Actuaries on the side of capital

16. October 2026 · Write a comment · Categories: Actuarial, AI, Cartoons, Climate Change, Economics, Education, Pensions, Professions, Risk

I think I may have been naive.

A couple of weeks ago I took the IFoA’s AI Manifesto to task for wanting to be on the Red Team rather than the Blue Team, ie the one supposed to be stopping as many AI errors as possible. As I said then:

The Red Team breaks into systems by exploiting a single vulnerability. That is comparatively easy. The Blue Team needs to reassure its clients that it has removed ALL vulnerabilities.

But what if you are not working to protect people from vulnerabilities? What if you are working to protect and accumulate capital instead?

Today I was alerted to the latest article from the IFoA GenAI Working Party, Agent Skills in the Enterprise: Making Actuarial Process Knowledge Reusable. It explains “how an agent skill package can connect reusable instructions with scripts, controlled references, templates, examples and tests”. This will allow organisations to “preserve not only completed models, reports and workpapers, but also the process checks, review decisions and handling of exceptions that produced them using the “agent skill” framework”. As the report puts it:

The problem is not simply that organisations need better prompts. They are preserving the outputs of professional work while leaving much of the procedure that produced them implicit. A completed report records what was concluded. It rarely records every data check, exception, escalation point and review decision needed to reach the conclusion reliably next time.

I can immediately see the motivation. I have been that person trying to replicate a previous valuation result produced by a former colleague I can’t contact, with incomplete data and a-no-longer-supported valuation system which keeps going on the blink. But it was the mention of process knowledge which caught my attention.

I wrote about process knowledge and its importance around a year ago, citing the example of the shrines at Ise Jingu in Japan (which I had learned about from Dan Wang’s Breakneck). This is a now over 1,300 year project to preserve the traditional techniques of building these shrines which involve no nails, just dowels and wood joints. Skills are passed from one generation to the next, there is a tree planting programme which has survived a dozen or more historical eras, pandemics, volcanic eruptions, earthquakes, invasions and oh so many wars over that period. As well as two nuclear bombs.

The important thing is not the ability to build a shrine over 1,300 years later exactly as it was built then of course. It is a proof of concept. It has preserved intricate difficult skills over more than a millenium. And it has involved people, lots and lots of people.

By contrast, the IFoA project has a different, rather shorter term, goal, which is laid out as follows:

This is the first of five articles. The second examines how completed work can become reusable packages. The third introduces SkillOps as the discipline for governing agent skill packages in actuarial work. The fourth considers the consequences for consulting when expertise previously carried through human capital is codified in reusable agent skill packages and becomes intellectual property. The fifth places skills within the wider challenge of continual learning.

It is the fourth article which really bothers me. Once not just the details of a project, but all of the other parts which do not normally get passed on (ie the process knowledge) are captured in this system, it becomes intellectual property, which Cory Doctorow defines as:

any rule, law or policy that allows a company to exert control over its critics, competitors or customers

Up until now, process knowledge has not been given much attention, mainly because it can’t be turned into intellectual property. Process knowledge has always been what remains in the heads of the skilled technicians employed by businesses after everything not nailed down which can be taken ownership of by those businesses has been. Process knowledge has always been the nailed down part. It is the part that has allowed the last vestiges of worker power within most corporations to survive.

Now a group of actuaries think they have come up with a plan to monetize that for the firm as well. To pull up those last remaining nails of worker power.

Think how the IFoA GenAI Working Party would have approached the Ise Jingu shrines.

First you outsource the tree planting programme to a specialist forestry manager. Minimum tender of course: need to get maximum value for money here. Don’t worry about having control over the delivery of timber of just the right type in just the right condition for a unique project. Just leave that to the specialists working on a budget.

Then you sit with the old guys taking you through the various processes involved. Might need some video capture for some of it. Make sure everything they say is captured and then cross-referenced for easier access subsequently. Don’t take too long over it as time is money. Don’t actually feel what it’s like to work with the tools, just note down everything about tool selection. Don’t actually apply the required pressure in the right direction with respect to the grain of the wood, its dryness, the precise cut from the trees selected. Just make sure the video is high enough quality.

I would be surprised if this project survived 20 years. In fact, in view of the fantasy economics of the AI industry, I would be surprised if it lasted even five years if the AI Agents involved in this project relied to any degree on the survival of any of the Magnificent 7.

And this is just to build a shrine out of wood.

These two projects are doing two different things. One is trying to preserve a human activity over a non-trivial period of time. The other is attempting to monetize it so that it can be included in the bottom line for the next quarter. And perhaps to float the idea that your business might be able to dispense with those pesky new employees acquiring process knowledge.

Which brings me to another alarm call. This time from an anonymous group of senior professionals in the UK and European insurance and reinsurance industries called Sounding the Alarm and published in English, French and German. It is not long, so I urge you to read it, but I want to focus on this passage about how the insurance industry is responding to the climate crisis:

Our industry’s strategy is to manage renewals in order to limit our exposure as the physical risk manifests so that premiums are sufficient to cover the rising claims load. This is not a malicious act but a simple response to the commercial realities we are faced with.

We will do this in three ways which many clients are unaware of and governments across Europe are failing to internalise the consequences of:

Firstly, we will reprice our cover. We will simply make policies much more expensive to reflect this elevated physical risk and uncertainty. This will have wider consequences for economic inequality, making it harder for less affluent households to access insurance. It will also increase costs for critical industries such as farming or shipping , creating a significant social and financial burden for government s and, in turn, its taxpayers.

Secondly, we will limit coverage to exclude elevated risks such as wildfires as well as other less predictable risks . The nature of insurance being re – negotiated on a 12 – month basis allows us to do this without friction. Ensuring customers really understand that this is happening is critical.

Thirdly, if there is no way to bring premiums and claims into balance or introduce risk reduction measures we will – for certain geographies and sectors – simply withdraw coverage . This will particularly affect coastal, mountain and flood-prone communities.

This approach is our way of managing our own financial exposure and maintaining profitability at a time of increasing physical risk and increasing uncertainty. Doing so is critical to ensure we can continue to pay claims, therefore fulfilling both our fiduciary duty and our role in society.

This is the flipside of the capitalisation of process knowledge of course. If it can no longer be monetized then ditch it, all the while spouting about “our role in society”. The people on the receiving end will not care whether it is a malicious act or not, it will feel like one.

Both of these stories tell us which side many actuaries are on, and it is the side of capital rather than the side of the people from who it has been extracted. It is not malicious, and it is how many actuaries understand fiduciary duty. To the contract rather than to public interest.

I look back on my own actuarial career. Some time as a scheme actuary where I really felt I was safeguarding the pensions of ordinary people, some time protecting the wealth of already fairly wealthy people from the tax authorities, some time in insurance feeling really quite remote from customers of any kind. And then 10 years helping students into actuarial work. Have I really just been a tool of capital this whole time? Is this why a IFoA sustainability WhatsApp group, which is all about connecting sustainability thought leaders together and raising awareness of the impact of the climate emergency across the finance sector (where I first saw the Sounding the Alarm memo), is so small?

Dan Davies, highlighting Robin Wriggleworth’s new book, A Fabulous Debt: The Epic Story of How Bonds Built the Modern World, wonders whether life insurance actuaries and general insurance actuaries (referred to as casualty actuaries here) have a similar relationship as bond traders and equity traders. It’s a good read. There is even a reference to Craig Turnbull’s magisterial A History of British Actuarial Thought! And this is the conclusion:

Which leads me to the paradox of the title. Reading the histories of actuaries, there seems to be quite a similar needle between the life and non-life insurers; one group place their trust in the higher mathematics, the other deals with heuristics, rules of thumb and vibes. It all comes to a head when you have to draw up the accounts, of course – the big intellectual battle seems to have been the casualty actuaries’ practice of setting reserves depending on the sum of each individual policy, which is really contrary to the spirit of treating risks as draws from a single distribution.

So it makes me think that there is some potential general principle here. Fields of human endeavour where management makes most use of complicated mathematics are likely to be less intrinsically complex and difficult. We use quantitative techniques only when we are content with regarding something as quantifiable.

This feels like a possible explanation. If your acknowledged expertise is in clever mathematics, you are likely to favour techniques which make more things quantifiable and therefore manipulable with clever mathematics. And the more actuaries flood into new fields, the further the quantifying will go.

Capitalism has always been in the business of quantifying things, allocating them to someone (often using considerable violence to do so) and then selling them as property. But late-stage capitalism has a now almost cartoonish obsession with quantifying even things that cannot be easily or successfully quantified, extracting ownership of the thing at the point of quantifying it and then selling it on.

When all the process knowledge has been turned into intellectual property, proprietary knowledge behind paywalls that hide the fact that it doesn’t really work any more, businesses will start to realise that they still have important gaps that are now nearly impossible to fill. There may be a Sounding the Alarm memo about it from anonymous insiders.

But it will be too late by then.

Telling a different story

07. October 2026 · Write a comment · Categories: Actuarial, Cartoons, COVID-19, Economics, Education, Health, Prediction, Professions, Regulation, Risk

We shall not cease from exploration
And the end of all our exploring
Will be to arrive where we started
And know the place for the first time.

T.S. Eliot – Four Quartets

I feel like I am having a bit of a T.S. Eliot week. I have been writing about the OBR since the beginning of this blog in 2013, with their repeated failures as a forecaster forming the banner for the blog for many years.

What has brought me back to the OBR, as if for the first time, is recalling during the recent Funding the Future conference the words of the very good and wise friend of mine who was there with me. I had invited him to talk to one of my undergraduate groups at the University of Leicester during a professional skills session a few years ago. We were looking at past disciplinary cases of the Institute and Faculty of Actuaries and discussing what the actuaries involved could have done better.

In one of the case studies we considered, an actuary had produced a quarterly reserving report for a company, estimating the reserves on a ‘high’ basis of £74.5 million, a ‘low’ basis of £36.9 million and a ‘best’ basis of £52.1 million. The company then produced financial statements for the year, approved by the board of which he was a part, containing a reserve figure of £15.5 million. My friend told the students that the way to challenge in a situation like this is not to focus on the numbers, but instead see that each different number reflects a different story being told. So you need to look at what the story would need to be for the £15.5 million to be an appropriate figure and take issue with the things that don’t make sense within that story.

It was great advice then and still is, and it is definitely the way to look at the OBR I think. We find a story unsatisfactory if the characters are shallow, do not behave in a credible way, and the plot oversimplifies a much richer situation (something which every story must do to some extent to be manageable to the reader) in a deeply unsatisfying way.

Several other commentators have talked about the inability of the OBR to forecast anything (including me) – this is the equivalent of insufficiently fleshed out characters behaving in unbelievable ways. Richard Murphy, for instance, pointed out how ridiculous the proposed character plotline for inflation was at the last budget:

Whereas in fact of course the downward trajectory predicted at the last budget didn’t look remotely likely even then. The Consumer Prices Index (CPI) rose by 3.1% in the 12 months to August 2026, up from 2.9% the previous month.

However it is Dan Davies’ recent couple of Substack posts (one and two) which get to the heart of the problem in my view. Dan Davies’ contention is that it is the plot oversimplification which is the main problem here. As he says:

The system we have set up only seems to be able to communicate two states though – the signal is either “COMPLIANT – WAR CHEST” or “NONCOMPLIANT – BLACK HOLE”. It would be a significant improvement even for the OBR to add some measure of urgency or non-urgency to its press release – a sentence like “this surplus is well within the forecast error, however, so it should not be used to justify a change in policy”.

But, in his view, it is even worse than that:

In general, most things which a government spends money on will tend to have effects on the economy which go well beyond the five year forecast. The OBR uses an information set which contains only a small and quite arbitrary subset of government decisions – it is, literally, not capable of representing the system it is meant to control at an acceptable level of accuracy.

The justification for ignoring the future consequences of current spending seems to be no more sophisticated than what we pejoratively call “Treasury Brain” – the belief that a) spending departments always claim that their budget should be seen as an investment, b) that they systematically overestimate the long term benefits of current costs and c) that the best solution to a) and b) is to completely ignore any future benefits from investment or future costs caused by noninvestment. It’s just not good enough.

It is this dog’s breakfast that apparently tells us whether we are on track to meet the plotline the government has set for itself. Its three fiscal rules:

Rule 1. The current budget should be on course to be in balance or surplus by 2029/30 (‘stability rule’);

Rule 2. Net financial debt should fall as a share of the economy in 2029/30 (‘investment rule’); and

Rule 3. Some types of welfare spending must remain below a pre-specified level (the ‘welfare cap’).

And if that gruesome threesome doesn’t set your heart racing about the country’s future story, you are not alone. Because the people banging on about fiscal space will always push for governments to spend less, regardless of the circumstances. For instance, at the height of the pandemic in December 2020, Moody’s were saying this (with excess deaths already estimated at over 30,000 in the UK by Public Health England at that point):

However, compared to the government’s March budget (that was quickly overtaken by events), there are some initial signs that fiscal policy outside of investment is likely to be less expansive than previously announced. What remains unclear is whether this ambition will be able to withstand the political pressures that seem to be inevitable given the government’s previous commitments. Even before the Spending Review, longer-term spending commitments for health, education, and defence had already been announced. Together, these three areas account for around 60% of total expenditure.

One of the themes from the Funding the Future conference was, to quote from Educating Rita:

“There must be better songs to sing than this”.

I agree. One possibility is proposed by the New Economics Foundation, who suggest categorising policies by their level of multiplier effect (ie how much economic activity is increased by an increase in spending) and replacing fiscal rules with a “fiscal referee” who can make a more holistic judgement addressing many of the omissions Dan Davies complains about. This would then lead to a discussion rather than the compliant/non-compliant cliff edge we currently have, and allow the government to make its case. And it would not automatically incentivise cuts like the current system does.

Other possibilities exist. As Dan Davies describes it:

any accounting system is a mental prison of some kind, and one which needs to be periodically escaped from

In my view, a jailbreak is long overdue.

Models of the first and second kind

09. September 2026 · Write a comment · Categories: Actuarial, Economics, Education, Health, Professions, Science Fiction
Copper parts of a vehicle have been mounted on a much larger wooden structure in an exhibit at the Vatican Museums
My photograph of an exhibit at the Vatican Museums

Worldbuilding in science fiction has certain rules, or so I thought. And the first of these according to some sources at least seems to be consistency. According to the Quirkworthy website:

The basic message is very simple: your world must be internally consistent. Doesn’t matter if it’s science fiction or fantasy, and it makes no odds if it’s a novel, game, or opera. At all times, your world must be consistent to itself.

So when Jeff Noon and Steve Beard came to the Birmingham Science Fiction Group a couple of years ago, I pricked up my ears when one of them (Jeff I think) said that the first book of the Ludwich Chronicles, Gogmagog, which they were discussing, was not consistent. They were following Cady Meade’s viewpoint which journeyed 60 miles along the river Nysis inside a ghost and the focus was to set a particular mood. It was built from the bottom up.

This idea appealed to me then, and has, in my view, become a more and more important idea recently. We all build our views of the world from the bottom up based on our own experiences and they are frequently inconsistent with those of other people. The problem comes when we stop accepting that and treat our models as, in some way, top down and universal.

I had a great example of this a few years ago in the Vatican Museums. Some bits of bronze they reckoned to be parts of a cart buried in an Etruscan tomb had been discovered and were then displayed on an entirely speculative wooden model of a cart (to be fair to them, the Monteleone chariot dated to around 530 BC, was a rather more complete find and the wooden model looks like it was modelled on that). The trouble is, once you have seen the pieces on the cart, it is difficult to think of them in any other way. Rather like some of those early dinosaur reconstructions and possibly unhelpful in a field as fast-moving as archaeology.

Source: The book of the great sea-dragons, Ichthyosauri and Plesiosauri, [gedolim taninim] gedolim taninim, of Moses. Extinct monsters of the ancient earth. With thirty plates, copied from skeletons in the author’s collection of fossil organic remains, (deposited in the British museum.) by Hawkins, Thomas, 1810-1889
https://archive.org/details/bookgreatseadra00hawk/page/n5/mode/2up

We do this everywhere. Every competitive market is a model, as relentless in its pursuit of victory within the rules (all of which must be stress-tested as to how they are going to be applied by each individual referee in each individual encounter) as the Premier League. Sometimes if you question some of the underlying assumptions behind some of these models, you are told that is just the way the world works.

But the way the world works is opaque. Novelists have attempted to show us glimpses of it for centuries. Historians are sometimes able to agree about how it has worked in a specific geography for a short period of time. Occasionally, as a result of our own experiences, we may feel that we have managed to grasp some truth about the world and how it works in our own lives. But often the clarity slips through our fingers when we throw more light on it. The clarity certainly never seems to last that long. For clarity you often need an organisation signed up to a model.

Much has been written in recent years about our dependence on models and our inability to look outside them in many cases, most notably Escape from Model Land by Erica Thompson. This has mainly focused on the models we make to try and understand the world. But there also models behind those models which effectively determine what kinds of models of the first kind we create. These are the organisations and institutions we look at the world from.

It was in a time of rapid transition and uncertainty much as our own is that the groups of organisations we call professions emerged in the nineteenth century. The model of the second kind they adopted was partly that set out by Daniel and Richard Susskind in their book The Future of the Professions.

According to the Susskinds, there is a Grand Bargain between society and the professions, which means (and I am paraphrasing a little here), in return for professions providing:

  • Expertise, experience and judgement;
  • Delivered affordably, accessibly, reassuringly and reliably;
  • With knowledge and methods maintained and kept up to date, members trained, standards and quality of work enforced and only appropriately qualified individuals allowed in;
  • Acting honestly and in good faith; and
  • Putting clients’ interests ahead of their own.

In return, society will give the professions:

  • Respect and status;
  • Exclusive rights to perform/provide socially significant activities or services; and;
  • Independence to decide how they do it and how much they can be paid for it.

What professions expect from society is jealously guarded. My own profession’s uneasy relationship with the universities can plausibly be traced back to Newton’s influence on what mathematics could be taught there, therefore denying actuaries the status they craved without setting up their own professional bodies to supply it. The last attempt to allow an allied profession to carry out limited medical activities ended with the Leng Review effectively strangling it, egged on noisily by the BMA. And it is not hard to find articles defending increases to executive remuneration way beyond that of the people who work for them as the norm.

What society expects from professions often gets less attention directed at it. Four of the five bullets above tend to form part of the professional code of most professions in some form, although there are frequent fines of large professional firms for failures in the standard of the services provided.

But what of delivering professional services affordably, accessibly, reassuringly and reliably? What has tended to happen, as the group of people requiring professional services has widened, is that the affordability and accessibility have been increasingly called in to question. And online self-service looks likely to be attempted for a wider and wider range of services as time goes on.

So is the professional structure we have going to remain? If the experience of the nineteenth century, when most of these professions emerged, is anything to go by, the level of disruption will vary hugely by profession and institution and the period of transition could be very long in some cases. But it seems clear that such a period has begun. This has serious implications for actuarial education, amongst much else.

And whatever replaces them is likely to be built from the bottom up.

Normals: new and otherwise

25. August 2026 · Write a comment · Categories: Actuarial, Climate Change, COVID-19, Economics, Health, Media & Politics, Risk

Climate campaigners get very irritated with media talking about the “new normal”, pointing out, quite reasonably, that for it to be the new normal would require a degree of climate stability that we have not got, nor have any prospect of getting while we continue to argue about whether net zero (the policy, remember, which is about moving us to a position where we don’t increase the amount of carbon in the atmosphere year after year) is affordable. Poverty and health campaigners got very irritated by the call to “get back to normal” after the pandemic, when it had so clearly demonstrated how our “normal” way of organising society had failed to protect so many of its citizens. As even I could see in March 2020:

My view is that some things that must be different post COVID are already clear. I think as a society we are going to demand more resilience, for example:

  • Resilience of our health service – this means much higher levels of spending, building deliberate over-capacity into the system in normal times;
  • Resilience of our food supplies, for example strengthening domestic supply chains;
  • Resilience of our population, so that we do not have 1.6 million food parcels needing to be given out in a year by the Trussell Trust, in the absence of a pandemic, for instance; and
  • Resilience of our infrastructure – to everything from floods to banking crises to pandemics to storms and heatwaves.

A picture circulating at the time of a Santiago apartment block with a projection onto it of “No volveremos a la normalidad porque la normalidad era el problema” (we won’t get back to normal because normal was the problem) was actually taken the previous year when the Chilean President had used the word “normality” to justifying lifting the state of emergency, leading to large protests:

Source: https://x.com/inesmorsantos/status/1190192093165211648?ref_src=twsrc%5Etfw%7Ctwcamp%5Etweetembed%7Ctwterm%5E1190192093165211648%7Ctwgr%5E%7Ctwcon%5Es1_&ref_url=https%3A%2F%2Fodi.org%2Fen%2Finsights%2Fcovid-19-we-wont-get-back-to-normal-because-normal-was-the-problem%2F “We won’t go back to normal, because ‘the normal’ was the problem.”

But we all have trouble with fast moving situations, or even just moving situations. Remember the media coverage in the early weeks of Covid utterly focused on the number of cases going up each week rather than on the underlying pattern this showed, which had been predicted and could be responded to.

In the Institute and Faculty of Actuaries syllabus, subject CS2 Risk Modelling and Survival Analysis has 20% of its content on dealing with our trouble with moving situations via time series:

It boils down to a number of tricks to turn our moving situation into a non-moving or stationary situation, which we can then analyse.

So not being able to deal with things that aren’t stationary is entirely normal. Indeed the Standard Normal Distribution, originally developed in response to a gambler’s query and another thing that we spend a lot of time transforming other distributions into if we can, has a fixed mean of 0 and a fixed variance (a measure of how far things stray from the mean) of 1:

Outside statistical analysis, we use different techniques to make things appear normal. Denial, ie ignoring the departure from normality, is a big one. When this one is no longer tenable in the face of mounting evidence that we are not in Kansas anymore, we often try and depict where we have got to as normal now. This will have been a good strategy in the past: once a natural disaster has passed, taking stock of what has been lost and what remains and working within these new parameters makes more sense than hankering back to how things were before the disaster struck.

However this strategy comes unstuck when one or both of two things are true:

  1. The disaster, or change-event more generally, is not a one-off but a continuing process.
  2. The way we were living before the disaster made the disaster more likely.

So, on climate change, both 1 and 2 are true. On the pandemic, 2 (if you define the disaster as the number of people who died during it, which I do) is clearly also true. And, although it may not be a continuing process, none other than the former Chief Scientific Advisor to the UK Government regards another pandemic as “inevitable”.

We have built systems to look at past disasters and, in particular, try and guard against 2. The Covid Inquiry is working its way through the evidence about the pandemic, and has already produced definitive evidence on how we could do things differently for those who wish to read it, but the reporting of its work is patchy, with sometimes unhelpful fixations on the wrong thing.

And denial tends to fight back as our go-to defence mechanism, which is why we often seem to need to have Public Inquiries about the same things again and again and again.

It is all quite normal. That is the problem.

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.

Professions, triangulation and the costs of adaptation

28. July 2026 · Write a comment · Categories: Climate Change, Economics, Education, Health, Professions
The Charybdis is a swirling water feature in the temperate house at Savill Garden. It was designed by Giles Rayner in 2006. https://funandgames.org/web/wp-content/uploads/2020/09/The-Charybdis_Savill-Gardens_9257-2-scaled.jpg – you may have recently seen the original in The Odyssey

Last week I mentioned that I thought this blog, for the rest of the year at least, would be about what we resist, what we create and what we could nurture in the face of a terrifying future. This week I thought I should start to put a bit of flesh on that particular carcass.

One source for my thinking on this is Alex Steffen. I recently attended one of his Personal Climate Strategy: The Basics webinars. He is particularly good on the importance of continually updating your world view in the face of climate discontinuity and increasing evidence of societal brittleness, and how professions can often be a barrier to doing this:

The greatest danger in any work that asks you to think systemically about the future is getting locked into the worldview that made sense to you when you first began, that you built your successful career on.

We all have limited time and energy. Building up an insightful mental model of how the world works takes a lot of both. The pay-off is in the profit and sense of purpose gained from one’s expertise. It is very common, when you’re highly rewarded for a given set of working insights, to commit more to those insights as your career unfolds, to begin even to defend those insights from challenging new perspectives (ones you fear might devalue your intellectual stock in trade). This “sunk-cost expertise” can easily become a set of shackles.

The article then goes on to explain the process of triangulation, by which professionals can “deflate pressure (from the public, regulators or activist stakeholders) to change more quickly and shore up the power of management and experts who would otherwise be forced to admit that they don’t really know what they’re doing”. If someone starts by saying that they support what you are suggesting, then responds with a bunch of short-term easy actions and claims that these are the start of a journey towards what you are suggesting, you are probably being triangulated.

Another is a recent article by Richard Murphy on the political economy of adaptation. As he says:

The biological idea that first made me think this might be possible is called allostasis. It is not a complicated concept. It simply describes the way living organisms survive by continually adapting to the changing world around them.

As we all know, nothing alive exists in a stable environment. Every living thing must continually respond and adapt to changing circumstances. Human beings are no exception. Our brains and bodies are constantly anticipating change and adjusting to it. Most of that work happens without us ever noticing. Allostasis happens all the time, and most of us do not notice. But the fact is that this continual adaptation has a cost.

Murphy points out that, at a time of continual change like ours, that cost is high. And the adaptation required is much higher for people who cannot just throw money at their problems. He then goes on to say:

That changes how we think about political economy. Politics then becomes the process by which societies decide how those costs of adaptation are distributed, whilst economics becomes the study of how institutions either increase or reduce them. Accounting becomes the means by which we identify who ultimately bears the cost of adaptation and health becomes one of the principal ways in which we observe its effects.

I think there is a lot to this approach, which would also provide a structure to identify and critique the triangulation process set out by Steffen. Murphy only mentions education once in this piece:

Education should recognise that human beings learn differently, rather than assuming that everyone should conform to a single model.

I would go a lot further than that, because I think education is the key to helping individuals with their own adaptation strategies as well as in developing the political understanding to see how the costs of adaptation are currently distributed and how to change that within a democratic system. This seems to be an extension of what I have been writing recently about how not to be a reverse-centaur for instance.

The implications for this in health, education and our institutions are considerable in my view and growing all the time. So that is what I am going to be writing about for a while.

Starting next week with allostasis.

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.

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.

« Older articles