Again and again and again

27. November 2025 · Write a comment · Categories: Economics, Health, Media & Politics

On 20 November, the UK Covid-19 Inquiry published its second report and recommendations following its investigation into ‘Core decision-making and political governance’. The following day these were the headlines:

This contrasts with the Inquiry’s first report and recommendations following its investigation into the UK’s ‘Resilience and preparedness (Module 1)’ on Thursday 18 July 2024. Then the following day’s headlines looked like this:

Whereas the first report had recommended a radical simplification of the civil emergency preparedness and resilience systems, including:

  • A new approach to risk assessment;
  • A new UK-wide approach to the development of strategy, which learns lessons from the past;
  • Better systems of data collection and sharing in advance of future pandemics;
  • Holding a UK-wide pandemic response exercise at least every three years and publishing the outcome; and
  • The creation of a single, independent statutory body responsible for whole system preparedness and response.

The second report on the other hand merely reran the pandemic, pointing out where we went wrong on:

  • The emergence of Covid-19;
  • The first UK-wide lockdown;
  • Exiting the first lockdown;
  • The second wave; and
  • The vaccination rollout and Delta and Omicron variants.

And crucially who to blame for it. Its recommendations were far less specific and actionable in my view than those from the first report. And yet it got all the headlines, with glowering images of Baroness Hallett and pictures of Boris Johnson with head bowed.

The first report dealt with what we could do better next time and was virtually ignored (only The Daily Mirror and The Independent carried “They failed us all” headlines about the Covid Inquiry first report). The second dealt with who to blame and it dominated the headlines. I think this neatly encapsulates what is wrong with us as a country and why we never seem to be able to learn from our own past mistakes or the examples of other countries.

This is not about defending Boris Johnson or any of his ministers. It is about realising that they are much less important than our own ability to sort out our problems and study any evidence we can to help us do that.

The NHS suffers from the same problem, as Roy Lilley has described here, too many inquiries and most of their recommendations ignored. Again and again and again. We choose to focus on the minor and irrelevant at the expenses of the major and important. Again and again and again. As Lilley says:

Until we make it OK for people to say… I made a mistake… we will forever be trapped in a Kafka world of inquiries coming to the same conclusions…

…If inquiries worked, we’d have the safest healthcare system in the world. 

Instead, we have a system addicted to investigating itself and forgetting the answers.

It is part of a pattern repeated yesterday, focusing on the micro when our problems are macro. Rachel Reeves increased taxes by £26 billion in yesterday’s budget, which was much less than the £40 billion in her first budget, and yet still led to the BBC reporting “Reeves chooses to tax big and spend big” and the FT leading with “Rachel Reeves’ Budget raises UK tax take to all-time high“, and with this graph:

This is hilariously at odds with the message of what it was reporting last week:

The latter was obviously an attempt to head off a wealth tax, which appears to have been largely successful. Our averageness when it comes to tax, though, is supported by this graph using OECD data from Tax Policy Associates:

Our position in the middle of the pack will be little affected by what happened yesterday. And that and all the chatter about the OBR leaking it all an hour in advance rather drowned out the fact that there was relatively little additional spending (around £12 billion overall, a quarter of which was on the welcome removal of the two-child limit). The main point was to increase our “fiscal headroom” to £22 billion, ie the amount the Government can spend before they breach their own fiscal rules.

It looks like we are going to do what we are going to do, with fiscal headroom management masquerading as economic policy, and otherwise just sit around waiting for the next disaster. Which we will then have a big inquiry about to tell us that we weren’t remotely prepared for it. Which we will then ignore…and so it continues. Again and again and again.

AI Knows Zero

21. November 2025 · Write a comment · Categories: AI, Climate Change, Economics, Media & Politics, Professions

A couple of weeks ago I wanted to find an article I had written about heat pumps to check something. So I Googled weknow0 and heat pump. This did give me the article, from December 2022, I was after, but also an “AI overview” that I hadn’t requested. The above is what it told me.

Now this is inaccurate on a number of counts. Firstly, I have published 226 articles over the more than 12 years I have been writing on weknow0.co.uk and I have only mentioned heat pumps in two of these. These articles did focus on the points mentioned in 3 of the 4 bullet points above and in one of them I also set out how the market at the time (December 2022) was stacked against anyone acquiring a heat pump, a state of affairs which has thankfully improved considerably since. However to claim that my blog “provides a consumer-focused perspective in the practicalities and challenges of domestic heat pump adoption in the UK” is clearly hilarious.

In fact anyone seeing that would assume I talked about little other than heat pumps, so I decided to do a search on something else that I talk about infrequently and see what I got (I searched “weknow0 science fiction”):

This seems a considerably better summary of the recent activity on the blog, which is also unrecognisable as the blog summarised in response to the previous search.

Right at the end, it suggests a reason for the title of the blog which isn’t an unreasonable guess from a regular reader. But guess it still is, and it does not appear to have processed the significant number of blog posts with variants of we know zero in the title to fine tune its take.

So someone using the AI overview as a research tool would get a completely different view of what the blog was about depending upon which other word they used alongside weknow0. Perhaps that doesn’t matter too much to anyone other than me in this case, but it is part of a broader issue. It is not summarising the website it is suggesting it is summarising.

Of course many of you will now be shouting at me that I need to give the system more focused prompts. There is now a whole area of expertise, lectured in and written about at considerable length, called “prompt engineering”. There are senior professionals who have rarely given their juniors the time of day for years, giving the tersest responses to their completely reasonable queries about the barely intelligible instructions they have given for a piece of work, suddenly prepared to spend hours and hours on prompt engineering so that the Metal Mickey in their phone or laptop can give them responses closer to what they were actually looking for.

At this point, perhaps we should perhaps hear from Sundar Pichai, the Google CEO:

https://www.bbc.co.uk/iplayer/episode/m002mgk1/the-interview-decisionmakers-sundar-pichai-running-the-google-empire

As part of Faisal Islam’s slightly gushing interview with Pichai, we learn that the AI overview on Google is “prone to errors” and needs to be used alongside such things as Google search. “Use them for what they are good at but don’t blindly trust them” he says of his tools which he admits to currently investing $90 billion a year in. This is of course a problem, as one of the reasons people are reluctantly resorting to the AI overview is because the basic Google search has become so enshittified.

And that kind of echoes what Cory Doctorow has said about Google. Google need to maintain a narrative about growth. You will have picked this up if you watched the Pichai interview above, from the breathless stuff about “one of the most powerful men in the world” “perhaps being one of the easier things for AI to replicate one day” to:

You don’t want to constrain an economy based on energy. That will have consequences.

To the even more breathless stuff about us being 5 years from quantum computing being where generative AI is now.

The reason for all the growth talk, according to Doctorow, is that Google needs to be growing for it to be able to maintain a price earnings ratio of 20 to 1, rather than the more typical 4 to 1 of a mature business. So it’s all about the share price. As Doctorow says:

Which is why Google is so desperately sweaty to maintain the narrative about its growth. That’s a difficult narrative to maintain, though. Google has 90% Search market-share, and nothing short of raising a billion humans to maturity and training them to be Google users (AKA “Google Classroom”) will produce any growth in its Search market-share. Google is so desperate to juice its search revenue that it actually made search worse on purpose so that you would have to run multiple searches (and see multiple rounds of ads) before you got the information you were seeking.

Investors have metabolized the story that AI will be a gigantic growth area, and so all the tech giants are in a battle to prove to investors that they will dominate AI as they dominated their own niches. You aren’t the target for AI, investors are: if they can be convinced that Google’s 90% Search market share will soon be joined by a 90% AI market share, they will continue to treat this decidedly tired and run-down company like a prize racehorse at the starting-gate.

This is why you are so often tricked into using AI, by accidentally grazing a part of your screen with a fingertip, summoning up a pestersome chatbot that requires six taps and ten seconds to banish: companies like Google have made their product teams’ bonuses contingent on getting normies to “use” AI and “use” is defined as “interact with AI for at least ten seconds.” Goodhart’s Law (“any metric becomes a target”) has turned every product you use into a trap for the unwary.

So here we are. AI isn’t meant for most of you, its results are “prone to errors” and need to be used alongside other corroborating material or “human validation”. It needs you to take a course in prompt engineering even if you never did the same to manage any of your human staff. It is primarily designed to persuade investors to keep the share price up to the levels the Board of Alphabet Inc have become accustomed to.

Figleaf Economics

12. November 2025 · Write a comment · Categories: COVID-19, Demographics, Economics, Legal, Media & Politics, Professions

In my last post I referred to Dan Wang’s excellent new book, Breakneck, which I have now read at (for me) breakneck speed, finishing it in a week. It has made me realise how very little I knew about China.

Wang makes the point that China today is reminiscent of the US of a century ago. However he also makes the point that parts of the US were terrible to live in then: from racist segregation and lack of representation, to massive industrial pollution and insensitive planning decisions. As he says of the US:

The public soured on the idea of broad deference to US technocrats and engineers: urban planners (who were uprooting whole neighborhoods), defense officials (who were prosecuting the war in Vietnam), and industry regulators (who were cozying up to companies).

China meanwhile has a Politburo stuffed with engineers and is capable of making snap decisions without much regard to what people want. There is a sense of precarity about life there, with people treated as aggregates rather than as individuals. The country can take off in different directions very quickly and often does – there is a telling passage about the totally different life experiences of someone born in 1959 compared to someone born in 1949 (the worst year to be born in China according to Wang) – and even the elites can be dealt with brutally if they fall out of line with the current direction of travel. But they have created some impressive infrastructure, something which has become problematic for the US. Only around 10% of its GDP goes towards social spending, compared to 20% in the US and 30% amongst some European states, so there is no effective safety net. Think of the US portrayed in (as Christmas is fast approaching) “It’s a Wonderful Life” – a life that is hard to the point of brutality with destitution only one mistake away. And there is a level of social control alien to the west, controlling where people can live and work and very repressive of ethnoreligious minorities. And yet there is a feeling of progress and forward momentum which appears to be popular with most people in China.

As Wang notes at the end of his introduction:

“Breakneck” is the story of the Chinese state that yanked its people into modernity – an action rightfully envied by much of the world – using means that ran roughshod over many – an approach rightfully disdained by much of the world. It is also a reminder that the United States once knew the virtues of speed and ambitious construction.

The chapter on the one child policy, which ran for 35 years, is particularly chilling (China announced its first population fall in 2023 and its population is projected to halve to 700 million by 2100), and now the pressure is on women to have more children again. There is also a chapter on how China dealt with Covid – Wang experienced this first hand from Shanghai for 3 years – which made me understand perhaps why we wasted so much money in the UK on Track and Trace. You would need to be an engineering state to see it through successfully, and China ended up taking it too far in the end.

The economics of China is really interesting. As Wang notes:

China’s overbuilding has produced deep social, financial and environmental costs. The United States has no need to emulate it uncritically. But the Chinese experience does offer political lessons for America. China has shown that financial constraints are less binding than they are cracked up to be. As John Maynard Keynes said, “Anything we can actually do we can afford.” For an infrastructure-starved place like the United States, construction can generate long-run gains from higher economic activity that eventually surpass the immediate construction costs. And the experience of building big in underserved places is a means of redistribution that makes locals happy while satisfying fiscal conservatives who are normally skeptical of welfare payments.

This goes just as much for the UK, where pretty much everywhere outside London is infrastructure-starved (and, as Nicholas Shaxson and John Christensen show here in their written evidence to a UK Parliamentary Committee, even where infrastructure is built outside London, the financing of it sucks money away from the area where the infrastructure is being built and towards finance centres, predominantly in London), but there is also strong resistance from all the main parties to significant redistribution via the benefit system. This results in inequalities which even the FT feels moved to comment on and a map of multiple deprivation in England which looks like this:

The good news is that it doesn’t have to be this way in the UK, there are prominent examples of countries operating in a different way, eg China. The bad news is that China is not doing it because of economics. They are doing it because the state was set up to build big from the beginning. It is in its nature. The lesson of China is that it will keep doing the same things whatever the situation (eg trying to fix the population fall caused by an engineering solution with another engineering solution). Sometimes the world economy will reward their approach and sometimes it will punish it, but that will not be the primary driver for how they behave. I think this may be true of the US, the EU states and the UK too.

Daniel Kahneman showed us in Thinking Fast and Slow, how most of our mental space is used to rationalise decisions we have already taken. One of the places where I part company with Wang is in his reverence for economists. He believes that the US should listen more to both engineers and economists to challenge the lawyerly society.

In the foreword for The Principles of Economics Course from 1990 by Phillip Saunders and William Walstad, Paul Samuelson, the first person from the US to win the Nobel Memorial Prize in Economic Sciences in 1970, wrote:

“Poets are the unacknowledged legislators of the World.” It was a poet who said that, exercising occupational license. Some sage, it may have been I, declared in similar vein: “I don’t care who writes a nation’s laws—or crafts its advanced treaties—if I can write its economic textbooks.” The first lick is the privileged one, impinging on the beginner’s tabula rasa at its most impressionable state.

My view would be that the economists are already in charge.

As a result, my fear is that economics is now used for rationalising decisions we have already made in many countries now, including our own. We are going to do what we are going to do. The economics is just the fig leaf we use to rationalise what may otherwise appear unfair, cruel, divisive and hope-denying policies. The financial constraints are less than they are cracked up to be, but they are a convenient fiction for a government which lacks any guiding principles for spending and investment otherwise and therefore fears that everyone would just be asking for more resources in its absence, and they would have no way of deciding between them.

The Trigger’s Broom Process of Career Management

04. November 2025 · Write a comment · Categories: Actuarial, AI, Media & Politics, Professions, Regulation
New (left) and old (right) Naiku shrines during the 60th sengu at Ise Jingu, 1973, via Bock 1974

In his excellent new book, Breakneck, Dan Wang tells the story of the high-speed rail links which started to be constructed in 2008 between San Francisco and Los Angeles and between Beijing and Shanghai respectively. Both routes would be around 800 miles long when finished. The Beijing-Shanghai line opened in 2011 at a cost of $36 billion. To date, California has built only a small stretch of their line, as yet nowhere near either Los Angeles or San Francisco, and the latest estimate of the completed bill is $128 billion. Wang uses this, amongst other examples to draw a distinction between the engineering state of China “building big at breakneck speed” and the lawyerly society of the United States “blocking everything it can, good and bad”.

Europe doesn’t get much of a mention, other than to be described as a “mausoleum”, which sounds rather JD Vance and there is quite a lot about this book that I disagree with strongly, which I will return to. However there is also much to agree with in this book, and none more so than when Wang talks about process knowledge.

Wang tells another story, of Ise Jingu in Japan. Every 20 years exact copies of Naiku, Geku, and 14 other shrines here are built on vacant adjacent sites, after which the old shrines are demolished. Altogether 65 buildings, bridges, fences, and other structures are rebuilt this way. They were first built in 690. In 2033, they will be rebuilt for the 63rd time. The structures are built each time with the original 7th century techniques which involve no nails, just dowels and wood joints. Staff have a 200 year tree planting plan to ensure enough cypress trees are planted to make the surrounding forest self-sufficient. The 20 year intervals between rebuilding are the length of the generations, the older passing on the techniques to the younger.

This, rather like the oral tradition of folk stories and songs, which were passed on by each generation as contemporary narratives until they were all written down and fixed in time so that they quickly appeared old-fashioned thereafter, is an extreme example of process knowledge. What is being preserved is not the Trigger’s Broom of temples at Ise Jingu, but the practical knowledge of how to rebuild them as they were originally built.

Trigger’s Broom. Source: https://www.youtube.com/watch?v=BUl6PooveJE

Process knowledge is the know-how of your experienced workforce that cannot easily be written down. It can develop where such a workforce work closely with researchers and engineers to create feedback loops which can also accelerate innovation. Wang contrasts Shenzhen in China where such a community exists, with Silicon Valley where it doesn’t, forcing the United States to have such technological wonders as the iPhone manufactured in China.

What happens when you don’t have process knowledge? Well one example would be our nuclear industry, where lack of experience of pressurised water reactors has slowed down the development of new power stations and required us to rely considerably on French expertise. There are many other technical skill shortages.

China has recognised the supreme importance of process knowledge as compared to the American concern with intellectual property (IP). IP can of course be bought and sold as a commodity and owned as capital, whereas process knowledge tends to rest within a skilled workforce.

This may then be the path to resilience for the skilled workers of the future in the face of the AI-ification of their professions. Companies are being sold AI systems for many things at the moment, some of which will clearly not work with few enough errors, or without so much “human validation” (a lovely phrase a good friend of mine actively involved in integrating AI systems into his manufacturing processes used recently) that they are not deemed practical. For early career workers entering these fields the demonstration of appropriate process knowledge, or the ability to develop it very quickly, may be the key to surviving the AI roller coaster they face over the next few years. Actionable skills and knowledge which allow them to manage such systems rather than being managed by them. To be a centaur rather than a reverse-centaur.

Not only will such skills make you less likely to lose your job to an AI system, they will also increase your value on the employment market: the harder these skills and knowledge are to acquire, the more valuable they are likely to be. But whereas in the past, in a more static market, merely passing your exams and learning coding might have been enough for an actuarial student for instance, the dynamic situation which sees everything that can be written down disappearing into prompts in some AI system will make such roles unprotected.

Instead it will be the knowledge about how people are likely to respond to what you say in a meeting or write in an email or report, and the skill to strategise around those things, knowing what to do when the rules run out, when situations are genuinely novel, ie putting yourself in someone else’s shoes and being prepared to make judgements. It will be the knowledge about what matters in a body of data, putting the pieces together in meaningful ways, and the skills to make that obvious to your audience. It will be the knowledge about what makes everyone in your team tick and the skills to use that knowledge to motivate them to do their best work. It will ultimately be about maintaining independent thought: the knowledge of why you are where you are and the skill to recognise what you can do for the people around you.

These have not always been seen as entry level skills and knowledge for graduates, but they are increasingly going to need to be as the requirement grows to plug you in further up an organisation if at all as that organisation pursues its diamond strategy or something similar. And alongside all this you will need a continuing professional self-development programme on steroids going on to fully understand the systems you are working with as quickly as possible and then understand them all over again when they get updated, demanding evidence and transparency and maintaining appropriate uncertainty when certainty would be more comfortable for the people around you, so that you can manage these systems into the areas where they can actually add value and out of the areas where they can cause devastation. It will be more challenging than transmitting the knowledge to build a temple out of hay and wood 20 years into the future, and will be continuous. Think of it as the Trigger’s Broom Process of Career Management if you like.

These will be essential roles for our economic future: to save these organisations from both themselves and their very expensive systems. It will be both enthralling and rewarding for those up to the challenge.