The inequality of redundancy

05. August 2026 · Write a comment · Categories: Actuarial, Birmingham, COVID-19, Economics, Health, Pensions, Science Fiction

In October 2009, while working as a pensions actuary in Birmingham, I attended the Institute and Faculty of Actuaries’ Joining Forces in Mortality and Longevity multidisciplinary conference at the Royal College of Physicians in Edinburgh. The canapés were excellent and, of the plenary speakers, I particularly remember Rudi Westendorp from Leiden University who, in response to the question of whether it was nature or nurture that was responsible for longevity, said it was both.

It was also the first and last time I have used a sleeper train. I had a trustee meeting on the Friday morning south of London and decided that it would be a good idea to get the sleeper from Edinburgh to London on the Thursday night. I hadn’t really researched it in advance and I suppose I was expecting a cabin to myself, but it turned out I was in fact sharing with a German guy who looked like he rode the overnight trains of Europe all the time. There was a set of bunk beds which took up most of the cabin and my memories of that night were of my being thrown around every time the train took a bend down the East Coast mainline, not sleeping a wink while my room-mate snored soundly throughout and then of his taking an annoying amount of time to brush his teeth in the morning. The trustees did not get me at my best.

But I digress. The session from the conference which has stayed with me ever since was by Eugene Milne from Newcastle University. As the blurb for his session A new model of mortality and survival stated:

A new mathematical model mimics patterns of mortality in species from nematodes to humans. Net risk, it suggests, arises from two components, an interactive element accounting for historical falls in human mortality, and redundant decay which shapes lifelong risk. This suggests “intrinsic ageing” is unrelated to the slope of the mortality curve, and is unlikely to have altered for humans in recent centuries.

Eugene Milne went on to become Director of Public Health for Newcastle and took them through the pandemic. The full paper in the British Actuarial Journal from 2009 is here.

At a time where actuarial mortality modelling consisted either of projecting observed trends into the future (with no real explanatory power for observed features like cohort effects) or attempted to project a range of causes of mortality based on the likely progress in treating them (which is limited by the quality of information on death certificates), Milne’s model stood out for starting from a biological model of gradually diminishing redundancy within the body. He recognised its limitations, as he said at the time:

As a bridge between actuarial and biological approaches to ageing it falls, as yet, between two stools. The examples in this paper are generated by probabilistic computer modelling. This is clearly not adequate for
actuarial use and the model needs to be developed further to provide a form that will serve that purpose. On the other hand, it describes (as noted in section 4) a biology that would be ‘needed’ in order to construct organismal risk as it is observed. This it does well, providing a coherent account of why mortality patterns appear as they do. Yet its theoretical ‘biology’ is at odds with currently favoured theories of ageing. If the biological quantity described in the NBM [nested binomial model] as redundancy exists, we do not yet know what it is, nor why it should appear to act in so sequestered and consistent a fashion.

But the idea stayed with me, and perhaps that made me particularly receptive to Richard Murphy’s recent article about allostatis, which he describes as “the way living organisms survive by continually adapting to the changing world around them”. As Murphy points out:

If something breaks, a wealthy person can simply have it repaired or replaced. If travel arrangements fail, alternatives can be found. If income is interrupted, there are savings to draw upon. Problems remain, because they always will, but they rarely threaten the stability of everyday life for a wealthy person. In other words, the amount of adaptation required of them is reduced.

There have been a number of attempts over the years to draw attention to how your level of income affects your ability to adapt to your environment.

In George Orwell’s Down and Out in Paris and London, he describes the effect of poverty:

For, when you are approaching poverty, you make one discovery which outweighs some of the others. You discover boredom and mean complications and the beginnings of hunger, but you also discover the great redeeming feature of poverty: the fact that it annihilates the future.

However Orwell has been criticised, as the temporary tramp that he was, for deciding that meant the end of anxiety. More recently, Jack Monroe used Terry Pratchett’s example of Captain Vimes’ boots, to illustrate how what life costs depended on how much you already had:

A really good pair of leather boots, the sort that would last years and years, cost fifty dollars. This was beyond his pocket and the most he could hope for was an affordable pair of boots costing ten dollars, which might with luck last a year or so before he would need to resort to makeshift cardboard insoles so as to prolong the moment of shelling out another ten dollars.

Therefore over a period of ten years, he might have paid out a hundred dollars on boots, twice as much as the man who could afford fifty dollars up front ten years before. And he would still have wet feet.

Jack developed the Vimes Boots Index to highlight inflation in basic food products, which then persuaded the ONS to launch a shopping prices comparison tool.

But to return to the idea of redundancy: it is clear that if you have, say, redundant money which can be brought in to play when things go wrong, then things generally go much better for you. But imagine if you have used up any redundancy quite some time ago and therefore any reverse is a potential crisis. Your stress levels will be much higher all of the time, as your body tenses for the battles it knows lie ahead about anything from a car that won’t start to a boiler that packs up to a hike in the price of bus fares or the basic food products on the Vimes Boots Index. Day in, day out.

At the moment one of the differentials in redundancy is around heat stress. Housing which cannot be cooled without electricity which cannot be afforded. Day in, day out, for much of the summer so far. But in winter the same housing will need far more heating because its occupants cannot afford capital investment like insulation.

And the reason for this enormous inequality in the level of redundancy, is of course wealth and income inequality. The Equality Trust sets out the statistics as follows:

The UK has very high inequality of income compared to other developed countries; the 9th most unequal incomes of 38 OECD countries (OECD, 2022).

The UK’s wealth inequality is much more severe than income inequality, with the top fifth taking 36% of the country’s income and 63% of the country’s wealth, while the bottom fifth have only 8% of the income and only 0.5% of the wealth according to the Office for National Statistics.

And this stress, day in, day out, means that people also die earlier, as shown below in the House of Commons Library research briefing on Inequalities in life expectancy, using ONS figures (and honestly they’re not picking on Blackpool):

And yet the most likely way for you to hear the word redundancy is when some company is planning to get rid of some of its workforce.

The trouble with people is that you don’t need them until you do, as Jonn Elledge has written here:

There are substantial differences between the US military and the NHS: but what both have in common is that, when they need something, they really do need it. The entire notion of “efficiency” is misplaced.

Similarly, in Nate Hagens’ latest interview, with biologist and biophysicist Olivier Hamant, they explore:

…how cheap, abundant energy allowed human societies to substitute the “safety net” of resource abundance for the safety net that living systems actually rely on: diversity, redundancy, and cooperation.

Until the resources stopped being so abundant.

And then there is the kind of workplace sustained redundancy programmes create, as Seth Godin says in a recent blog post:

“How few people can we get away with?” That’s a question many bosses think hard about. Automate. Streamline. Improve productivity and take humans out of as many tasks as possible. It’s a time-tested way to create profits and to increase a certain kind of reliability. Claude Code is popular with many organizations for precisely this reason.

“How can we include more people into this process?” is a less popular but often more valid way to create value. In an organization that is in the business of bringing insights, humanity and care to problems, more involvement from people creates better outcomes. The challenges make it far more valuable.

Which sort of organization would you like to work for?

And what sort of society do we want to have? One that supports the people in the bottom quintile with no redundant capital, so that they might have the resources available to maintain the stability of everyday life and reduce the adaptation required of them? Or one which keeps demanding more and more from those it allocates less and less of national wealth to. To quote from another Orwell book, Nineteen Eighty-Four, from the mouth of O’Brien, Big Brother’s Grand Inquisitor:

If you want a picture of the future, imagine a boot stamping on a human face—for ever.

I think we can all come up with better pictures of the future than that one.

Nutted by Newton

03. July 2026 · Write a comment · Categories: Actuarial, AI, Economics, Education, Professions, Risk

Isaac Newton may or may not have been nutted by an apple. His friend William Stukeley, whose memoir of Newton was the source of the story, states it as follows (spelling and punctuation from Stukeley’s manuscript at the Royal Society):

“why should that apple always descend perpendicularly to the ground,” thought he to him self: occasion’d by the fall of an apple, as he sat in a comtemplative mood: “why should it not go sideways, or upwards? but constantly to the earths centre? assuredly, the reason is, that the earth draws it. there must be a drawing power in matter. & the sum of the drawing power in the matter of the earth must be in the earths center, not in any side of the earth. therefore dos this apple fall perpendicularly, or toward the center. if matter thus draws matter; it must be in proportion of its quantity. therefore the apple draws the earth, as well as the earth draws the apple.”

However there may be stronger grounds for believing that Newton nutted English mathematics and, as a result, the actuarial profession.

I thought all this to myself, occasion’d by participation in the Actuarial Teachers and Researchers Conference (ATRC) this week. It was great. There were lots of interesting talks, and people were very engaged and respectful in how they discussed them. There was a lot of expertise in the room about both education and actuarial practice and theory. It felt like it was a room that could take on difficult topics and make progress in tackling them.

There were several calls for the need to change assessment, one of them by me, whether due to large student cohorts and the difficulties of engaging them, or the ease with which AI can duplicate examination solutions or because the credentials provided by those assessments seem increasingly irrelevant to the actual actionable skills, knowledge and experience required to operate successfully as an actuary. And there was an equally robust response from the Institute and Faculty of Actuaries (IFoA) to the effect that assessments would not be changing significantly in the latest changes due to come in by 2029.

My favourite presentation was by Angus Macdonald, about his recent short paper on Newton, Leibniz and Actuarial Science. It conjectures that the argument between Leibniz and Newton over who invented calculus resulted in the stagnation of mathematics in English universities and meant that actuaries needing to gain respectability for their advice were forced to create a professional body (in company with architects, accountants and engineers) rather than rely on universities to develop actuarial thinking as happened in continental Europe. This stagnation (Macdonald quoted G.H.Hardy, talking about the Cambridge mathematics exams, saying that they had “. . . effectively ruined serious mathematics in England for a hundred years”) was felt across the whole Anglosphere, with attempts to create institutions with equal status to the traditional universities leading to the establishment of business schools in the USA in the late 19th and early 20th centuries.

This explained a lot for me. The suspicion of our actuarial courses amongst some of our mathematics colleagues at times at Leicester. The occasionally uneasy relationship between the IFoA and the accredited universities where students can gain exemptions from their exams. The horror from some at the very idea that an actuary might qualify as a result of university courses, like they can in the Netherlands, for instance. ATRC seemed the appropriate place to explore these ideas.

Angus Macdonald considers that the Newtonian and Leibnizian branches have nearly rejoined, but I feel that our actuarial education system still suffers from the long shadow cast by these two 17th century gentlemen and their personal enmity. The ferocity with which some within the profession opposed what they saw as a threat to the popularity of the fellowship qualification posed by the new chartered actuary designation was hard to explain when the number of practising certificates issued for chief actuaries, pension scheme actuaries, etc was only around 1,100 (out of over 17,000 fellows), but if the whole profession originated from a highly developed form of status anxiety compared to academics, it becomes much easier to understand. As they say, the apple doesn’t fall far from the tree.

Now, nearly 180 years on from this “unstoppable” “rush to respectabilize” (according to Jeremy Paxman) I think it is legitimate to ask:

  1. Why does the IFoA still insist on detailed accreditation of individual university courses on basic mathematics, statistics and business economics? Do they not trust them to teach them right? Do they think that there is something better about learning these universal subjects via a bespoke course created by a tiny professional body with 34,000 members globally?
  2. Why are they so concerned about what assessment methods the universities use? Do they consider that they have more educational expertise on this than some of the leading universities in the world?

I have written previously about the changes in assessment I think are necessary and floated some ideas about where actuarial education might sit to accommodate these. My view was that the IFoA, faced with the need to innovate at all levels of its education system at a time of great uncertainty, might wish to get out of the foundational mathematics and business education tuition of the core principles subjects and leave this to the university system, in a truly Leibnizian way.

However there is a problem. The university system is facing a tough time. UK higher education is shrinking according to the UCU branch at Queen Mary’s, which has set up a a live page of all the redundancies, restructures, reorganisations, and closures taking place across the UK Higher Education (UKHE) sector. The numbers from the Higher Education Statistics Agency (HESA) bear this out, with overall student numbers falling, driven by a 10% fall in overseas entrants with a non-European Union permanent address.

In actuarial science, the list of UK universities offering accredited courses has not changed for some time, and it is a small group within the university system. These courses must be seen as vulnerable. I don’t think it is a coincidence that it is so hard to persuade one of this tiny band to run the ATRC. This week’s was the first since 2021 and the list of past hosts is not very long:

Source: https://atrc.le.ac.uk/

The IFoA needs to ask itself what it would do if there were some high profile closures of actuarial courses and whether perhaps it might be time to protect the core mathematical education arrangements for actuaries through a broad brush accreditation of a wider range of courses, rather than the very detailed accreditation process it currently carries out on core principles subjects.

I also doubt that it has the capacity on its own to significantly restructure its assessments beyond the objective based assessments it has developed to work within its proctored environment.

The core practice and specialist subjects leading to fellowship are the areas where actuaries have, rightly, the strongest views about content and assessment structures. It surely makes sense that the expertise within the profession and the university system are pooled in a joint endeavour rather than risking both failing independently.

In contrast to Newton, who had quite a temper, Leibniz was famously parodied by Voltaire in his Dr Pangloss character in Candide who believed that “All is for the best in this best of all possible worlds.”

Let’s not be too Panglossian about the current state of actuarial education.

How Not To Be A Reverse-Centaur – Part 2

16. June 2026 · Write a comment · Categories: Actuarial, AI, Cartoons, Economics, Education, Professions, Risk, Science Fiction
A no entry sign over an image of a reverse-centaur where the robot is in control

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:

  1. 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.
  2. These marks would be based on marking criteria they would never see.
  3. 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.
  4. 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).

Source: https://hitchhikers.fandom.com/wiki/42

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.

They will also have developed the four capabilities set out in Carlo Iacono’s Teach Judgement, Not Prompts:

  1. 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.
  2. 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.
  3. 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.
  4. 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.

The AI Rollercoaster

11. June 2026 · Write a comment · Categories: Actuarial, AI, COVID-19, Education, Professions
Source: https://xkcd.com/249/ This work is licensed under a Creative Commons Attribution-NonCommercial 2.5 License

It all started for me in May 2017, with the challenge from Daniel and Richard Susskind in their book “The Future of the Professions”, which set out two possible futures for the professions. Either:

  • They carry on much as they have since the mid 19th century, but with the use of technology to streamline and optimise the way they work; or
  • Increasingly capable machines will displace the work of current professionals.

Their research suggested that, while these two futures would exist in parallel for some time, in the long run the second future would dominate. The actuarial profession was going to be particularly vulnerable. As the Susskinds wrote:

Accountants and consultants, for example, are particularly effective at encroaching on the business of lawyers and actuaries.

I stood in the Institute and Faculty of Actuaries Council elections that month, on a platform saying that we needed to urgently respond to this challenge. I didn’t get elected.

However, at the University of Leicester we pursued a curriculum transformation programme in response to this challenge aimed at developing actuaries of the future who had:

  • Highly developed presentation skills, both in writing and in speech
  • Great team working skills
  • Strong IT skills – comfortable with working with data
  • Clarity about why they are there and the desire to use their skills to solve problems

The 2017 post also talked about emerging trends which had hardly started at all yet:

  • The end of reserved roles for actuaries
  • Different ways of communicating advice
  • Online self-help for users of actuarial advice
  • The advance of roboactuaries and their assistants

A paper called 2036: An actuarial odyssey with AI written for the Society of Actuaries in July 2016 by Dodzi Attimu and Bryon Robidoux discussed the possibilities for robo actuaries and robo actuarial analysts.

They estimated that robo actuarial analysts would be with us in 5-10 years and would provide:

A system that has limited cognitive abilities but can undertake specialized activities, e.g. perform the heavy lifting in model building (once the specification/configuration is created), perform portfolio optimization, generate reports including narratives (e.g. memos) based on data analysis, etc.

Whereas a robo actuary was more like 15-20 years away and which they also helpfully described:

We mean a software system that can more or less autonomously perform the following activities: develop products, set assumptions, build models based on product and general risk specifications, develop and recommend investment and hedging strategies, generate memos to senior management, etc.

Then, in 2018, there was the whole Bullshit Jobs argument posed by the late David Graeber, discussing Keynes’ prediction in 1930 that:

In quite a few years – in our own lifetimes I mean – we may be able to perform all the operations of agriculture, mining, and manufacture with a quarter of the human effort to which we have been accustomed.

Graeber, in Bullshit Jobs, pointed out that this never happened, despite pretty much all of the technological developments and income increases which Keynes predicted. He suggested that the future which the Susskinds were predicting is already happening in terms of needing fewer people to fill the meaningful roles within organisations but that, rather than employing fewer people, we are either creating “bullshit” jobs which even the people doing them can see no point to or bullshitizing existing roles for which the meaningful need has passed. It was as if the organisations themselves have attempted to maintain the outward appearance of the same structures by disguising the hollowing out of so many of their functions with simulated business.

Why? One of the reasons he thought the situation had been allowed to develop was that noone believed that capitalism could produce such an outcome. Graeber gave the example of the creation of Obamacare, where Barack Obama “bucked the preferences of the electorate and insisted on maintaining a private, for-profit health insurance system in America” in order to protect jobs in health insurance.

Then we had the pandemic, and the painful return to work which found that people were not necessarily keen to return to populating those office empires, preferring to work remotely. Some of the attempts by the captains of industry to get them back were a little desperate.

Now nine or ten years on from the initial challenge, we are deluged in articles about how AI is impacting different areas of actuarial work, whether it is already replacing graduate roles and what actuarial students need to do to make themselves employable. And now the blinkers also seem to have come off about capitalism not producing the need for fewer jobs.

Ian Pay of the ICAEW’s quote from last year was just one example:

Historically, accountancy firms have typically had a pyramid structure – wide base, heavy graduate recruitment. Firms are now starting to talk about a ‘diamond model’ with a wide middle tier of management because, ultimately, AI is not sophisticated enough yet to make those judgment calls.

But hang on a moment. Now there is something called an “AI boomerang”. Sam Altman of Open AI and Dario Amodei of Anthropic have both been backtracking on their predictions of job lay offs due to AI. As the Gold and Geopolitics Substack puts it:

Two-thirds of the companies that ran AI-driven layoffs last year are now rehiring. One in three spent more on the rehiring than they saved on the original cuts. Robert Half calls them “AI boomerangs” – which is the name a consultant invents when there’s a market in unwinding what the last consultant sold you.

The last few years of AI-generated headlines (in both senses of the phrase) have been quite the rollercoaster.

I do not want to add to the deluge, as currently you would need a LLM summarising reports for you 24/7 just to keep up with it as it is.

And there are good reasons for not rushing to judgement on this. It is only six weeks ago that the Bank of England’s Head of Financial Stability warned that global stock markets are overvalued. As she said:

The thing that really keeps me awake at night is the likelihood of a number of risks crystallising at the same time – a major macroeconomic shock, confidence in private credit goes, AI and other risky valuations readjust – what happens in that environment and are we prepared for it?

Since then, the economics of the major AI players has only got more bonkers. In this environment, there is considerable uncertainty about what students should be learning to prepare them for the world they will need to rebuild from the rubble of the current one.

Daniel Susskind reckons a “no regret” strategy for education would focus on the basics, which he describes as literacy, numeracy and critical thinking, and the critical use of AI. Carlo Iacono talks about the work which will always be hard to automate as follows:

The work that depends on reading a room. The work that relies on institutional memory. The work where the important fact is not in the document. The work where the answer is political, ethical or relational as much as technical. The work where being right is not enough, because someone has to be accountable for the consequences.

But you have to get into the organisation first before you can develop much of this. I remain reasonably comfortable with our prescription from 2017 in terms of broadly what the curriculum should be trying to achieve. Curriculum changes take time and, tempting though it is to pile into syllabus changes aimed at incorporating the latest cutting edge technological developments, the likelihood is that you will be arriving at the wrong fire. As a social media post this week put it:

The danger is that, as Agentic AI in particular looks so much like the predictions of 2016, we declare it the new messiah and bet everything on this being the future. I certainly think that 2036 will look very different to now, but I am not convinced that we have the shape of it yet. This may just be another bullshit alternative, waiting for the next crisis to mutate into something else.

What we can say with certainty is that the future for early professionals is as uncertain as any of us can remember. And, in my view, the best way to support our young people starting their professional lives (or whatever is going to replace professional lives) is to make the value they add much clearer to anyone who might want to work with them in the future.

Future education systems are going to need to help their graduates demonstrate their value in ways they haven’t historically needed to. AI has not brought new problems, it has accelerated existing ones. And the gap between actual actionable skills, knowledge and experience and the credentials which are supposed to represent them is the key one I believe as far as those graduates are concerned.

Because currently the companies who might want to take them on have to guess what they can do to a large extent. What does a 1st mean? A 2.1? Do the differences matter to their employer? Should they interrogate the details of student courses? How would they incorporate that into a manageable recruitment process? Some people see a future of AI generated applications by the thousand per student doing battle with AI powered triage systems operated by potential employers.

This is already an issue in academia. The conclusions of one academic paper on submissions to one major academic journal were stark:

Submission volume has risen 42% since the late 2022 release of ChatGPT, while writing quality has declined. The rise in AI-generated writing accounts for nearly all of these trends.

On the other hand, researchers complain about the increasing use of AI peer review to try and cope with these increased volumes, and some have tried to game the LLMs they believe they are dealing with.

I think we can do better than this in actuarial teaching and learning.

And this will be the subject of my next post.

Answering a better question

05. June 2026 · Write a comment · Categories: Actuarial, AI, Economics, Education, Professions
Source: https://xkcd.com/1319 This work is licensed under a Creative Commons Attribution-NonCommercial 2.5 License

I didn’t understand statistics until I started taking actuarial exams that required me to master particular statistical techniques, decide which ones were appropriate to the problem I was looking at, apply them accordingly and be able to interpret what the results did and didn’t tell me. An A at GCE O level in maths, and A at GCE A level in both maths and further maths and a maths degree from Oxford did not give me those abilities.

I didn’t understand economics until I started putting together modules which could be taught on both BSc and MSc courses and then teaching them. My economics module on the way to qualifying as an actuary, based very heavily on Economics by Begg, Fischer and Dornbusch, did not give me that understanding.

There is a pattern here: the most impactful experiences we have are frequently at a bit of a distance from the credentials we present to the world. Your education is not a paragraph on your CV, it is your lived experience, sometimes assisted by, sometimes actively hindered by and often pursued completely independently of the educational institutions you have had a relationship with during your life.

Daniel Susskind has marched into this often fraught relationship between credentials and actual actionable skills, knowledge and experience in the last lecture of his Gresham College series on The Future of Work, called Education – And Its Limits. His analysis is a very clear expression of the problems that will be created if AI systems prove to be half as capable and long-lasting as people from OpenAI and Anthropic are telling us they will be.

Susskind argues that trying to future-proof students through education was a hopeless task and that working on the assumption of unresolvable uncertainty was the better way forward. He suggests a “no regret” strategy for education would focus on the basics, which he describes as literacy, numeracy and critical thinking, and the critical use of AI. Others in the audience suggested some other “basics”: communication skills for instance.

The other strand of Susskind’s basics was critical use of AI. And his challenge to the audience was whether we can teach AI without losing the basics in the process.

After a bit about the need to make continuing education in later life more accessible, he looked at his list from a previous lecture (which I briefly touched on here) of problems for a post AI future:

  1. Distribution (replacing wages);
  2. Contribution (how do you “pull your weight”);
  3. Power (domination by Big Tech on economics, politics, liberty, social justice and democracy); and
  4. Meaning (fulfilment in life).

And this is why I continue to watch Susskind’s output, because he is the unusual combination of an extremely orthodox economist (see his book Growth: A Reckoning for proof of this) and someone who has been wrestling with the challenges of more capable systems to our way of doing things for over 10 years. What Susskind gives you is a peek at how the actual economists advising our governments would deal with things if OpenAI and Anthropic are proved right. It is as if you had someone who both thought, as Ben Bernanke, Chair of the Federal Reserve, did in October 2007, that “the banking system is healthy” and also that the banking collapse was going to happen anyway.

Because what he reveals is that, if Anthropic are right, orthodox economists have really got no policy prescriptions worthy of the name.

On 1. Distribution: Susskind acknowledges that, if the labour market could not redistribute wealth effectively any more, then a bigger state would be needed to do so (but he was at pains to emphasise that this would not be the 20th century central planning type of state).

On 2. Contribution: Susskind thinks that perhaps we should allow people to make non-economic contributions! As if all of the activity in society which economists routinely ignore really wasn’t already happening!

On 3. Power: Susskind says the political power of Big Tech with regard to liberty, social justice and democracy is a problem. We have anti-trust legislation that can deal with Big Tech’s economic power, but not its political power. I don’t know what kind of political power he thinks Big Tech would have without the economic power that has been granted it by a steady erosion of that anti-trust legislation over recent years.

On 4. Meaning: he has little to say other than something about us currently having policies for work but not for leisure.

And in all of this, there is the implicit underlying assumption of a stable future environment for all of this tech to operate within.

For me it brought to mind something a friend of mine who was in a tent with Cory Doctorow at the How The Light Gets In festival at Hay-on-Wye last week. “He has a theory of change” he said.

He really does, including about how to break the economic power of the Big Tech companies. You all need to read Enshittification for the full account, but my review of the book here is a sneaky peek.

Susskind really really does not have a theory of change. Which tells me that the economics profession does not have one either.

However I continue to watch him as I find he goads me into thinking what some better answers might be to the questions he asks. And perhaps also a better question than whether we can teach AI without losing the basics in the process. I think a better question would be what do we need to learn when the future is uncertain.

First of all, let’s remind ourselves of the problem. If noone cares how your advice was constructed, but your client can get advice that ticks the compliance box more cheaply and quickly from an AI system, while the experienced professional still has some role in managing the process, it may increasingly be a struggle to justify the cost of the junior colleague. So the future education system is going to need to help that future junior colleague demonstrate their value in ways they haven’t historically needed to. AI has not brought new problems, it has accelerated existing ones. And the gap between actual actionable skills, knowledge and experience and the credentials which are supposed to represent them is currently the key one as far as that future junior colleague is concerned.

The temptation is to rush into syllabus changes towards what currently looks like the cutting edge activity. I agree with Susskind here that this would be a mistake. He cites the example of Michael Gove, amongst many other education ministers at the time, mandating the teaching of coding in 2014. Now we find that the new AI systems (despite the problems highlighted by Hannah Fry, Kyle Kingsbury and others I talked about here) are most suited to writing code and Anthropic claim that Claude is now writing 80% of its own code. Programmers are saying that, on the famous XKCD cartoon above, they are now living on the theory curve.

But both higher education institutions and the professions who still want to be in the game of developing the next generation of professionals can do a lot more both to reduce the gap between credentials and actual actionable skills, knowledge and experience and to make it clearer to employers that they have done so. That will be the subject of my next post.

The meatspace layer for actuaries

20. May 2026 · Write a comment · Categories: Actuarial, AI, Cartoons, Economics, Education, Media & Politics, Pensions, Professions, Regulation, Risk
A suited pinhead wearing a pirate's hat stands in the stern of a pirate ship below a dangling ladder
Source: Nick Foster – December 2013 – originally drawn to deride George Osborne’s austerity as Pugwash Economics, repurposed now as I am worried about the actuarial profession pulling up the ladder on the next generation

The “black box” was a constant refrain when I was working as an actuarial consultant. It was where the results from a process were being accepted without any understanding of how they were arrived at. Something we felt that any self-respecting actuarial consultant should challenge in their own work and everybody else’s.

However when you came to actually present analysis or arguments to a client, you expected a certain amount of that expertise to be taken as read, to effectively be inside a black box as far as the client was concerned. They couldn’t be expected to understand all of the aspects of what you were talking about, otherwise they wouldn’t need you. Good practice was always to put them in a position where they could understand and make decisions about the key aspects of your advice without needing to engage with the other parts. As the expert, you decided what was in the black box.

Now the black box is back with a vengeance for all the professionals who have relied upon them in their working lives. As Dan Davies puts it:

The same black-box property which stops you from being second guessed or overruled means that nobody is interested in your explanations for your decisions; it is definitional of being a black box that you are going to be judged by results.

And, if you are in the business of advising in the teeth of uncertainty, as actuaries are, then this is likely to be a real problem. If noone cares how your advice was constructed, but they can get advice that ticks the compliance box your client has to complete more cheaply and quickly than you can, the more automated black box is going to win the business. The experienced professional still has a role in managing this process, verifying the results coming out of the black box and determining what can still be kept out of the black box, but he may be increasingly struggling to justify the cost of his junior colleague.

I wrote about how devastating the fall in graduate job listings was 9 months ago, so where have we got to since?

Well things don’t look so bad in the UK right now according to the Office for National Statistics (ONS), reverting to close to the average after a post pandemic surge in the finance and insurance sector:

Source: https://www.ons.gov.uk/employmentandlabourmarket/peoplenotinwork/unemployment/datasets/vacanciesbyindustryvacs02

However, if we look at the United States, which tends to show us where the UK finance sector is going, it looks far more ominous:

Yesterday Sky News ran a story about Standard Chartered‘s CEO who, in his desperation not to describe over 7,500 job losses as cost cutting, said this:

It’s not cost-cutting. It’s replacing in some cases lower-value human capital ​with the financial capital and the investment capital we’re putting in.

We may need to sit with that statement for a little while.

Daniel Susskind talks about this risk in his latest lecture entitled A World Without Work: in summary, to paraphrase only slightly, sure relatively junior white collar roles may already be particularly hard hit by AI, but he is optimistic because of the impact on GDP and we cannot pause because of China. He then goes on to talk about the four problems he sees for a post AI future:

  1. Distribution (replacing wages);
  2. Contribution (how do you “pull your weight”);
  3. Power (domination by Big Tech on economics, politics, liberty, social justice and democracy); and
  4. Meaning (fulfilment in life).

Susskind has gone from thinking that the fear that AI is coming for your jobs was overblown and that it was just task encroachment that we faced, to now thinking that it may encroach on all the tasks in most fields. Jevons Paradox (that technological innovation that increases the efficiency of a resource’s use leads to a rise in consumption of that resource) is no comfort if that new demand is robot-met.

Carlo Iacono suggests that the move of junior roles to AI may be subtle to begin with:

The weakness among young workers may appear as fewer people entering employment from outside the workforce. Firms may not fire large numbers of juniors; they may simply hire fewer of them.

That matters. The labour market can look healthy while the entry path narrows. Senior workers stay employed. Output rises. Productivity improves. There is no dramatic wave of redundancies.

Yet the first rung is being taken out.

It may also be masked by the fact that there remains a shortage for actuaries beyond the entry roles. There is almost a hint of desperation to approaches like this looking for introductions from a retired actuary like myself:

(followed by a list of clients he is working for)

Source: recruitment consultant who will remain anonymous. I am assuming “candies” are candidates

And, even if you think the risk of the AI Bubble bursting soon, taking down the global stock markets underpinned by the Magnificent 7, is exaggerated, you do need to be suspicious about the current abilities of AI to replace junior staff. My experience with another, somewhat earlier, actuarial technology, the pensions valuation engine, would suggest that the outputs need to be analysed very carefully before sharing with a client: it often had dependencies between what should have been independent variables hidden in the programming, or vagaries in the setup which left out non-standard benefit rules for your particular scheme, for instance. Or the student who had set it up initially (a complicated process usually) might have made a mistake or you might have not communicated with them very well to start with. Or a hundred other things.

For whatever reason, there was often still a lot to do after the valuation engine had produced some output.

Can this sort of thing happen with agentic AI? Well think about that student programming the valuation engine, but on steroids. Its patchy capabilities combined with its basic psychopathy leads to, as Hannah Fry entertainingly demonstrates here, some serious problems arising with the agent’s relentless to and fro with the large language models it depends upon, asking them what it should do next. As Hannah says:

I built an AI agent. She opened a shop selling novelty mugs, emailed a journalist without being asked, and then leaked our passwords to a total stranger.

As Kyle Kingsbury wrote about having an AI agent as a colleague in a programming team:

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?

Yet despite all this, the money continues to pour in to the construction of AI infrastructure. There are already websites up and running for all of the parts of tasks AI cannot encroach upon.

Source: https://rentahuman.ai/

The bottom rung of the actuarial ladder is clearly in danger. This is a particular problem for the actuarial profession, which has traditionally relied on longer periods of work-based training for its future qualified actuaries than many other professions. Training to become an actuary takes a long time. Median time to fellowship is still around six years, with some taking up to ten or giving up. The exams are hard to pass. There have been attempts by the profession to tackle some of these disincentives: the Chartered Actuary designation to make a destination of the generalist qualification before the specialisation of the fellowship, championed on this blog and launched in the teeth of opposition by some fellows, being one example.

It has led to a culture within actuarial firms around managing the extended time in training, with rituals around study leave and results days. One of the fears expressed in opposition to the introduction of the Chartered Actuary designation was that, if this could be achieved almost entirely within formal education at universities, the value of working alongside experienced actuaries would be lost.

It has led to a culture within the profession itself of managing large parts of its education system in house. Half of its revenue and around 30% of its expenditure are on “pre-qualification learning and development”. Sometimes it looks more like an education business with a professional side hustle.

But then the new AI toys have come along, and it turns out that many of those experienced actuaries may be less keen on graduates coming in and needing supervision from them after all. Many of them may rather spend hours on AI prompts than on developing another human being.

I fear that, increasingly, companies are not going to accommodate actuarial students in their work plans without significant persuasion. And, if the number of students studying while in work falls, the profession itself is going to struggle to finance its own bespoke education system at an acceptable cost to its members.

It will be hard for the profession to challenge this too: it is going to be good for many of those already established in their roles as the market for more experienced actuaries, when the market has no interest in developing the actuaries of the future, becomes increasingly competitive.

If the actuarial profession does accept the challenge of protecting the pipeline of future experienced actuaries it will need to review its entire education syllabus through this lens. It will also need to engage with other partners involved in what is in effect a problem of capital formation and collective action: government incentives may be needed to encourage firms to continue to train early career professionals and discourage free-riding. There may be no way back for the student with no actuarial qualifications learning on the job. The universities may be needed to plug people in at a different career point, which will require them to innovate themselves even further into the professional training role than ever before. As Carlo Iacono points out:

educational institutions may be pushed to simulate more of the apprenticeship environment. That does not mean adding a thin “AI literacy” module. It means creating settings where students practise judgement under uncertainty, in realistic workflows, with feedback that is close enough to hurt and useful enough to teach.

It will not be at all easy. But the alternative is a future without opportunity for those who do not already have it and an ageing profession withering on the vine it refused to nurture.

The world according to the fig tree

06. May 2026 · Write a comment · Categories: Actuarial, Climate Change, Economics, Media & Politics
This fig tree is in the cemetery at Mission Santa Barbara. “Fig Tree” by HarshLight is licensed under CC BY 2.0.

I am reading a wonderful book at the moment: The Island of Missing Trees by Elif Shafak. It has allowed me to inhabit the Cyprus of the late 50s and mid 70s and understand a bit more about why my time on the island after my birth in 1962 was so short. It is also the first book I have read where a major character is a fig tree.

And it is the fig tree that makes the most acute observations about humans. My favourite one is this:

Even so, based on personal experience, I can tell you one thing about humans: they will react to the disappearance of a species the way they react to everything else – by putting themselves at the centre of the universe.

Humans care more about the fate of animals they consider cute – pandas, koalas, sea otters and dolphins, too, of which we have many in Cyprus, swimming and frolicking about our shores. There is a romantic idea as to how dolphins perish, washed to the beach with their beak-like snouts and innocent smiles, as if they have come to bid humankind one last farewell. In truth, only a small number do that. When dolphins die, they sink to the bottom of the sea, as heavy as childhood fears; that’s how they depart, away from prying eyes, down into the blue.

Bats are not deemed to be cute. In 1974, when they died in their thousands, I didn’t see many people shedding a tear for them. Humans are strange that way, full of contradictions. It’s as if they need to hate and exclude as much as they need to love and embrace. Their hearts close tightly, then open at full stretch, only to clench again, like an undecided fist.

Humans find mice and rats nasty, but hamsters and gerbils sweet. Doves signify world peace, whereas pigeons are nothing more than carriers of urban filth. They proclaim piglets charming, wild boars barely tolerable. Nutcrackers they admire, even as they avoid their noisy cousins, the crows. Dogs evoke in them a sense of fuzzy warmth, while wolves conjure up tales of horror. Butterflies they look on with favour, moths not at all. They have a soft spot for ladybirds, and yet if they were to see a soldier beetle, they would crush it on sight. Honeybees are favoured in stark contrast to wasps. Although horseshoe crabs are considered delightful, it’s a different story when it comes to their distant relatives, spiders…I have tried to find a logic in all this, but I have come to the conclusion that there is none.

This compulsion of humans to put themselves at the centre of the universe and dominate everything else is being written about by many writers at the moment, all of them giving it different names. Nate Hagens sees our species as part of an economic Superorganism:

This Superorganism is mindless, unplanning, and energy-hungry. It isn’t evil, it doesn’t feel, and it doesn’t care about equity, ecology, or human wellbeing. It solely optimizes for throughput, scale, and for more – even when more becomes the problem. There is no mastermind behind the wheel, only billions of incentives aligned in the same direction toward extraction and consumption.

Samuel Miller McDonald refers to it as “parasitic energy capture”. Pointing out that:

When the limits to their extraction of resources are exceeded, the parasitic systems must either suffer a crash or must invade and take the energy of a more distant ecology or society.

Luke Kemp refers to the consequent empires we have built as Goliaths, with diminishing returns on extraction ending fairly predictably:

The result is more extractive institutions creating growing instability, internal conflict, a drain of resources away from government, state capture by private elites, and worse decision-making. Society – especially the state – becomes more fragile. Private elites tend to take a larger share of extractive benefits. The state, and many of the power structures it helps prop up, then usually falls apart once a shock hits: for Rome it was climate change, disease, and rebelling Germanic mercenaries; for China it was often floods, droughts, disease and horseback raiders; for the west African kingdoms it was invaders and a loss of trade; for the Maya it was drought and a loss of trade; and for the Bronze Age it was drought, a disruption of trade and an earthquake storm.

And so it should come as no surprise that the latest Planetary Solvency report from the Institute and Faculty of Actuaries and Anglia Ruskin University – Planetary Solvency: Tipping into the wild unknown – catalogues a terrible toll on the Earth system which supports us, with biodiversity loss, climate shocks and geopolitical conflict disrupting the food system, risking catastrophic impacts for the financial system and for society as a whole.

A few examples from the report:

  1. The world lost 26.8 million hectares of natural forest in 2024 alone. This is larger than the entire UK, which spans 24.9 million hectares. This activity generated 10 gigatons of carbon emissions;
  2. In the UK alone, bees and other pollinating insects have on average lost a quarter of their habitat since 1980. Around 75% of the different crops used in global food production relies on pollinators to some extent, although by weight the dependence is around 35%. Loss of pollinators would reduce yields for most crops but would wipe out some altogether, eg brazil nuts, kiwi, melon and cocoa.
  3. Around the UK, warming seas have already begun shifting fish populations northward, with cod, haddock, and salmon being replaced by species like anchovy, bluefin tuna and squid (the real story behind the catfish sold in fish and chip shops headlines)…If global warming, ocean acidification, overfishing and pollution continue on their current trajectories, the economic and social consequences are likely to be severe. In the event of more extreme tipping points, such as the collapse of the Gulf Stream, the consequences could be even more catastrophic.
  4. Around 70% of emerging infectious diseases originate in animals, with land-use change, deforestation and wildlife trade increasing the risk of future pandemics.

So what can be done? The planetary solvency report defers to the UK Government’s Global biodiversity loss, ecosystem collapse and national security – a national security assessment at this point, which makes the following points:

  1. The UK does not have enough land to feed its population and rear livestock: a wholesale change in consumer diets would be required. It would also require greater investment in the agri-food sector so that it is capable of innovating in sustainable food production.
  2. Some technologies exist that could help, but need significant research, development and investment to have a chance of working at scale. Protecting and restoring ecosystems is easier, cheaper and more reliable. The time required to develop and scale technologies is unknown without further research. Both existing (plant pre-breeding, regenerative agriculture) and emerging technologies (AI, lab grown protein, insect protein) offer potential solutions.

The other writers mentioned above all look at the future slightly differently:

Hagens is pessimistic about our chances of stopping the Superorganism, but believes we can start planning now for what comes next. Miller McDonald hopes for the “opening up of possibility for alternative forms of organisation of human life”. Luke Kemp says that collapse has historically benefited the 99% at the expense of the elite 1%, although he does worry that our modern economy makes us more dependent upon global infrastructure and we have much scarier weapons than in the past.

But shocks in the short and medium term – of the climate, of the economy and of our politics – now have a feeling of inevitability about them. I wonder how the fig tree will feel about them.

Healthy life expectancy is unwell

28. April 2026 · Write a comment · Categories: Actuarial, COVID-19, Demographics, Health, Media & Politics, Pensions, Regulation
Source: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthandlifeexpectancies/datasets/healthstatelifeexpectancyallagesuk

Yesterday an extraordinary thing happened: the news story about the UK’s falling healthy life expectancy led the BBC News for a while, ahead of the King’s visit to the US in the wake of the assassination attempt on Trump’s team and the latest twists in the Mandelson affair. And so it should: over the decade 2012–14 to 2022–24, healthy life expectancy in the UK fell by about 2 years, to 60.7 years for males and 60.9 years for females.

And that is just the average. As we can see from what I felt was the most informative graphic from the Health Foundation’s report, some of the local authority areas have seen precipitous falls over the same period. Merthyr Tydfil has fallen from 57.6 years to 50.1 years. North Lanarkshire has fallen from 58.3 years to 52.3 years. And in England, Sandwell has fallen from 57.7 years to 51.3 years. In the 2012-14 data, only one region had no local authorities with a healthy life expectancy below the state pension age. By 2022-24, most regions have a healthy life expectancy below 66 years.

Healthy Life Expectancy (HLE) is defined as the number of remaining years that an individual can expect to live in “very good” or “good” general health. Rates of “very good” and “good” general health by sex and five-year age band are captured from the following survey general health question on the Annual Population Survey (APS) and in the Census 2011 and Census 2021:

How is your health in general; would you say it was…

  • Very good?
  • Good?
  • Fair?
  • Bad?
  • Very bad?

I last wrote about HLE in 2017 in response to John Cridland’s review of the State Pension Age. My view at that time, when healthy life expectancy was plateauing rather than falling like a stone, was that it was time to consider a universal basic income model. Then only the poorest decile was going to be condemned to 18 years of working in poor health until they could claim a state pension. Now the overall averages in some local authorities have moved down to join them, this consideration appears rather more urgent.

In 2014, I was concerned about what happens if the healthy life expectancy doesn’t increase in line with the planned increases to the State Pension Age and, towed along 10 years behind it, Normal Minimum Pension Age (NMPA). Well here we are: 26 of the little local authority blobs are at or below the current NMPA of 55. This nearly doubles to 49 local authorities (assuming the fall in HLE doesn’t continue, which feels like a heroic assumption at the moment) when the NMPA is due to rise to 57 in April 2028.

As the Health Foundation report says:

While healthy life expectancy has declined, life expectancy has remained broadly stable for the UK overall, indicating that the deterioration is not primarily driven by changes in mortality. However, in more deprived areas, life expectancy remains below pre-pandemic levels, suggesting mortality plays a greater role in reducing healthy life expectancy in these areas. Worsening self-reported health remains a key factor throughout the UK, highlighted by a falling proportion of life spent in good health and by wider evidence of declining health among the working-age population.

Other countries have not experienced this, illustrated by the UK sliding down the international comparison tables:

Source: https://www.who.int/data/gho/data/indicators/indicator-details/GHO/gho-ghe-hale-healthy-life-expectancy-at-birth

In the complete table the UK is sandwiched between Puerto Rico and China, with (from World Bank data) GDP per capita respectively of $39,344 and $13,303, compared to the UK’s GDP per capita of $53,246 (all from 2024).

Andrew Mooney, The Health Foundation’s principal data analyst, said: “The UK has the highest levels of obesity in western Europe and there has been a surge in mental ill health, especially among young people.”

Perhaps, instead of obsessing over GDP growth, we should be focusing on what countries like Iceland, Norway, Australia and New Zealand have been doing in recent years to tackle population health. I think it would make us all feel better.

Talking Terraforming in Birmingham

08. April 2026 · Write a comment · Categories: Actuarial, Birmingham, Climate Change, Media & Politics, Risk, Science Fiction
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:

https://www.eventbrite.co.uk/e/1985958692911

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!

Here we are again

19. March 2026 · Write a comment · Categories: Actuarial, COVID-19, Health, Media & Politics, Professions

I have caught Covid for the third time this week, so naturally my thoughts have turned to how it all began.

There are a few Covid posts starting to turn up online as the 6th anniversary of it all rumbles around. The British Foreign Policy Group have helpfully published a timeline from which I have taken everything that happened before Boris Johnson locked us down for the first time:

So a lot had happened by 23 March. You will all have your favourite bits from the saga above, I think mine is 22 January, when Public Health England announced they had moved the risk level to the general public from very low to low.

I remember teaching a macroeconomics class on 12 March when we knew it was going to be the last session on campus. The penny hadn’t dropped. Students were asking about how they would hand work in. We agreed it would have to be online. Some lecturers were talking about microwaving paper submissions to sterilise them. We had a little giggle about that. I had spoken to Stuart McDonald (now MBE) earlier that day where we had reluctantly agreed to postpone his visit to campus to speak to the Leicester Actuarial Science Society (LASS). Stuart would of course become one of the actuarial stars of the pandemic for his work with the COVID-19 Actuaries Response Group. I had a similar conversation by email with Lord Willetts, who was Chancellor at the University of Leicester at the time and who was going to talk to LASS about his books The Pinch and A University Education. We talked of postponing rather than cancelling. The realisation that everything was changing for the foreseeable future was still not there.

It took a long time for the penny to drop for the Government as well. As this analysis of the establishment of the “Covid Disinformation Ecosystem” says:

January featured fear and disbelief, February proved covid couldn’t simply be ignored, March was when governments realised the hospitalisation rate could overwhelm healthcare.

And a Government that was slow to respond initially was very vulnerable to the groups which sprung up during 2020 and 2021. As the Counter Disinformation Project says:

And the main initial target for the UK section of the ecosystem was Boris Johnson who was meeting privately with newspaper owners and editors. Enough doubt was put into Johnson’s mind that he dithered and delayed when cases began to rise, leading to a private meeting with Heneghan, Gupta and Sweden’s Anders Tegnell in September before he chose to ignore his scientific advisors’ calls for a circuit breaker lockdown. In the run up to the deadliest weeks of the pandemic the papers were calling for Johnson to “Save Christmas’.

However I don’t want to focus on our collective inability to make decisions during crises this time. This time I want to focus on the impact of the pandemic on our mental health.

By coincidence, today the 386 page Module 3 report from the Covid Inquiry on The impact of the Covid-19 pandemic on the healthcare systems of the United Kingdom was published. The longer this Inquiry goes on, the more it appears to resemble a truth and reconciliation commission rather than something likely to improve the handling of future pandemics. It gets past transgressions on the record, but in a way designed to move us on rather than improve our preparedness and organisation. I certainly saw nothing in the summaries that I didn’t already know. Module 3 has made 10 recommendations. The only one which mentions mental health at all is the last one on Psychological and emotional support for healthcare workers.

Looking through the module titles, it would seem that this is unlikely to be rectified until Module 10 – Impact on society – reports, currently scheduled for the first half of 2027. I find this relegation of our collective trauma to the lowest priority astonishing.

Two years ago, the Centre for Mental Health produced a review of the evidence so far on COVID-19 and the Nation’s Mental Health. They noted that:

Data on the prevalence of mental health difficulties is harder to assess. For children and young
people, surveys in England have provided a time series since 2020 that suggests very strongly that
mental ill health is indeed more prevalent now than it was before the start of the pandemic. A steady
rise in the decade prior to 2020 seems to have been followed by a sharp rise, and numbers have
stayed high ever since. We do not have the equivalent data for adults, meaning that a clear picture
has yet to emerge, but there is persuasive evidence that levels of mental ill health have been rising
over the last decade, and the pandemic has contributed to many of the risk factors people face.

Before concluding as follows:

Crucially, the pandemic exposed fault-lines in the nation’s mental health, and the stark inequalities
faced every day by people living with mental illness. The public’s mental health was deteriorating
in the years running up to the pandemic, and mental health services were struggling to deal with
the consequences of many years of underfunding and austerity measures across public services.
People with a mental illness were already dying 15-20 years sooner than the general population, and
facing widespread hardship. The pandemic exacerbated these inequalities, creating new risks to
people’s mental health and reducing access to support.

We now have the opportunity to learn from this experience and build a mentally healthier future.
We can act now to boost the public’s mental health in the aftermath of the pandemic, protecting
those who have experienced the worst effects and offering better support to groups that don’t yet
have access to the right support. And we can incorporate mental health into preparations for future
emergencies, so that responses are psychologically informed from day one.

They also made 10 recommendations, mostly for the NHS and Department for Health and Care, but also covering education, communications and considerations for the upcoming (at the time) review of the Mental Health Act. Less than half of these recommendations have been addressed at all.

Now we are two years on from that report, what has changed?

Well, Roy Lilley has drawn a rather dispiriting picture for us. He draws attention to Wes Streeting’s announcement in the Health Service Journal on 12 March, that the proportion of the NHS budget spent on mental healthcare would be cut for the third year in a row. Lilley lists how the demands on mental health services have mushroomed since before the pandemic:

  • Around two million people were in touch with mental health services in 2019, today it’s around three million;
  • Child and Adolescent Services: in 2019 around 500,000 referrals. Now around a million;
  • And only around 45% of referrals are accepted, meaning the true demand is even higher;
  • Talking therapies are up by 60%; and
  • Crisis team referrals and sectioning under the Mental Health Act are also up 60%.

And he summarises the problem like this:

The total economic cost of mental ill-health in England in 2022 was estimated ~£300bn a year when lost productivity, welfare and wider costs are factored in.

The total MH budget is about £16bn. Meaning, the NHS is spending roughly £1 trying to address a £18 national problem.

It feels like we are still waiting for the penny to drop.


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