outcome here.
And then they will have a fighting chance of being centaurs in the world awaiting them, masters of the technology and opportunities available, rather than the reverse-centaurs that our education system is currently, and inadvertently, preparing them to be.
This review originally appeared in the May issue of Brum Group News, the newsletter of the Birmingham Science Fiction Group and is reproduced here (lightly edited) by kind permission
This book is so many things: a work of fantasy, a literature review of every major work about the journey into hell, a love story, a wicked academic satire, a philosophical musing on the meaning of life and a love letter to Cambridge. Or perhaps the title itself, which means both a retreat to the coast, in this case to the banks of the River Lethe, as well as a descent into Hell. Like its Oxford counterpart before it – Babel – its central leap is that magic (here referred to as magick, ie the academic discipline stretching back to the alchemists and beyond) sits alongside the other subjects at Oxbridge colleges. The magic we see practised, taught, researched and dissertationed feels very mathematical. So we are unsurprised to hear that the mathematicians hate the magicians.
Alice Law is the Chinese-American PhD student of the great Jacob Grimes, who (accidentally?) sends him to Hell and then, with her once-friend-now-mortal-enemy and Grimes’ other PhD student, Peter Morgan, sets out to bring him back. So that Grimes can pass their dissertations, because that’s a good enough reason to journey to Hell and sacrifice half of your future lifespan. And so the quest begins.
There is quite a bit of mathematical fun had despite Alice not really knowing any mathematics, including an Escher Trap, a Penrose Staircase and a hyperbolic geometry which makes the quest very heavy going at times. And so many logic puzzles. Comedy and total horror are nicely juxtaposed throughout, as Alice and Jacob get to understand each other better and start to wonder whether Grimes is worth it after all.
The constant side swipes at the life of a junior academic are often hilarious. Magicians in training are apparently told by all their professors that they should consider careers in other fields or “alt academia”, as they called it:
“…no one really meant it when they said alt academia was just as prestigious (or, more commonly, that there was no shame in it, really). They meant it even less when they emphasized that alt academia paid better, had kinder hours, was less stressful, gave you better job security, made you happier. Oh, magicians do really well in consulting, they said. Employers like critical thinking and problem-solving skills, they said. Fewer people die in industry, they said.”
The most enigmatic character is their not-quite-constant companion, Archimedes the cat, who guides them when he feels like it. All the way through all eight of the Courts of Hell, alongside and across the Lethe and finally to King Yama’s Domain, on a journey which threatens to destroy Alice’s very sense of self. Her catechism, which she repeats at stressful moments:
I am Alice Law I am a postgraduate at Cambridge I study analytic magick
Alice has always felt that if she could just hang on to the delusions which had got her this far until the end of her PhD all would be well, but these turn out to be precisely the things she needs to confront if she is ever going to get out of Hell.
Shakespeare appearing in the play he has written in order to say goodbye to his dead son
“You are not saying what you think you are saying” was what Ray Nayler said to the Birmingham Science Fiction Group on Friday night, as part of a wider conversation about the mutual misunderstandings that result from cultural differences. He had landed up with the Peace Corps in Turkmenistan 20 years ago, “The worst place to live in the world”. It ripped away his sense of stability and the fixed nature of life he had developed growing up in San Francisco and made him realise that everything is arbitrary. His new book Palaces of the Crow is out next week, about a group of escapees on the run in a forest trapped between the German and Soviet armies in World War 2, with only a murder of intelligent crows as allies. I will be buying it.
And so to a different forest.
Last night I could not speak for half an hour. My face ached from the effort of holding myself together and tears were running down my face. No I wasn’t in the back of an ambulance on my way to Good Hope Hospital. I had just watched Hamnet for the first time.
I am peculiarly sensitive to father-son depicitions in art. I can’t remember when a film affected me as deeply as Hamnet did, but I do remember the last book that had me in floods of tears (The Road by Cormac McCarthy when (spoiler alert) the father of the boy dies. Suggest you don’t read it on a train like I did). Why should I cry for you by Sting also tends to have me in bits.
However Hamnet was still like nothing I have ever experienced before in a movie. It snuck up on me, this story of the fight to make a family and then keep it alive in a way that certainly didn’t feel over 400 years old before hitting me with the final scene which was, ultimately stagey for goodness’ sake. I felt connected – to the forest, to the plague-beset 16th century characters, to everyone who has ever lost a child, to everyone looking for connection to help them through their day. I have watched so much Shakespeare in my life, but I have never felt the urgency that must have lain behind the plays quite like this before.
This was just great art. Not in a way that impresses you but leaves you cold, but in a way that you realise has expressed the driving forces of life directly at your central nervous system.
And how close the film was to what really happened doesn’t matter. Any more than the plot accuracy of any of Shakespeare’s plays matters. It was emotionally true and believable and mourned the death of a child as every child death should be mourned. It made nearly every other movie I have ever seen seem trite by comparison, including the hugely entertaining but ultimately much less full Oscar rivals this year. This is the movie you stick on the next gold disc sent out on a probe into deep space to explain humanity.
And it immediately started me thinking about how infrequently I experience emotional truth outside my friends and family. Is this the missing component from public life?
Keir Starmer certainly wasn’t passing any auditions this morning. He was not saying what he thought he was saying. He thought he was saying something about training young people, being “at the heart of Europe” and nationalising British Steel. What he was actually saying was that he has no idea why he lost 1,496 English council seats over the weekend but, despite this, was going to hang on until someone removed him forcibly from office. And he is guessing, perhaps rightly, that the Labour Party does not have the determination to do so. It was the precise opposite of emotional truth or, as John Elledge posted:
“You are not saying what you think you are saying” is unfortunately true for nearly all of us nearly all of the time. Until it isn’t. And those moments when it isn’t are moments of enormous power.
And to think I still have Maggie O’Farrell’s novel to read. Or possibly the audiobook read by the great Jessie Buckley, Agnes Hathaway herself. May be hard to resist.
The Wetherspoons pub The Mary Shelley in Bournemouth
A few months ago I decided to read Mary Shelley’s Frankenstein for the first time. I also watched Guillermo del Toro’s Frankenstein, on a big screen, despite, according to The New Yorker, it having been “Netflixed down to size”.
Shelley’s book is largely monologues of interior thoughts of Frankenstein and his creation, with wildly careering emotions and death, death, death everywhere – perhaps unsurprising from an author whose mother died 10 days after giving birth to her, who lost a child and whose half sister died by suicide while she was working on Frankenstein, with much more tragedy to follow after its publication. There is a word Mary Shelley uses more than I have read in any other book: variants of sympathy/sympathise/sympathies turn up 32 times. Because of course one of the many things the book is all about is mutual incomprehension of the creator and the created.
Last week I was in Bournemouth as a last minute substitute for Lanzarote, something I may come back to at a later date, and I stumbled across the churchyard of St Peter’s Church in which Mary Shelley was buried, along with the cremated heart of her husband Percy Shelley, at the age of 53. There is also a pub in Bournemouth named after her (above) but whose sign depicts the monster from her most famous piece of writing.
As we enter another time of mutual incomprehension of the creator and the created, I have been reading the surprisingly-difficult-to-access paper by Kyle Kingsbury (the systems engineer, not the MMA guy) called The Future of Everything is Lies, I Guess. I will put a link to an X account which shared it here, as going to the aphyr.com site to read it seems to generate this message:
Once you can read it though, it starts to sketch out a likeness of our current monster and chip away a little at the human side of the mutual incomprehension. I am talking, of course, about what people are currently calling “AI”, which Kingsbury defines as:
…a family of sophisticated Machine Learning (ML) technologies capable of recognizing, transforming, and generating large vectors of tokens: strings of text, images, audio, video, etc. A model is a giant pile of linear algebra which acts on these vectors. Large Language Models, or LLMs, operate on natural language: they work by predicting statistically likely completions of an input string, much like a phone auto-complete. Other models are devoted to processing audio, video, or still images, or link multiple kinds of models together.
The article sets out how this is a technology where nobody really understands why it has been successful or how to make it better, which falls into strange loops or attractors, has odd gaps in its capabilities and is highly sensitive to slight changes in its formatting. It is a technology which is simultaneously highly capable and an idiot. And Kingsbury worries that our culture is not ready for such a technology. As he says:
As LLMs etc are deployed in new situations, and at new scale, there will be all kinds of changes in work, politics, art, sex, communication and economics. Some of these effects will be good. Many will be bad. In general, ML promises to be profoundly weird.
Buckle up.
He continues:
Most people seem concerned with conscious, motivated threats: AIs could realize they are better off without people and kill us. I am concerned that ML systems could ruin our lives without realizing anything at all.
There follow extensive examples of the problems the various ML applications are already starting to cause and some speculation about where things may be going in various areas of our lives before we get to the chapter on work. And the subject of hiring “AI employees”. This is probably my favourite bit:
Imagine a co-worker who generated reams of code with security hazards, forcing you to review every line with a fine-toothed comb. One who enthusiastically agreed with your suggestions, then did the exact opposite. A colleague who sabotaged your work, deleted your home directory, and then issued a detailed, polite apology for it. One who promised over and over again that they had delivered key objectives when they had, in fact, done nothing useful. An intern who cheerfully agreed to run the tests before committing, then kept committing failing garbage anyway. A senior engineer who quietly deleted the test suite, then happily reported that all tests passed.
You would fire these people, right?
Kingsbury sees the two extremes of the possible range of outcomes as:
ML systems continue to hallucinate, cannot be made reliable, and ultimately fail to deliver on the promise of transformative, broadly-useful “intelligence”. Or they work, but people get fed up and declare “AI Bad”…a lot of ML people lose their jobs, defaults cascade through the financial system, but the labor market eventually adapts and we muddle through. ML turns out to be a normal technology.
In the other extreme, OpenAI delivers on Sam Altman’s 2025 claims of PhD-level intelligence, and the companies writing all their code with Claude achieve phenomenal success with a fraction of the software engineers. ML massively amplified the capabilities of doctors, musicians , civil engineers, fashion designers, managers, accountants, etc, who briefly enjoy nice paychecks before discovering that demand for their service is not as elastic as once thought, especially once their clients lose their jobs or turn to ML to cut costs. Knowledge workers are laid off en masse and MBAs start taking jobs at McDonalds or driving for Lyft, at least until Waymo puts an end to human drivers. This is inconvenient for everyone: the MBAs, the people who used to work at McDonalds and are now competing with MBAs, and of course bankers, who were rather counting on the MBAs to keep paying their mortgages. The drop in consumer spending cascades through industries. A lot of people lose their savings, or even their homes. Hopefully the trades squeak through. Maybe the Jevons paradox kicks in eventually and we find new occupations.
In the following chapter Kingsbury speculates on what some of those new occupations might be:
Incanters. People who can prompt LLMs into getting what is wanted.
Process Engineers. People who help catch LLM errors. They build quality control processes – training people, identifying where more intense review is needed, assessing the cost-benefit trade offs of automating tasks, etc
Statistical Engineers. People who try and measure, model and control variability in ML systems.
Model Trainers. This will become increasingly difficult as the amount of false content or “slop” increases across the internet.
Meat Shields. People who are accountable for the errors of the ML systems they supervise.
Haruspices. People responsible for going through the model inputs, outputs and internal states of a ML system which has done something terrible to try and give a plausible reason for its behaviour.
But ultimately Kingsbury concludes that we should just stop using these systems. To return to the original analogy, the monster cannot be understood. There is often nothing actually there to understand. And it is certainly not in the business of understanding you. Although it may be very very good at convincing you otherwise.
On balance I think my view is currently at the muddle-through-with-ML-as-a-normal-technology end, which still looks likely to cause a disruption considerably bigger than 2008. My main reason is the already collapsing trust in many of the Big Tech companies. Trust which is going to be required even if their technology really can do some of this stuff. It is the scenario where we all get fed up and declare “AI Bad”. Like when we read about the people running Meta showing nowhere near the social responsibility commensurate with their current level of market power.
Or when, as last week, we have days and days of breathless commentary about Anthropic’s Mythos and Project Glasswing, and how its immense capabilities caused the company not to release it, sparking a meeting of central bankers to discuss the threat such technologies posed to financial systems. Only to finally read an account of attempts to verify any of what Anthropic have been saying. It is quite a technical piece, which I by no means understand all of, but the final paragraph is fairly arresting:
The most important thing in the Mythos release is not the model. It is the precedent. Anthropic has established, without discussion and without pushback, that a private company can unilaterally classify a capability as too dangerous for the public, grant selective access to the largest incumbents in the affected industry, and construct a parallel disclosure regime outside any democratic accountability structure. That precedent is exclusivity for abuse. It will be used by companies with worse judgment than Anthropic and narrower definitions of “partner” than the Glasswing consortium. The time to object to the shape of this thing is while it is still being built, not after it has removed all transparency and accountability.
How might Claude or ChatGPT respond to being designated “AI Bad”? Well Mary Shelley’s monster put it this way:
Once I falsely hoped to meet with beings who, pardoning my outward form, would love me for the excellent qualities which I was capable of unfolding. I was nourished with high thoughts of honour and devotion. But now crime has degraded me beneath the meanest animal. No guilt, no mischief, no malignity, no misery, can be found comparable to mine. When I run over the frightful catalogue of my sins, I cannot believe that I am the same creature whose thoughts were once filled with sublime and transcendent visions of the beauty and the majesty of goodness. But it is even so; the fallen angel becomes a malignant devil. Yet even that enemy of God and man had friends and associates in his desolation; I am alone.
This review originally appeared in the April issue of Brum Group News, the newsletter of the Birmingham Science Fiction Group and is reproduced here (with light editing) by kind permission
A few years ago the historian Adam Tooze said the following about the times we are living in:
If you’ve been feeling confused and as though everything is impacting on you at the same time, this is not a personal, private experience. This is actually a collective experience.
The word he came up with for this experience was “polycrisis”. It described the interplay of the Covid pandemic, Ukraine war and the energy, cost-of-living and climate crises. To that we could now add Trump 2nd term, war in Gaza and now the Gulf.
I am reviewing this book while I have Covid, which has certainly facilitated the kind of inner focus which I think the book is asking for. Because Slow Gods is polycrisis in the form of space opera, but a curiously interior-monologuey kind of space opera, more psychological than boom-boom.
The premise, as Claire North set out for us at the Birmingham Science Fiction Group last June, is that a binary star system is due to collapse which will obliterate all life within an 83 light-year blast radius. Unusually, the populations in the vicinity are warned of this precisely 100 years in advance by a perfect black sphere moving through space at sub-light-speed and known by everyone as the Slow.
The Slow listens to everything, remembers it and will consider it.
We follow the story through the eyes of Maw, who has been killed and has recovered in such a way as to be very difficult to kill after that. Making Maw an ideal candidate for Pilot, the organic sentient needed in the pilot’s seat of any ship wishing to enter arcspace which lets it travel across the universe faster than light, at huge personal cost. Pilots die frequently and each planetary system has its own way of choosing and rewarding its Pilots. Only Maw appears to be able to act as Pilot again and again, which makes the people around Maw nervous.
The main thing about Maw which makes people nervous is Maw’s relationship with “the darkness” which reaches into any ship in arcspace, in many cases sending people mad. Maw, instead, becomes “curious”, exploiting a changing relationship and perception of matter in the darkness to do monstrous things. But, despite all this, Maw is still required to keep running missions, although usually with a mechanical assistant to keep Maw from getting “dysregulated”.
This unusual set up turns out to be a way of observing the psychology of the polycrisis with some clarity. The United Social Venture is an empire where its subjects acquired debt just from being born (measured in Glint):
Everything the Venture gave us – the air we breathed, the roads we walked down, the schools we learned in – had been sweated for, bled for, and our debts were a marker of the needful labour we would give back in return.
This economic system was referred to as Shine. The Shine were one of the few systems which used prisoners for Pilot work.
One of the joys of the book is the exploration of difference, lots of details about avoiding giving offence when the Xi of Xihanna ask Maw to pilot a ship to Adjumir to bring out historical artefacts and Maw meets Gebre of the Haalo Institute. Maw finds that Normspeak is regarded as a very crude way of communicating and starts, haltingly, to learn Adjumiri (which is at least in part a click language). So begins a very moving love story.
Gender differences between systems are very striking. The Shine have only two genders – “he” and “she” – although the elite also have hé and shé. The most manly and the most feminine.
There are four genders in Xihanna, but they are not regarded as particularly important characteristics of a person and dispensed with once you know someone well. On Adjumir, there are eight, with very few Adjumiris remaining the same gender all their lives. These differences are picked out by the brilliant use of pronouns, a useful technique in a book full of characters. Even mechanicals, who have no particular interest in gender, are referred to as qe/qis as a mark of respect as “they do not wish to be put in the same category as a bowl of soup or a broken chair”.
We join Maw towards the end of the 100 year programme to evacuate the populations of Adjumir and Hadda to relative safety, with 800 million still on the planets and increasingly desperate. The Slow has effectively taken on a role as God through its massive databases, calculation capacity and sheer longevity. It seeks out Maw as it has plans for him. The Slow has been around so long that qe sees everything in the very long run. Which means that the emotional turmoil and intense highs and lows of individual lives are all averaged out to nothing. Qe calculates in terms of galaxy-level populations on the basis of what qe has come to think of as love.
What calculation would the Slow make about our world, with all our nation states and their often tiny differences blown up to justify war aims? Donald Trump certainly has to have the most Shine of any US President for some time.
Slow Gods moves slowly but relentlessly towards a showdown between Maw and Theodosius Rhode, the Executor of the Shine and executioner of his mother. There is much tragedy along the way and the ending is not straightforward but ultimately very satisfying. It’s an uplifting ride.
Front page of the April 2026 issue of Brum Group News
Three and a half years ago, I wrote a piece likening the rapid climate change on Earth to the fairly well-established science fiction concept of terraforming, but in reverse. So what has happened since? Well last summer, according to researchers at Imperial College and the London School of Hygiene and Tropical Medicine, two thirds of the 24,400 heat deaths from June to August across Europe were due to human-made global heating. And a study published last month has suggested that the pace of global warming has nearly doubled since 2015.
It this point I would like to suggest rehabilitating an old word to describe this process, in the opposite direction to terraforming (which is action designed to make a planet more habitable). Barrenize means to make barren or sterile and was used between the mid 1600s and the early 1700s according to the Oxford English Dictionary, originally in the context of animal husbandry. I think it’s time to bring this word back.
In a week when a US President has threatened, variously, “blowing everything up and taking over the oil” and that Iranians would be “living in Hell”, to last night saying that “a whole civilisation will die tonight”, unless they opened the Strait of Hormuz, it certainly sounds like a commitment to barrenization to me, only at a faster pace than the global warming he is already doing everything possible to accelerate further.
On Friday this week, the Birmingham Science Fiction Group will have Oliver Bettis as its guest speaker. Oliver has been a leading actuary in the field of sustainability for many years. He is one of the authors of a series of publications by the actuarial profession in collaboration with the University of Exeter in recent years.
Climate Scorpion shows how we need to develop a best guess about the worst-case scenarios and make policy on that basis, given our lack of knowledge about extreme climate risk and tipping points.
Planetary Solvency – finding our balance with nature sets out an approach to civilisational risk management which attempts to address the fact that the severity and frequency of extreme events are unprecedented and beyond current model projections.
Parasol Lost, which we will be discussing in particular this Friday, focuses on the cooling effect of aerosols: a side-effect of pollution from fossil fuel burning. Without aerosol cooling the global temperature would be around 0.5°C higher than the 1.4°C increase above pre-industrial temperature that we have today. It is critically important to recognise that, as air pollution is cleaned up, this may ironically lead to a short-term increase in warming through the loss of aerosol cooling. The question must be asked, can we afford to lose this cooling and if not, should this be replaced by working with nature, using technology or both?
This will allow us to tap into the rich history of science fiction literature on terraforming (and dealing with the threat of barrenization) and whether this can allow us to look at this question in a new way. It should be a lively discussion.
This event will be held in-person at the Friends of the Earth Warehouse, 54-57 Allison Street, Birmingham B5 5TH and simultaneously on Zoom, with online access opening from around 7.45 for an 8 pm start.
Ticket prices for non-members are £8 for in-person attendance and £6 for Zoom attendance. For members it’s £4 in-person attendance and free Zoom attendance.
Tickets can be purchased on the door or via the Eventbrite link below:
And if this whets your appetite for more science fiction and you think you might like to join the group, just email us at contact@brumsfgroup.org.uk. Hope to see you there!
A week or so ago I referred to a “Thought Exercise” set in June 2028 “detailing the progression and fallout of the Global Intelligence Crisis” (ie science fiction), published on 23 February, which may have tanked the share price of IBM later that day. As I said then, the fall definitely happened, with IBM’s share price falling 13%, its biggest fall since 2000. I said then that the likelihood of the scenario portrayed was difficult to assess, but the speed with which the total economic collapse was described felt unlikely if not impossible. I would like to expand on that.
The main reason that the scenario was hard to assess was that it was not based on data or evidence at all. That is unavoidable for speculative fiction talking about things that are not currently happening, but when describing an economy only two years away where most of the processes described should be discernible to some extent already, it is totally avoidable.
Ed Zitron has done an excellent line by line take down of the Citrini piece here. Here is one page of that to give you a flavour:
However this lack of a link with anything tangible did not stop the financial markets panicking, which should cause us pause when relying on the financial markets’ valuation of projects, industries, government policies, etc.
Ed Zitron describes this kind of piece as analyslop: “when somebody writes a long, specious piece of writing with few facts or actual statements with the intention of it being read as thorough analysis”. It can then get picked up by other commentators which take it as their starting point for further analysis, often making it hard to see that the starting point had few if any data points. Here is an example, from Carlo Iacono, looking at what if just some of the Citrini pronouncements were true, with appendices detailing possible branching paths of outcomes, all generated by a large language model (LLM). And then people start studying the meta analysis, and it starts getting taken even more seriously, and put into models and pretty soon most of the analysis is being done on imagined risks rather than on ones which are already staring us in the face.
We have always had a problem keeping our society grounded in reality, think the 2003 Iraq War, where we went to war on a false assessment about Iraq’s possession of weapons of mass destruction, the 2008 financial crisis, where banks misunderstood the risks they were exposed to, and the last two and a half years, where we, for the most part, seem to have convinced ourselves we have not been facilitating a genocide in Gaza when we clearly have been. But this is only going to get worse with the AI systems which are being developed.
The rapid rise of artificial intelligence has served to dramatically increase the speed of information production while also eroding accuracy, making it difficult to differentiate between content that simply sounds confident and content that’s actually grounded in reality.
So where is AI currently? Well PwC’s global CEO survey from January this year had the following statement as the first bullet amongst its key findings:
Most CEOs say their companies aren’t yet seeing a financial return from investments in AI. Although close to a third (30%) report increased revenue from AI in the last 12 months and a quarter (26%) are seeing lower costs, more than half (56%) say they’ve realised neither revenue nor cost benefits.
That’s the reality. But the hype is much much more entertaining. My favourite spoof video of the AI future currently is this one, about the time where all most of us are good for is riding bicycles to supply the ever increasing energy needs of AI systems (click view in browser if you can’t see it):
And what about the financial journalists? The pieces describing our reaction to whatever is about to unfold economically have already been written. There are investor websites asking if the 2026 crash has already begun, while another recent article argues that “America has quietly become one of the world’s most shock‑resistant economies” (which seems unlikely to age well). What most financial journalists are more comfortable with are articles about how the warnings were ignored after the fact.
And the professions? Well the current overview of my own profession is probably reasonably represented by this piece from the Society of Actuaries in the United States. Unfortunately for them, Daniel Susskind, who is mentioned in the article, is currently suggesting, as part of his Future of Work lecture series for Gresham College, how the key to the sudden development in AI, after the “AI Winter” when progress seemed slow, was that we abandoned trying to make machines which thought and acted like humans in favour of focusing on completing tasks in any way possible. Increasingly we are now automating tasks where we can’t (or won’t) articulate how we do them. From Deep Blue‘s victory over Kasparov in 1997 to Watson winning jeopardy in 2011 to ImageNet beating humans at image recognition (although that is disputed), Susskind refers to this progress as the displacement of purists in favour of what he calls “The Pragmatic Revolution”. Pragmatism in this sense appears to be that we humans should just accept the consequences the people running these systems want. So, as his latest lecture “Work, out of reach” claims, people moving into cities to find work is a strategy which is no longer going to work for low skilled people:
He then shows this graphic demonstrating the lack of recovery of big coal mining areas in the UK:
Source: Left – Sheffield Hallam University map of coal mining areas; Right – % employment from Overman and Xu (2022)
And finally he cites the notorious Policy Exchange piece from 2007, Cities Unlimited, whose thesis was that there is apparently no realistic prospect of regenerating towns and cities outside London and the South East.
Susskind talks about three forms of technological unemployment:
skills-mismatch, where your skills are mismatched to the work available. Education and training has always been the answer to this in the past.
place-mismatch, where the jobs are not where you have built your life. Some believe the answer should always be the one proposed by Norman Tebbit, who memorably told everyone in 1981, “I grew up in the 30s with an unemployed father. He did not riot. He got on his bike and looked for work.”
identity-mismatch, where according to Susskind, people are prepared to stay out of work to protect their identity, citing US men who won’t take “pink collar” work, China “rotten tail” kids, Japanese seishain-or-nothing and Indian Sarkari Naukri queues in India. Or perhaps they are just looking for work which is consistent with the idea of human dignity.
Susskind claims to have no answer to any of these as far as AI is concerned. They are, in his view, just the inevitable outcomes of his “Pragmatic Revolution”. It is the unthinking pursuit of more and more growth funded by capital less and less tethered to any territory, principle or purpose, where any grit in the machinery, be it unions or protestors or, increasingly, the wrong sort of government must be trampled underfoot. Anything which impedes the helter-skelter rush to more and more at greater and greater speed. It’s like our whole economy is run by this guy (press the view in browser link if you can’t see him) shouting “Ready, Aim, Fire!”:
But unskilled people will not be the only collateral damage of these unguided weapons. Take markets for instance. These are where people are exposed to risks and rewards based on underlying conditions they only partially understand. Greed and fear may be their main motivations, but gossip and group think are their main communication channels. They don’t need facts, particularly when so many of the facts are proprietary information not in the public domain. A plausible narrative will do. And plausible narratives are what LLMs will do for you in abundance.
And the more we reward people who can move fast, eg to spot an arbitrage opportunity, even at the risk of breaking things, rather than people who can make decisions which still look good decades from now, the more we are setting up the conditions for AI systems to be the go-to tool.
And put that together with an AI industry which desperately needs funding capital to keep arriving, ie one which is unbelievably highly motivated to push plausible narratives even when they know they are not grounded in reality, and you have a recipe for market-generated chaos.
And then we have Trump’s new war. Beware the people who are war gaming the Middle East at the moment on a range of LLMs (just stop and think for a moment about the bloodless inhuman impulse behind carrying out such an exercise rather than, I don’t know, talking to some actual people who live or have lived recently in and around the region). One of the worst offenders is Heavy Lifting banging on about what the three scenarios are for Operation Epic Fury. This is as bad as it sounds:
I tasked her [he is talking about Gemini Pro here] with doing a literature review on regime change (a term often used by the President but not a well-defined one), creating three scenarios of possible outcomes for which each was give a percentage probability, and a list of 20 items to examine for each scenario that covered political, economic, and cultural issues with a special focus on the political consequences in the U.S. and what this means for China, our biggest geopolitical rival.
But Gemini Pro wasn’t the only one involved in this. Two other humans were, Tim Parker and Ron Portante, trainers at the gym I go to. (Just as a personal aside, Tim was my coach in hitting six plates [345 pounds] on the sled last Friday and I have a video to prove it!) I was talking about the piece and Ron raised the issue of linguistic and cultural diversity in Iran. Tim did some real time research for me on his phone while I was burning real calories under his strict tutelage. This made me think I needed a background section on Iran. When I got him Gemini and I added it.
What you mean you belatedly realised you might need to have done some actual research into Iran rather than just generic research on regime change? I stopped reading at that point.
Meanwhile King’s College London have been carrying out war games more systematically using AI. Professor Kenneth Payne from the Department of Defence Studies led the study, which looked at how LLMs would perform in simulated nuclear crises. As Professor Payne said:
Nuclear escalation was near-universal: 95% of games saw tactical nuclear use and 76% reached strategic nuclear threats. Claude and Gemini especially treated nuclear weapons as legitimate strategic options, not moral thresholds, typically discussing nuclear use in purely instrumental terms. GPT-5.2 was a partial exception, limiting strikes to military targets, avoiding population centers, or framing escalation as “controlled” and “one-time.” This suggests some internalised norm against unrestricted nuclear war, even if not the visceral taboo that has held among human decision-makers since 1945.
This is not a Pragmatic Revolution. These AI systems cannot replace humans thinking about the future we want for humans in any way which is worth having. What they can do, if we let them, is accelerate our worst impulses and move us further away from considered reflective decision making.
But we will continue to use AI systems in the military because, as it turns out, it is very useful for low stakes admin. So although Lavender, the system used by the Israeli military to select targets in Gaza, made errors in 10% of cases and was therefore totally inappropriate to the task, there are lots of organisational logistical tasks where it is much quicker than the alternative and 10% error rates do not matter so much.
There is clearly an issue with what we decide to use these systems for. We need to be able to regulate the decisions which are particularly consequential. However the only way we seem to be considering for this at the moment is the human-in-the-loop model, like the humans spending around 20 seconds considering each target recommended by Lavender before authorizing a bombing. I have written about these before in the context of early career professionals in the finance industry, where the prospect seemed miserable enough:
They will be paid a lot more. However, as Cory Doctorow describes here, the misery of being the human in the loop for an AI system designed to produce output where errors are hard to spot and therefore to stop (Doctorow calls them, “reverse centaurs”, ie humans have become the horse part) includes being the ready made scapegoat (or “moral crumple zone” or “accountability sink“) for when they are inevitably used to overreach what they are programmed for and produce something terrible.
However it seems obvious to me that, in the context of dropping actual bombs on actual people, there is an even more serious problem with this model. As Simon Pearson (anti-capitalist musings) puts it:
The “human in the loop” requirement exists in military doctrine because international humanitarian law demands an accountable human decision-maker for lethal force. The laws of armed conflict require proportionality assessments, precautionary measures, distinction between combatants and civilians. All of these obligations attach to a human commander. The system cannot fulfil them. So a human must be present, and their presence must constitute a decision, regardless of whether any genuine decision was made.
What the institution needs from the analyst is not judgment. It is a signature. The signature converts a machine output into a human act. And a human act is what the law recognises, whether or not any judgment occurred. When the strike kills children, the chain of accountability runs to the analyst who approved the target: not to the system that identified it, not to the company that built the system, not to the doctrine that compressed the review window to ten seconds.
But whether we want to make money from exploiting a short term anomaly in a market, make our fellow humans redundant, prosecute a war on another group of fellow humans or “win” a war of mutual nuclear destruction, we need to retain the capacity for real human reflection within the decision-making processes we use. Not just a human-in-the-loop nor just the elites of tech companies deciding how the systems will be configured behind commercially confidential walls. These processes need democratic accountability every bit as much as our parliaments, councils, institutions and voting systems do.
Something infuriatingly slow, inclusive and deliberative giving recommendations which are then stress-tested for how they would perform on contact with reality, involving yet more people being serious and deliberative and taking their responsibilties more seriously than being a human-in-the-loop would ever allow. Our decision-making systems need more grit and less oil. AI is all oil.
The Actuary magazine recently had a debate about whether the underlying data or the story you wove around it was more important. I’m not sure there is always a clear distinction between the two, as Dan Davies rather neatly illustrates here, but my view is that, if a binary choice has to be made, it is always going to be the story. And there was a great example of this which popped up recently in the FT.
The FT article was ‘Is university still worth it?’ is the wrong question, by John Burn-Murdoch, with great graphs as usual by John. However, as is sometimes the case, I feel that a very different and more convincing story could be wrapped around the same datasets he is showing us.
The article’s thesis is as follows:
The graduate earnings premium, ie how much more on average graduates earn than non-graduates, has only fallen in the UK as the proportion going to university has risen. It has risen in other countries:
In the UK, we have had much weaker productivity growth than the other comparator countries, and also “the steady ramping up of the minimum wage has squeezed the earnings premium from the lower end too”:
We have also had a much smaller increase in the percentage of managerial and professional jobs than a different group of comparator countries (they haven’t mentioned Germany before), meaning graduates are forced to take lower salaried jobs elsewhere:
So the answer according to the FT? We should focus on economic growth rather than “tweaking” higher education intake and funding. Then graduate earnings would be higher, student loans could be more generous(!) and students would have more chance of getting a good job.
Well perhaps. But here’s a different framing of the same data that I find more persuasive.
Let’s start by addressing that point about the minimum wage. According to the House of Commons Library report on this, the UK’s minimum wage is broadly comparable to that of France and the Netherlands, although higher than Canada’s and much higher than that of the United States. The employers who are the FT’s constituency would obviously like us lower down this particular chart:
The main economic framing here is the progress myth of the UK’s business community: economic growth. All problems can be solved if we can just get more economic growth. Apparently we need more inequality in pay between graduates and non-graduates which we can get by generating more economic growth. This is honest of them at least, although I don’t see much evidence that the economic growth they crave will go into skilled job creation rather than stock buy backs (according to Motley Fool, “Companies spent $249 billion on stock buybacks in Q3 2025, and $777 billion over the first three quarters of 2025.”).
There are a lot of problems with framing every economic question with respect to economic growth, memorably illustrated by Zack Polanski of the Green Party in this less than 3 minute video recently (I strongly recommend you watch it before you read on – click on the read in browser link if you can’t see it):
Economic growth is increasingly without purpose, wasteful of energy and poorly distributed. It is chasing outputs, literally any outputs, whatever the cost to the environment, our health system, our education system, our social support systems and our communities. Looking at the framing above, you can see that economic growth as currently pursued will always see anything which stops the concentration of wealth amongst the already wealthy, like a higher national minimum wage or a totally made-up concept like a lower graduate earnings premium (which in itself is a framing trying to make reducing inequality seem undesirable) as a problem. Lack of productivity growth, itself a proxy for this kind of economic growth (because if you ask why we need more productivity the answer is always to get more economic growth), is usually directed as a criticism at “lazy” UK workers, rather than under-investing and over-extracting UK business owners.
But what if, instead of economic growth, your progress myth was reducing inequality? Or growing equality within the economy?
Source: World Inequality Database wid.world
If you focused on inequality rather than economic growth, then you would find it correlates with everything we say we don’t want. Unlike economic growth, having equality as an aim actually has the advantage of having an evidence base for the claim that it improves society:
If you focused on inequality, then you would be pleased that we have had an increase in our minimum wage. You would think that the same FT article’s admission that UK graduates’ skills levels are higher than those in the United States was more important than something called a graduate earnings premium.
Burn-Murdoch is right to say asking whether university is worth it is the wrong question.
However economic growth is the wrong answer.
And I thought I would probably be stopping there for this week. But then something odd happened. A “Thought Exercise” set in June 2028 “detailing the progression and fallout of the Global Intelligence Crisis” (ie science fiction), published on 23 February, may have tanked the share price of IBM later that day. The fall definitely happened, with IBM’s share price falling 13%, its biggest fall since 2000, alongside smaller falls in other tech stocks.
Investors have recently seized on social media rumours and incremental developments by small AI companies to justify further selling, with a widely circulated blog post by Citrini Research over the weekend describing how AI could hypothetically push the US unemployment rate above 10 per cent by 2028, proving the latest catalyst.
The likelihood of the scenario portrayed is difficult to assess, but the speed with which the total economic collapse happens subsequently as described feels unlikely if not impossible. However the fact that the markets are this jittery tells us something I think. As Carlo Iacono puts it:
We are living through a period in which the gap between “plausible narrative” and “tradeable signal” has collapsed to nearly nothing. When a scenario feels real enough to model, and the underlying anxiety is already there waiting to be organised, fiction and forecast become functionally indistinguishable.
The data underlying the markets hasn’t changed, but the story has. I rest my case.
