Today marks 100 years since the birth of Genrikh Altshuller.

I never met him.

The closest I came was a rumour that he might sign copies of his newly published ‘Innovation Algorithm’ book published through the Altshuller Institute in the US. The year before my first TRIZCON in 1999. Sadly, he passed away before the books could be shipped back and forth across the Atlantic. The thought that I might acquire a copy of a signed book from the man I’d admired for so long turned out to be a momentary wish that would never be granted.  

And yet, in a strange way, I feel like I have spent much of the last 35 years in conversation with him. It began in 1991, when I was working at Rolls-Royce. I first came across the 40 Inventive Principles of TRIZ. They immediately intrigued me. Here was a suggestion – an outrageous suggestion, to some of my colleagues – that invention might not simply be a mysterious act of genius. Perhaps there were patterns. Perhaps the same kinds of problems had been solved before. Perhaps there was something systematic to be learned from the world’s inventors.

I wanted to know more. I needed to know more. My search led me to Altshuller’s Creativity As An Exact Science. The Rolls-Royce library requested a copy on loan from the British Library. Six weeks later, it arrived. I remember looking at it and seeing that I was the third person in Britain ever to have opened it. Convinced that this might be the only copy in the country, I am now slightly embarrassed to admit that I surreptitiously photocopied every page and made my own copy. That copy became rather important.

“Nothing invented outside Rolls-Royce could possibly be any good”

Rolls-Royce in those days was a rather arrogant company. Or perhaps, more accurately, the engineers were. There was a fairly widespread belief that if something had been invented outside Rolls-Royce, it probably wasn’t good enough. And so, when I began trying to spread the word about Altshuller’s extraordinary proposition – that creativity could be an exact science – the scepticism was almost absurd. Surely creativity couldn’t be systematised. Surely there couldn’t possibly be only 40 Inventive Principles. Surely somebody somewhere had misunderstood something.

So we did what Rolls-Royce engineers do. We spent the next three years trying to prove him wrong. We looked for more principles. We challenged the patterns. We tested the ideas against real problems. We searched for the holes in the theory.

And, along the way, something rather inconvenient happened. We generated dozens of patent applications. Eventually, we began to realise that we’d been asking the wrong question. The question wasn’t, ‘was Altshuller right?’ The real question was, ‘was it useful? That distinction has stayed with me ever since.

No methodology is the truth. No model captures the entire complexity of reality. No set of principles can possibly describe every act of invention. But if a body of knowledge repeatedly helps people solve problems that they were previously unable to solve, perhaps arguing about whether it is perfectly right is missing the point.

Altshuller’s work was useful. Very useful.

The book in the drawer

After the initial excitement, something rather curious happened. Altshuller’s work faded from view. I don’t know whether other engineers in the Company had the same experience, but I found myself returning to Creativity As An Exact Science whenever I needed fresh impetus on a difficult problem.

Only I did it quietly. The illegally copied book lived hidden in a drawer in my desk. Perhaps that was because the scepticism had never entirely gone away. Perhaps it was simply easier not to have the conversation. But whenever conventional thinking ran out of ideas, there was Altshuller, waiting in the drawer. And, remarkably often, he had something useful to say.

Building on the foundation

When I eventually left Rolls-Royce to establish what has now become Systematic Innovation, I knew exactly where the foundations would lie. Altshuller’s work would be central. But we also knew that the work could not simply stand still. Altshuller had started something enormous. He had demonstrated that invention could be studied systematically, that recurring patterns could be discovered, and that those patterns could be made available to other people.

The research needed to continue. And the tools needed to become easier to use and easier to teach. There was another principle that mattered to us too. Altshuller had always made clear that his work was intended for the benefit of mankind. So we made an early decision: once our research had paid for itself, the resulting tools would be made freely available. It seemed the right way to honour the spirit in which the work had begun.

The great unfinished story

After Altshuller’s death, something else became apparent. The TRIZ world had lost its centre of gravity. We tried, in our own small way, to help reunite it. The real competition, as far as we were concerned, wasn’t another group of TRIZ practitioners. It was Big Consulting and all the organisations offering clients expensive but largely conventional ways of thinking about innovation. But the vacuum left by Altshuller’s passing created a different dynamic. The anointed TRIZ Masters often seemed happier arguing with one another.

That always struck me as a tragedy. Here was a body of knowledge intended to help humanity solve difficult problems… and too much energy was being spent debating ownership of the intellectual territory.

We even at one point tried to raise the money to make a film about Altshuller’s life. There was no interest. Which also remains astonishing to me. His story was – and still is – an extraordinary one. A young Soviet engineer who decided to study invention. A man who wrote letters to inventors asking how they had made their discoveries. A researcher who began to uncover patterns in millions of patents. A thinker who dared to suggest that creativity might be made systematic. And spent time in a Gulag for his troubles. If ever there was a story that deserved to be told on film, surely this is one. Perhaps one day it will be. If there’s any justice it will.

Standing too far ahead of the parade

There is an expression about people who are so far ahead of their time that they appear to be standing alone. I sometimes think Altshuller was standing too far ahead of the parade. His ideas were difficult enough to accept in the middle of the twentieth century. Perhaps they were still too difficult to accept in the first two decades of the twenty-first. And perhaps even now, we haven’t quite caught up with him. But I have a suspicion that we may be getting closer.

The current excitement surrounding artificial intelligence has reopened some very old questions. Can creativity be systematised? Can invention be accelerated? Can we learn from the accumulated knowledge of previous solutions? Can machines help humans navigate the enormous space of possible ideas? These are not entirely new questions. Altshuller was asking them decades ago.

I have heard Satya Nadella quoted as saying that the AI industry may be “one innovation” away from Artificial General Intelligence. I suspect it is probably more like fifty-seven. And I suspect Altshuller knew what eight of them were back in the 1960s.

Such is life.

Some people receive recognition for their world-changing contributions during their lifetime. Others have to wait. Sometimes for decades.

Perhaps his time is coming

I never met Genrikh Altshuller. I never had the opportunity to thank him personally for the direction he gave my career. I never got to tell him about the engineers at Rolls-Royce who spent three years trying to prove him wrong, and accidentally generated dozens of patent applications in the process. I never got to tell him that the book I secretly photocopied in 1991 would become part of the intellectual foundation for an organisation that has now spent decades continuing the research journey he began. And I never got to tell him that, whenever the world seemed to be running out of ideas, I still found myself metaphorically opening that drawer. But perhaps that is the nature of real intellectual influence. You don’t have to meet someone for them to change the way you think.

Altshuller gave me – and a small but eager coterie of others – a different way of looking at invention. Not as magic. Not as a gift bestowed upon a fortunate few. But as something that could be studied. Something that could be understood. Something that could be learned. He called it Creativity As An Exact Science.

Perhaps the science was never going to be entirely exact. But the idea was important enough to change lives. It certainly changed mine. And as we today celebrate the centenary of his birth, I find myself wondering whether the rest of the world may finally be ready to catch up. One day soon, I think, Altshuller’s time will come.

It would be nice to think that his hundredth birthday might mark the tipping point.

Happy centenary, Genrikh.

Here’s to the parade finally catching up with you.

Every culture has its version of the ugly duckling story. Different from the others, awkward and seemingly unattractive, the duckling doesn’t fit in. It is mocked, rejected and misunderstood. Until, one day, it grows into a beautiful swan.

The moral is usually taken to be that appearances can deceive: what looks ugly today may turn out to be beautiful tomorrow. The outsider may become the admired insider. The misfit may become the influencer.

It is a surprisingly good metaphor for innovation. New ideas often begin life looking a bit like ugly ducklings. They are different. They don’t fit existing categories. They challenge assumptions. Most people don’t understand them, and many people don’t like them.

Then something changes. The idea begins to work. Customers discover its value. Adoption accelerates. The previously strange becomes desirable. What was once dismissed becomes fashionable. Eventually, everyone wants to be associated with the swan.

This is the familiar shape of the S-curve. At the beginning, progress is slow. The idea is finding its feet. Then comes the steep part of the curve: adoption accelerates, customers love the product, revenues grow and confidence builds. The organisation has found something that genuinely works.

For a while, it can feel as though the good times will last forever. But they don’t. Every S-curve eventually reaches an inflection point. This is the point at which the curve’s rate of growth is at its maximum. Beyond it, the curve continues upwards, but the gradient begins to decline. Growth is becoming harder, and we leave the ugly duckling story and enter a new one. One in which the swan starts to struggle.

In the first half of the S-curve, the organisation is generally doing what it set out to do. Take the beauty industry. At its best, the beauty industry is genuinely about beauty. It helps people look and feel more attractive. Cosmetics can be pleasurable, creative and confidence-enhancing. Hairdressing, skincare, fashion and many forms of personal care can help people express themselves and feel good about themselves.

The customer has a need. The industry helps satisfy it. That is a virtuous relationship.

But then the market matures. The obvious customers have been acquired. The obvious products have been developed. Competition intensifies. Sales targets that were once easy to hit become harder. Margins come under pressure. Growth slows. And the organisation faces a problem that every mature business eventually encounters: how do we persuade people to buy more when they don’t actually need more?

There are many possible answers. Some are good. Innovation can create genuinely new value. Better products can solve new problems. Entirely new customer needs can be discovered.

But there is another answer. One that turns out to be a lot easier to achieve. Change the customer’s perception of the problem. If it is difficult to persuade people that they need to become more beautiful, try persuading them that they are not beautiful enough.

And so the proposition subtly changes. Look how beautiful you could be becomes look at what is wrong with you. Confidence becomes insecurity. Aspiration becomes anxiety. The promise of beauty becomes the fear of ugliness.

Fear is a remarkably effective sales mechanism. Once its logic takes hold, it can become self-reinforcing. The more insecure people feel, the more products they buy. The more products they buy, the more the industry can normalise increasingly elaborate interventions. The standard of the “ideal” moves further away from ordinary human reality, creating yet more dissatisfaction.

The beauty industry has, in effect, started to sell the opposite of what it originally promised.

This is what makes the S-curve more than just a model of growth. It can also describe a change in the purpose of an industry. Before the inflection point, the enterprise creates value by helping customers move towards something they genuinely want. After the inflection point, growth can increasingly depend upon making customers feel that they are further away from it.

The industry doesn’t necessarily become evil overnight. There is no meeting at which somebody announces, “From now on, our purpose is to make our customers miserable.” It happens incrementally. A slightly more anxious advertisement. A slightly more unrealistic image. A slightly more aggressive sales target. A slightly more extreme product. A slightly greater emphasis on what is wrong rather than what is right. Each individual decision looks commercially rational. But taken together, they now, post-inflection point, produce something quite irrational: an industry whose continued growth depends upon the failure of its customers to feel fulfilled.

The beautiful swan has become an ugly one.

The the same pattern is found everywhere. Let’s call it a first principle.

The healthcare industry begins with a noble purpose: helping people stay healthy, recover from illness and live longer, better lives. But a mature healthcare economy increasingly find itself making more money from sickness than from health.

The fitness industry begins by helping people become stronger, fitter and more energetic. It ends up selling anxiety about body image, inadequacy and self-worth.

Fashion begins as self-expression and creativity, before becoming increasingly concerned with the fear of being unfashionable.

Social media begins by connecting people and strengthening communities, before discovering that comparison, outrage and inadequacy are extraordinarily effective ways of keeping people engaged.

In each case, passing the growth rate inflection point triggers the start of what can easily turn into a 180-degree reversal. The business starts by selling the positive condition that people want. Then, as growth becomes harder, it discovers that it can make money by selling the negative condition that stands between people and that positive condition.

Health becomes sickness.

Beauty becomes ugliness.

Confidence becomes insecurity.

Connection becomes loneliness.

Flourishing becomes dissatisfaction.

There is something almost Orwellian about this.

The industry retains its original name while gradually becoming its opposite.

The beauty industry becomes an ugliness industry.

The healthcare industry becomes a sickness industry.

An industry whose stated purpose is human flourishing can end up depending upon human dissatisfaction, and hence creating the precise opposite of flourishing.

And perhaps this is one of the great dangers hidden in the second half of an S-curve.

We tend to think of organisational decline as a financial problem. Growth slows. Costs rise. Competitors appear. Margins disappear. But there is another, deeper form of decline. The organisation can continue to succeed financially while becoming less aligned with the reason it exists. Indeed, its financial success can make the problem harder to see. The swan doesn’t look ugly to those inside the industry, it looks like a monthly pay cheque. In the same way that the problems of mature – top of the s-curve – capitalism, from a capitalist’s perspective, will be solved by more capitalism. That is what makes the ugly swan dangerous at a societal level.

The question is not simply where we are on the S-curve. It is, “what are we selling now?” Are we still helping people achieve something meaningful, something they genuinely value? Or have we discovered that it is easier to make money by convincing them that they are deficient, inadequate, unhealthy, unattractive, unsuccessful or incomplete?

The first half of the S-curve can produce beautiful swans. The second half almost always produces ugly ones. In which case, perhaps the real challenge of innovation is not simply learning how to transform ugly ducklings into swans, it is knowing when and how to retire – or reinvent – those swans before they turn ugly.

Satya Nadella recently suggested that the world may be “one innovation” away from AGI. I understand what he means. In a field moving as rapidly as artificial intelligence, it is entirely possible that one apparently simple conceptual breakthrough could change the trajectory overnight. History is full of such moments: an invention that suddenly removes a previously immovable constraint and makes what seemed impossible become merely difficult.

But I wonder whether there is another way of looking at the journey to AGI. Perhaps the question is not which innovation will get us there, but how many innovations are still missing?

Over the weekend, we saw what may turn out to be one of them. A team in Shanghai has proposed what it calls Next Concept Prediction (NCP), a potentially significant departure from the way today’s Large Language Models work. The basic observation is deceptively simple. LLMs are fundamentally built around predicting the next token, or, loosely, the next word. Humans, by contrast, appear to operate much more naturally at the level of concepts: we don’t experience thought as an endless stream of individual words, but as structures, relationships and ideas. NCP attempts to exploit that difference. The results reported so far are still awaiting the kind of independent validation that will tell us how significant the breakthrough really is. But if the claims stand up, the potential is striking: a step-change in both efficiency and energy consumption, alongside an important shift in the way machines represent and predict information.

What interests me, however, is not simply whether NCP works. It is why the direction of travel seems so familiar. From a TRIZ perspective, the move from predicting individual tokens to operating at the level of concepts looks remarkably like a jump along one of the classic patterns of technological evolution: the Mono–Bi–Poly trend.

First one element. Then two. Then many. Or, more generally, increasing sophistication in the way components are combined and organised to perform a function.

If that interpretation is right, NCP may not be an isolated stroke of genius. It may be a relatively predictable step in a much larger evolutionary journey. One that will eventually progress along all of the Trends that have emerged from our Evolution Potential research.

If we can look at today’s generative AI systems through this Evolution Potential lens, we can quickly map where the technology sits today, what the Shanghai team have just delivered, and which jumps would be needed in order to achieve the mythical AGI.

The difficult bit being deciding what definition of AGI to use. In the end, I’ve opted for Jeff Hawkins’ vision of machines possessing a more general, human-like capacity for understanding and learning.

Here’s an Evolution Potential radar plot showing the current generative AI position (grey area), the jump just made by NCP (orange) and the number of jumps that would have to be made to satisfy Hawkins’ AGI test (blue).

Before the weekend, the total was fifty-eight. Today it is fifty-seven.

All completely predictable. At least in terms of what is needed. The more difficult challenge, of course, concerns the question of timing. How quickly could the jumps be made is one question. How quickly should they be made is perhaps the more important one. Especially in light of the fact that we currently live in a race-to-AGI in which the winner looks like being the one that ignores safety the most. Perhaps, rather than waiting for seemingly ossified Government agencies to act, we should start writing some patent applications and use them to try and throttle the recklessness a little?

“How wonderful that we have met with a paradox. Now we have some hope of making progress.”
Niels Bohr

William Blake’s earlier version of Bohr’s quote was, “Without contraries is no progression.” But there is another line, from William Blake, that has been rattling around in my head while thinking about one of the most interesting challenges currently being posed to artificial intelligence:

“There is no other God, than that God who is the intellectual fountain of humanity.”

It feels like an appropriately Blakean way of saying something rather important. Perhaps the greatest breakthroughs do not come from intelligence simply knowing more than everyone else. Perhaps they come when intelligence is able to see something differently. To escape psychological inertia, and to make cognitive leaps.

Demis Hassabis has suggested what might be called an Einstein Test for AI. Can a machine make the kind of creative leap that transformed our understanding of the universe in the hands of Albert Einstein? It is a fascinating question. But it prompts another. Before asking whether AI can become another Einstein, might it be worth asking whether we can understand, at least in part, how Einstein-like leaps happen? And if we could identify some of the cognitive transformations involved, could we teach an AI to use them deliberately? That question leads to a rather intriguing thought experiment.

The Pre-TRIZ Einstein Experiment

Imagine that we could freeze history in 1905. Einstein has just published his Special Theory of Relativity. The world now has a radically new understanding of space and time. The speed of light is invariant. Space and time are no longer the absolute background assumed by Newtonian physics. But General Relativity does not yet exist. Einstein will spend the next decade trying to solve the problem of gravity.

Now imagine giving the scientists of 1905 something that did not yet exist. Not knowledge from the future. Not curved spacetime. Not the equivalence principle. Not Einstein’s field equations. Instead, imagine giving them a systematic map of the inventive transformations that humanity had already used successfully before 1905.

That map has a name today. TRIZ.

A map of inventive thought

TRIZ emerged from the work of the Soviet engineer, inventor and researcher Genrich Altshuller. He began with a deceptively simple question: ‘do successful inventions have anything in common? His research eventually suggested that, despite the enormous diversity of technologies and industries, inventors repeatedly used a relatively small number of recurring conceptual moves. These became the famous 40 Inventive Principles.

Altshuller started his research in the wake of the Second World War, and so clearly the 40 Principles as we know them today did not exist in 1905. But the inventions from which such Principles could be extracted already did. Humanity had already discovered the moves. It simply had not yet organised them into a systematic library. So our experiment is not quite as absurd as it first sounds. We are not giving 1905 the answers from the future. We are giving 1905 a better understanding of the patterns contained in its own past.

But first we need a problem. And TRIZ begins with one of the things Bohr found so exciting. A contradiction.

Gravity must act at a distance… but not too quickly

By 1905, Newtonian gravity remained spectacularly successful.

It explained the motion of planets. It described falling bodies. For more than two centuries, it had provided one of humanity’s most powerful descriptions of the physical universe. But Newton’s gravity carried an uncomfortable assumption. Gravity appeared to act across distance instantaneously. Move a massive object and, in the Newtonian picture, its gravitational influence is reflected everywhere immediately.

Then came Einstein’s Special Relativity. One of its central implications was that physical signals and influences could not propagate faster than the speed of light.

And suddenly we have a contradiction.

We want gravity to retain its successful ability to influence objects across enormous distances… but we must not allow physical influence to travel instantaneously.

Or, more provocatively:

Gravity must act at a distance… but it must not act at a distance too quickly.

This is precisely the kind of situation that TRIZ finds interesting. Neither side of the contradiction is obviously wrong. Newtonian gravity works. Special Relativity works.

The difficulty is that the two successful descriptions cannot simply be placed together without creating a problem.

That is where progress often begins.

Step One: Freeze history

So let us establish the rules. The year is 1905.

We are allowed everything that was scientifically known at that point.

We are allowed every invention made by humanity before that date.

We are allowed the accumulated evidence of successful problem solving contained in the history of technology.

But we are not allowed to cheat.

No curved spacetime.

No General Relativity.

No Einstein field equations.

No knowledge of what Einstein will discover during the next ten years.

No answer may be smuggled backwards through history.

Instead, we have only a contradiction.

How can gravity influence across distance without violating the relativistic constraints imposed by the speed of light?

Step Two: Ask who had already solved similar problems

This is where the experiment becomes interesting.

Translated crudely into TRIZ terminology, we have a conflict involving distance and speed.

The modern Contradiction Matrix is the result of accumulated research into which Inventive Principles have historically been used to resolve particular kinds of conflict.

For the distance-versus-speed contradiction, the most highly ranked recommendations include three particularly intriguing Principles:

13 – The Other Way Round

17 – Another Dimension

14 – Spheroidality/Curvature

The Matrix itself obviously did not exist in 1905. But here is the important question, ‘had humanity already used these cognitive moves to solve problems before Einstein needed them? The answer is plainly yes.

Turn the problem around

Consider the moving sidewalk. The conventional way of helping someone travel a distance faster might be to make the person move faster. But the moving sidewalk reverses the relationship. Keep the traveller relatively still. Move the world beneath them instead. That is Principle 13: The Other Way Round. Change what moves and what remains stationary. Reverse the conventional relationship between system and environment.

Leave the existing dimension

Consider the spiral staircase. The problem is one of distance, but the available footprint is limited. The obvious solution – extend the route – consumes more space and therefore requires either more time or more speed to get from bottom to top. The inventive solution is to leave the plane. ‘Use another dimension’. The spiral staircase allows substantial travel distance to be accommodated within a compact footprint. That is Principle 17. If the problem cannot be solved within the existing dimensional arrangement, change the arrangement.

Try curvature

And then there is perhaps the oldest and simplest example of all. The wheel. Dragging a load across a surface creates resistance. The solution is not simply to drag harder. It is to transform linear motion. Introduce rotation. Introduce curvature. That is Principle 14. And it is difficult to imagine a more ancient demonstration of the fact that sometimes an apparently linear problem becomes soluble only when we stop thinking in straight lines.

Three cognitive provocations

Now return to 1905. We still do not know the answer. But we now have three historically demonstrated cognitive transformations. And our 1905-TRIZ allows us to turn them into questions.

Principle 13: The Other Way Round

Change the relationship between observer and phenomenon.

What happens if we reverse the conventional viewpoint?

What does gravity look like from inside the system experiencing it?

What happens if the observer is falling?

This is not yet the equivalence principle.

But it is a route into precisely the kind of thought experiment that made the equivalence principle possible.

Principle 17: Another Dimension

What if the problem cannot be solved within the existing dimensional framework?

Are we describing the universe using the wrong arrangement of dimensions?

Could the difficulty disappear if space and time are treated differently?

Again, no answer has been supplied.

But an entirely new territory has been opened for exploration.

Principle 14: Curvature

And then comes the most provocative transformation.

What if we stop assuming flatness?

Must the geometry within which gravity operates be flat?

What happens if curvature is introduced?

And then the question that, in 1905, would have sounded extraordinary: What if space itself can be curved?

We have not rediscovered General Relativity. Einstein would still have had an enormous amount of work to do. But something important has happened. We have entered the conceptual territory in which General Relativity becomes thinkable.

And perhaps that is the real point of the Einstein Test.

The purpose is not to produce Einstein

The Pre-TRIZ Einstein Experiment cannot prove that TRIZ would have produced General Relativity. That would be an absurd claim. Einstein brought extraordinary scientific judgement, mathematical capability, persistence and imagination to the problem. He also had to distinguish between a provocative thought experiment and a description of physical reality. TRIZ cannot tell us which of our ideas nature will permit. But it can help with an earlier and equally important problem. Where should we look?

The experiment might therefore support a much more modest – but potentially profound – proposition… Systematic inventive heuristics may be capable of generating the kinds of conceptual provocations from which revolutionary scientific insights emerge.

That is rather different from saying that creativity can be reduced to an algorithm. It says that some of the transformations used in creative leaps may be recognisable, repeatable and deliberately invoked. And that brings us back to AI.

The question before the Einstein Test

If Hassabis’ Einstein Test asks: Can AI make a genuinely novel conceptual leap?

Perhaps there is a preceding question.

Can we identify the cognitive transformations that made Einstein capable of asking questions nobody else had thought to ask—and teach an AI to use them deliberately?

TRIZ represents one attempt to answer precisely that question.

Altshuller did not study Einstein. He studied invention. His remarkable proposition was that the accumulated history of human ingenuity contained recurring patterns. Successful inventors did not all think identically. But their solutions repeatedly involved similar transformations. Separate. Invert. Combine. Move into another dimension. Introduce curvature. Use available resources. Change the relationship between the system and its environment. And many others. The provocative possibility is that these are not merely engineering tricks. They are rather elements of a much more general library of cognitive moves. Moves that can be applied whenever a successful model encounters a contradiction it cannot resolve.

Which leads to the much bigger question, Why wait for another Einstein?

The Einstein Test asks, in effect, can AI produce one Einstein-level breakthrough? But if the cognitive transformations underlying major breakthroughs can be identified from the accumulated history of invention, why wait? Why wait for another Einstein to emerge? Why not systematically apply those transformations to the unresolved contradictions that science can already see?

After all, science is full of them. Successful theories that do not comfortably fit together. Measurements that refuse to behave as expected. Models that explain almost everything except the inconvenient thing that they cannot explain at all. The existence of such contradictions is usually treated as evidence of a problem. Bohr saw something else. “How wonderful that we have met with a paradox. Now we have some hope of making progress.” Perhaps every major unresolved contradiction in science should be treated in the same way. Not as a monument to ignorance. But as an invitation. An invitation to search.

The bigger destination

Here, perhaps, is where the Pre-TRIZ Einstein Experiment becomes something more than a historical curiosity.

Even before Einstein knew the answer, the accumulated history of human invention already contained cognitive transformations capable of pointing towards it.

If that proposition is even partly true, its implications are enormous. Today we possess not only the inventive history available in 1905. We have more than a century of additional science and technology. We have millions of documented inventive cases. We have systematic knowledge extracted from those cases. And we increasingly have AI capable of maintaining, searching and connecting conceptual spaces far larger than any individual human can hold in their head. Perhaps the most useful role for AI is therefore not to sit in isolation waiting for a mysterious moment of artificial genius. Perhaps it is to become a partner in a systematic process.

Identify the contradiction.

Search the accumulated history of successful transformations.

Find analogous conflicts.

Generate cognitive provocations.

Combine them.

Explore the resulting conceptual territory.

And then allow human scientists to bring the things AI does not possess… judgement, purpose, context, intuition and, perhaps above all, the ability to recognise what is genuinely important.

The question is no longer simply, Can AI become Einstein?

The more interesting question is, Can AI help thousands of scientists explore the conceptual territory from which the next Einsteins will emerge?

And perhaps there is an even bigger possibility. If Altshuller was right that humanity’s history of invention contains a discoverable library of recurring cognitive  transformations, then that library should not be confined to engineering or business or IT problems. It should be pointed at the contradictions that are still holding science back. The great unanswered questions. The theories that work beautifully… until they collide with another theory that also works beautifully. The paradoxes.

Because perhaps Bohr was right.

Perhaps the moment we encounter a contradiction is not the moment progress stops.

Perhaps it is the moment when progress finally has somewhere to begin.

And if we can systematically identify the cognitive moves that have helped humanity escape contradictions in the past, perhaps we do not have to wait for another Einstein to arrive.

Perhaps we can start looking now.

I’ve been reading John Higgs’s 2021 book, William Blake versus The World, and finding it enormously helpful. Blake has always been one of those figures I have admired more than understood. That is partly because he was writing more than two centuries ago, in a world sufficiently different from ours that it is easy to lose sight of what he was reacting against.

Higgs has helped me particularly with Jerusalem.

Like most English people, I have heard the poem – or, more accurately, Hubert Parry’s beautiful 1916 musical setting of Blake’s words – countless times. And like many people, I have always been slightly mystified by its status as something approaching an unofficial English national anthem.

Why Jerusalem?

John Higgs’s interpretation has helped me see it in a completely different way.

For many years, I have drawn a rather crude two-by-two matrix contrasting True and Correct. By “Correct”, I mean the objective world: facts, evidence, measurement, science and the material reality that emerged so powerfully from the Enlightenment. By “True”, I mean something rather different: the subjective world of meaning, mythos, imagination, spirit and those things that cannot necessarily be measured but nevertheless matter profoundly to human beings.

As with all goo 2×2 matrices, the ideal place to be is the top-right corner, in this case the place where True and Correct are both present.

And, reading Higgs, I suddenly realised that this is remarkably close to what Blake appears to have meant by Jerusalem.

Blake was living through the beginnings of the Industrial Revolution and the continuing consequences of the Enlightenment. Humanity was becoming increasingly successful at understanding and manipulating the material world. Science was telling us more and more about how things worked. Industry was transforming the physical landscape. Reason and measurement were becoming dominant ways of understanding reality.

All good things. Except, in Blake’s view, something important was being lost. The material was becoming separated from the immaterial. The measurable from the meaningful. The Correct from the True.

Blake’s Jerusalem, as I now understand it, was not simply a religious place. It was a metaphor for a world in which these things were reunited. In my crude matrix, it is the top-right corner. High Correct. High True. A place where we understand the objective world without losing our connection to meaning, imagination and spirit. A place where science and art do not compete. Where reason and imagination are not enemies. Where the material and the immaterial belong together.

That sounds rather more interesting than the version of Jerusalem I had previously carried around in my head.

And then there are Blake’s famous “dark Satanic Mills”. Whatever the precise historical referents Blake intended – and there is plenty of debate about that – Higgs’s contextualisation makes the broader idea easier to understand. The “mills” represent, at least metaphorically, a world in which the material has become dominant. A world of machinery, industry and reductionism. A world that is increasingly capable of manipulating reality but is in danger of losing sight of why.

In my matrix, that looks like the bottom-right corner: High Correct. Low True. We know how things work. But we no longer know what they mean. We have facts without wisdom. Information without purpose. Technology without imagination.

And Blake’s criticism was not confined to industrial machinery. He was equally suspicious of institutions of learning – especially Oxford and Cambridge – when they appeared to him to have reduced the world to what could be rationally analysed and categorised.

The irony, of course, is that we are still remarkably good at building that bottom-right corner. Perhaps better than ever.

Blake’s opposite to Jerusalem was Babylon. Again, I don’t want to turn this into a discussion about religion, because I think the metaphor works perfectly well without one. If Jerusalem represents the place where meaning and reality are reunited, Babylon represents its opposite: a world in which that connection has been lost altogether. In my matrix, I see it as the bottom-left corner: Low Correct. Low True. A place detached from objective reality, but without replacing it with genuine meaning. Not truth. Not correctness. Just confusion.

Jerusalem and Babylon, then, become opposite poles in a much broader human problem. How do we avoid losing either the objective reality of the world or the subjective truths that make life meaningful?

Which brings me back to my original question. Why has Jerusalem become something approaching an unofficial English national anthem? Because if Blake meant what I now think he meant, it is a rather odd choice. The England Blake imagined was not the England that existed. It was the England he hoped might one day be built. “Jerusalem” was not a celebration of the status quo. It was an instruction. A challenge. A destination. And, as far as I can see, we are not consciously trying to build it. We continue to separate science from art. Facts from meaning. Technology from wisdom. The measurable from the meaningful. We are extraordinarily good at the Correct. AI is even better. But both are much less good at the True.

And yet, when Parry’s music begins and thousands of people stand and sing about building Jerusalem “in England’s green and pleasant land”, something clearly happens. Perhaps most people singing it have no idea what Blake was actually proposing. Perhaps I didn’t either. But perhaps that doesn’t matter. Perhaps there is something subliminal in the appeal. Perhaps, underneath all the flags, nostalgia and ceremonial occasions, people are responding to something deeper.

Perhaps they are singing about a place they cannot quite describe. A place where the things we have separated might somehow be put back together. A place where we don’t have to choose between being Correct and being True.

Perhaps that is why Jerusalem still works. And perhaps the more interesting question isn’t why English people treat Jerusalem as a national anthem, but rather, when thousands of people sing it, are we – without quite knowing it – singing about the world we still want to build?

I live in an old Victorian house. Which has lots of benefits, but also a few annoying quirks. Most of which usually involve water in places you don’t ideally want water. The beginning of this year saw the arrival of a new leak above the kitchen window. We’d had what felt like a whole month of rain leading up to the start of the leak, so my troubleshooting psychological inertia took me outside and up a ladder to clear out the guttering. That didn’t work, so then I started looking for cracks and gaps in the walls and eaves. There were a couple of unlikely looking cracks. I tried a temporary silicon filler. That didn’t work either. At which point my better half, having now seen the stain on the kitchen ceiling grow to the size of an expensive redecoration job, the work surfaces covered in buckets, and, the last straw, water dripping into the light-switch, decided we needed professional help. Somewhat amazingly, Devon roofers usually being unwilling to climb onto roofs in Feburary in the rain, someone turned up the following morning. He couldn’t find anything wrong. So then we convinced another one to come. He couldn’t find anything wrong either. As he left, he suggested that perhaps the water was coming from inside the house. I told him that I’d looked and there were absolutely no pipes anywhere above the kitchen window. I looked again. It was impossible. But now there was no other viable alternative. So I tried turning the water off at the mains. Within minutes, much to my surprise, the sound of drops falling from the ceiling plopping into the line of buckets stopped. I looked harder for hidden pipework. Nothing. I then attempted to convince better half that maybe we could live with only turning the mains back on when we needed water. This didn’t go down well. I sort of agreed, the stopcock being several yards away from the house at the bottom of an arm-length hole in the ground inhabited by what always seems like half the spider population of the county. It was time to call in the professionals again. This time a plumber. He couldn’t find any pipework in the vicinity either. So he said the only thing we could do now was remove a part of the kitchen ceiling and see what we could see above it.

When he’d finished that task, the kitchen was covered in plaster dust and buckets and there was still no sign of the source of the leak. The only new clue was a damp ceiling joist. Meaning the leak must be upstairs in the better half’s office. The general rule in the house is that only she is allowed in her office. Now there’s a plumber in the room, re-arranging all the furniture, lifting carpet and then a couple of floorboards. Still nothing. Getting a little desperate now, he pulls away the skirting board. And finally, there it is, the dripping mains pipe.

At this point, I should perhaps also add to the story the fact that the people we bought the house from fifteen years ago turned out to be DIY-nuts. And more to the point not very good ones. If a job was worth doing, in Captain Bodge’s eyes, it was worth doing badly. Despite re-wiring most of the house after we moved in, there are still one or two ghostly lighting mysteries that have never been solved. And now, it turns out that the good Captain had at some point taken it upon himself to re-route the pipework from the mains into the house by feeding the pipe vertically up the inside of the wall, into the wall of the now precious office and through to the end wall of the office into the rest of the house. Don’t ask me where precisely, because I still don’t exactly know where it goes after it passes behind the office skirting board (probably because I’m still slightly scared at the sight of the Captain Bodge tie-wrap connecting the pipe to a passing electric cable conduit – see photo).

Meanwhile, now we’ve found the leak, the plumber looks at the 4” square cavity through which the leaky pipe is passing, gets down on his hands and knees, head to the gound, looks at the three (thanks, Captain Bodge) transition joints, scratches his head and let’s out a long sigh. No doubt at the unlikely prospect of being able to do what in effect looked like the plumbing version of keyhole surgery. ‘I’m getting too old for this’, he said as I watched him try and hacksaw off the offending joint and then, worse, install a new compression fitting into a space that had room for either the fitting or his hand, but not both. By way of what I hope is some kind of consolation, I tell him that I’ll re-install the skirting board and return the office to something like its original state. And I’ll fix the now very blown-looking light switch in the kitchen.

Six months later, we’ve finally managed to get a builder to come and repair the hole in the kitchen ceiling.

The point of this story is that during these six months it feels like life has decided to torture me with lots of images and stories of how, soon, we’ll have plumbing robots that will come and sort these kinds of leak problem out.

I understand that the AI and robot-hungry tech bros have a vested interest in painting a bright rosy picture of a utopian future where robots do all our manual work for us at the drop of a hat, but sometimes their level of naivety is so astonishingly high that I’m now convinced the primary existential threat to humanity is their apparent lack of understanding of the absolute basics of how new things get done. It’s one thing to win Nobel prizes for developing super-cunning protein folding algorithms that will create lots of exciting new proteins, quite another to put any of those proteins into our mouths. Similarly, it is one thing to train a robot to change a u-bend in a shiny new laboratory sink, and a very different thing to expect that robot to come and find and fix my leak. At this point in history, we know how to train robots to do very specific tasks. We give them lots of training data, and tightly bound the variability of the task. We can see the results of this design philosophy in the masses of industrial robotic solutions designed to operate 24 hours a day on highly repetitive jobs in very tightly controlled environments. Specialists know how to train specialists. Especially robot specialists.

Designing generalists, on the other hand, requires a completely different design philosophy. One that does not exist at the moment. Humans aren’t great at doing repetitive jobs. We’re two-9s reliable at best. AI and robots will beat us every time on boring repetitive tasks. What humans are great at is being creative generalists, capable of rapidly adapting to previously unknown situations and circumstances.

In the aerospace industry it has long been known that a two-9s pilot is not good enough to fly a plane demanding 12-9s and beyond levels of passenger safety. That’s why the automatic pilot, George, flies the plane for 95% or more of every flight. Another of the reasons planes are easily the safest form of transport is because planes have a very tightly constrained flight envelope. Don’t fly higher than this, don’t fly faster than that, don’t fly slower than that, don’t take-off if you weigh more than this. Stay within the envelope and George will get you where you need to go. On the other hand, get a simultaneous Canada-goose-strike in both your engines during take-off and George is completely out of his depth. Now you need Sully.

Same thing with my Victorian, Captain Bodge leak. The only time I’ll be inviting a robot in to fix that kind of problem will be the day the world knows how to design twelve-9s reliable generalist robots. The robot plumber that’s also capable of finding hidden pipes at a location its never seen before, making holes in the ceiling, removing skirting boards, doing keyhole pipe repair, cleaning up after itself, and re-assuring my better half that she’ll get her office back exactly the way it was before.

It will happen one day. But not in this AI Hype Cycle. Or the next. Or the one after that. In other words, when Satya Nadella suggested the world was ‘one innovation away’ from AGI, he probably meant ten. Maybe twelve.

Dick Fosbury changed the high jump. I’ve mentioned him several times over the years, Usually when trying to describe how universal s-curves are. How all systems hit limits and how, when they do, the world needs people like Dick Fosbury to come along and solve a contradiction or two.

Before Fosbury, high jumpers generally went over the bar facing downwards or sideways. Fosbury did something different. He turned around. He approached the bar on a curve, planted his right foot, and went over backwards. The result became known as the Fosbury Flop. At first, his coach tried to stop him, later everyone mocked him. And then, under the 1968 Olympic spotlight he changed the high-jump forever.

His Principle 13, The Other Way Around, solution to the how-to-jump-higher problem is the thing I’ve usually focused on. But one of the lovely things about mavericks like Fosbury is the deeper you look, the more you realise he’s not just solving one contradiction, he’s challenging them everywhere. Here’s my new favourite:

Before Fosbury, a conventional high jump was, fundamentally, about generating vertical force. Run. Plant. Jump. The harder and more efficiently the athlete can convert horizontal momentum into vertical lift, the higher they can go.

But Fosbury’s new other-way-around technique added another requirement. He didn’t just need to go up. He needed to turn around. More specifically, his body had to acquire the rotation required to take him over the bar backwards.

So now the take-off contained a contradiction. He needed maximum vertical lift, and he also needed to generate rotation. In TRIZ Contradiction Matrix terms Fosbury needed lift force and to change his orientation angle relative to the bar. Here’s what that conflict looks like when mapped onto the Matrix:

The first part of his solution involved (Principle 2) separating the two functions. For Fosbury that meant giving his left leg the task of initiating the rotational movement, and then having is right leg providing the vertical lift force. The left leg providing the penultimate step, and the right the final, launching step. Easy when you know how.

But then comes a much more subtle part of the story. If his left leg is tasked with the performing the rotation job, he needed a different kind of grip on the track to that required for his right leg. For rotation he needed a firm, non-slip interaction with the ground. And for lift his right he needed to support the rapidly moving body and generate the vertical impulse required to lift the jumper over the bar with as little ground resistance as possible.

How to achieve those two different requirements?

Answer: Asymmetry. Two different requirements, two different shoes (did you notice them in the photo at the top of the article?). For his left foot he wore a classic spiked running shoe, and on his right he wore a shoe with a smooth sole.

What I love most about this solution is it demonstrates escape from a classic piece of psychological inertia. Every shoe-shop on the planet sells pairs of identical shoes. Two feet. Two shoes. One design. Symmetry. Humans love symmetry. We default to symmetry. Companies sell symmetry. Consumers buy it.

But symmetry only makes sense if the required functions are symmetrical. Principle 4 is a reminder that every time we default to symmetry there’s a strong chance we’ve missed an opportunity.

An opportunity that, in The Wizard Of Foz’s case was likely the difference between Olympic gold-medal winning fame and a soon to be forgotten fool wearing odd shoes.

The Fosbury Flop changed high jumping by challenging an assumption about how the human body should go over a bar. The mismatched shoes challenge a smaller assumption. But perhaps a more transferable one. Whenever we see two things that have been designed identically, it may be worth asking whether they actually perform the same functions. If the answer is no, symmetry is no longer an advantage and its time to roll out Principle 4.

Capitalism is an extraordinarily powerful optimisation system. Give it a target and enough freedom to pursue that target and, sooner or later, somebody will find a better way of getting there. That has been the source of much of its success. It is also becoming the source of some of its problems. Because the obvious question is, what, exactly, have we asked capitalism to optimise? The answer, for the most part, is also obvious. Profit.

There is nothing inherently wrong with that. Profit provides an essential signal. It tells us that somebody, somewhere, values what we are doing sufficiently to exchange resources for it. It rewards efficiency. It encourages experimentation. It enables investment in future ideas. And, importantly, it allows a vast number of individual decisions to be made without requiring a central planner to decide what everyone should do.

That freedom has generated extraordinary prosperity. But as we approach the top of an S-curve, the same optimisation mechanisms that helped generate progress can begin to reveal their unintended consequences. If a company can increase its profits by improving human flourishing, that is excellent. If another can increase its profits by diminishing human flourishing while transferring the costs elsewhere, that too is currently a perfectly viable business model. And therein lies the problem.

Perhaps capitalism is not malfunctioning. Perhaps it is doing exactly what we have asked it to do.

The Wrong Feedback Loop

Consider a product that generates substantial profits for its producer while simultaneously creating costs elsewhere. Those costs might appear as:

• poorer physical health;
• addiction;
• mental ill-health;
• environmental damage;
• biodiversity loss;
• reduced autonomy;
• wasted resources;
• social fragmentation;
• or burdens transferred to future generations.

The producer receives the profit. Society absorbs the cost. Economists have, of course, had a name for this problem for a very long time: externalities. But perhaps the challenge now is becoming broader. We are increasingly capable of recognising that some activities don’t simply create a measurable environmental cost or health cost. They influence the overall direction in which society is travelling. Some increase our capacity to flourish. Others diminish it. And some do both.

Which suggests that perhaps we need a new feedback mechanism. Not one based on prohibition. Not one in which a central authority decides which products people are allowed to buy. And not one in which every undesirable consequence generates another layer of regulation. Instead: Keep the freedom. Change the feedback.

A Flourishing Economy

Imagine a taxation system designed around a simple question: Does this activity tend to move society towards or away from human flourishing? The answer would not be binary. Nothing would simply be labelled Good or Bad. Instead, every activity would occupy a position on a spectrum. At one end might sit activities that generate significant and demonstrable harm:

• highly addictive products;
• business models designed to exploit addiction or vulnerability;
• environmentally destructive processes;
• systems that destroy biodiversity;
• products deliberately designed for premature obsolescence;
• activities that transfer substantial costs to society or future generations.

At the other end might sit activities that generate demonstrable benefits:

• regenerative agriculture;
• biodiversity-enhancing processes;
• preventive healthcare;
• durable and repairable products;
• clean energy;
• technologies that increase human capability;
• products that save time and increase autonomy;
• education;
• activities that build resilience;
• products and services that increase meaning, connection and participation.

Between the two would sit almost everything else. And the taxation system would respond accordingly. The further an activity moved in the direction of diminishing flourishing, the greater its contribution back to society should be. The further it moved in the direction of increasing flourishing, the greater the tax relief, rebate or other economic advantage it could receive.

Well, almost. The simple answer to any kind of complex problem like human flourishing is almost inevitably wrong. Far more effective, if we instead chose to embrace the complexity, we should not simply tax the position. We should tax the trajectory…

Tax the Trajectory

Imagine two companies. Both currently manufacture products that sit on the negative side of the flourishing spectrum. Company A is happy where it is. Its business model depends upon maintaining the status quo. Company B is investing heavily in reducing the harmful consequences of its products. It is redesigning them. Reformulating them. Finding less damaging materials. Reducing dependence. Repairing environmental consequences.

Under a conventional tax system, the two companies will likely be treated identically.

Under a flourishing-based system, their trajectories would be different. Company A is remaining stationary. Company B is moving.

The system, therefore, should recognise that. Indeed, perhaps an organisation’s tax position should depend upon both: Where are you now? and: Which direction are you travelling?

This changes the nature of the game. The objective is no longer to divide the economy into saints and sinners. The objective is to create an incentive for movement. A company currently causing harm is not condemned to permanent punishment. It has a route towards a more favourable future. Conversely, a company that currently generates positive outcomes should not receive permanent immunity. If the evidence changes, so should its position. This is important because flourishing itself is not static. Nor are our attempts to understand it.

Flourishing Vectors

Perhaps the most useful way to think about this is not as a single flourishing score, but as a flourishing vector. An activity may have effects in several directions simultaneously. For example, a product might:

• improve physical health;
• reduce autonomy through dependence;
• save time;
• create environmental damage;
• generate social connection;
• and impose future costs.

What is its score? The answer cannot simply be found by asking whether the product is “good” or “bad”. We need to understand its direction and magnitude across several dimensions. A preliminary flourishing vector might include:

• Health
• Autonomy
• Capability
• Meaning
• Relationships and social connection
• Resilience
• Environmental regeneration
• Intergenerational wellbeing

An organisation’s position would therefore not be determined by one simplistic judgement. It would be based on evidence concerning the net direction of travel.

This would also make the system capable of learning.

An activity initially believed to be beneficial may later reveal harmful unintended consequences. Another initially considered problematic may be redesigned into something overwhelmingly beneficial. The vector changes. The trajectory changes.

The taxation changes. No activity needs to be banned. No category needs to be permanently condemned. The system simply updates its feedback.

Carrots More Than Sticks

The most important characteristic of such a system, however, should be its bias towards encouragement rather than punishment. The objective is not to create an ever more sophisticated system for taxing undesirable behaviour. The objective is to make desirable innovation increasingly attractive. That means carrots more than sticks.

Taxation should certainly become progressively heavier as demonstrable harm increases. Otherwise the system fails to deal with activities whose profits depend upon transferring costs elsewhere.

But the greater opportunity lies at the other end of the spectrum. What if an entrepreneur knew that solving a significant societal problem would not merely create a market opportunity, but would also place their business on an increasingly favourable tax trajectory?

What if investors could see ten years ahead and recognise that some activities were becoming progressively less economically attractive while others were receiving progressively stronger incentives?

What if companies were given ample warning that the system’s assessment was changing?

The result would not be an overnight shock. It would be a controllable change in direction. Capital would begin to flow. Innovation would begin to follow. The system would respond. Which, of course, is precisely what capitalism is rather good at doing.

Don’t Tax the Past. Signal the Future.

This suggests another important design principle. Any changes should be gradual and predictable. A company that has invested billions under one set of rules should not suddenly discover that the rules have changed overnight. That simply replaces market uncertainty with political uncertainty. A flourishing taxation system should therefore operate on long, clearly signalled trajectories.

Perhaps a Citizens’ Assembly determines that a particular activity is generating greater harm than previously understood. The response need not be, ‘your tax rate doubles next year’. Instead, the system might say, ‘based on the current evidence, your tax trajectory will progressively change over the next ten years unless the underlying flourishing vector changes’.

That gives everyone a choice. The company can:

• accept the future tax burden;
• innovate;
• redesign the product;
• reduce the harm;
• find a new business model;
• or invest somewhere else.

Investors receive the same signal. So do entrepreneurs. And the market remains free to decide how to respond. The system does not dictate the solution. It creates the conditions under which solutions become increasingly attractive.

Once again, the system decides…

But Who Decides What Flourishing Means?

And now we arrive at the most difficult question. Who gets to decide? Who determines whether one product increases human flourishing while another diminishes it? A government? Scientists? Economists? Philosophers? An algorithm?

None of these answers is particularly attractive on its own. Give the power exclusively to politicians and the system risks becoming an instrument of political ideology. Give it exclusively to scientists and we forget that flourishing involves values as well as measurement. Give it to economists and we risk reducing human wellbeing to what can be counted. Give it to algorithms and we merely conceal human value judgements behind mathematics.

So perhaps the answer is not to find the one group clever enough to decide. Perhaps the answer is to design another system…

A Four-Layer Feedback System

The model I find increasingly attractive looks something like this.

Layer 1: The Foundation

At the bottom sits a broad and deliberately difficult-to-change understanding of human flourishing. Not a detailed prescription for how people should live. A direction.

For example:

• health;
• autonomy;
• capability and opportunity;
• meaning and purpose;
• relationships and community;
• resilience;
• environmental sustainability;
• intergenerational wellbeing.

This is the equivalent of the system’s constitution. It should change slowly.

Layer 2: Measurement

The next layer belongs to evidence. Scientists, health researchers, ecologists, economists, psychologists and other relevant experts develop the best possible measures of the flourishing vectors. Their role is not to decide what society should value. Their role is to measure consequences. And, crucially, to update those measurements when new evidence emerges.

The system must be capable of admitting, ‘we thought this was beneficial. We were wrong’. Or, ‘we thought this was harmful. We now understand the situation differently’. That is not a failure. That is the feedback working.

Layer 3: The Citizens’ Assembly

The third layer is where society makes its value judgements. A rolling, continuously refreshed and representative Citizens’ Assembly considers the evidence. Its task is not to run companies. It does not ban products. It does not decide which technologies should exist. Instead, it determines how the evidence should translate into future economic signals. How much incentive? How much disincentive? How quickly should the change occur? What unintended consequences might result?

The rolling nature of the Assembly is important. No permanent elite. No single electoral cycle. No assumption that today’s judgement must become tomorrow’s orthodoxy. The membership changes. The evidence changes. The decisions change. The feedback continues.

Layer 4: The Market

And then comes the most important layer. The market decides what to do. Companies innovate. Investors reallocate capital. Entrepreneurs spot opportunities.

Consumers remain free to choose. Nobody needs to ban the product. Nobody needs to prescribe the solution. The economic landscape simply begins to reflect something that it currently reflects only imperfectly: the consequences of success.

The Real Contradiction

At the heart of all this sits a familiar contradiction. We want the extraordinary innovative power that economic freedom can generate. But we do not want unlimited freedom to damage the conditions upon which everyone else’s flourishing depends.

Traditionally, we try to resolve this contradiction through regulation. More harm leads to more rules. More rules lead to more loopholes. More loopholes lead to more rules.

Eventually, innovation and regulation begin an arms race.

Perhaps there is another way. Don’t remove the freedom. Change the feedback.

Make the system increasingly rewarding for those who move towards flourishing.

Make it progressively more expensive to profit from moving away from it. But always leave the route open. Always allow innovation. Always allow a company to change direction. And always recognise that our understanding of flourishing may itself need to change.

The Top of the S-Curve

Capitalism has been spectacularly successful. But perhaps some of its greatest successes are now revealing contradictions that were less visible during the steep growth phase. We have become extraordinarily good at producing. But not necessarily at distinguishing production from progress. We can make products more efficiently than ever. But efficiency at producing the wrong outcome is not progress.

We can optimise engagement. But engagement is not the same thing as meaning.

We can extend treatment. But treatment is not always the same thing as health.

We can increase consumption. But consumption is not necessarily flourishing.

Perhaps this is what happens when we reach the top of an S-curve. The old optimisation target has delivered most of what it can. The next leap requires a new target. Not the abandonment of capitalism. Not central planning. Not prohibition. A new feedback loop.

Who Decides?

The honest answer is that nobody should decide alone. That may be the most important design principle of all. The problem is too complex for government to solve. Too value-laden for science alone to solve. Too important to leave entirely to markets. And too dynamic to be captured in a permanent set of rules.

So perhaps the answer is another self-correcting system. A broad societal direction.

Expert measurement. Citizens’ judgement. Market freedom. And continuous feedback between all four.

We would still make mistakes. Of course we would. But the objective should not be to construct a perfect definition of human flourishing and impose it forever. That would be the opposite of flourishing.

The objective is to build a system capable of learning. A system capable of recognising unintended consequences. A system capable of changing direction.

A system that provides more carrots than sticks. And, perhaps most importantly, a system that does not ask us to choose between freedom and responsibility.

It asks us to design a better relationship between the two. The challenge is not to decide what everyone should do. The challenge is to create the conditions in which increasing human flourishing becomes the most attractive direction in which to go.

Don’t ban the behaviour. Don’t prescribe the solution. Tax the trajectory. And then let the system decide.

20 activities/products/services that tend to diminish flourishing

#	Product / service / activity	Why it tends to diminish flourishing
1	Tobacco and highly addictive nicotine products	Dependence and major health harms
2	Products deliberately engineered for harmful addiction	Transfers autonomy from the individual to the provider
3	Gambling products with high addiction/exploitation potential	Financial, psychological and family harm
4	Highly processed foods designed around overconsumption	Can exploit reward systems while undermining long-term health
5	Excessive added-sugar products	Significant health burden when consumption is chronically high
6	Ultra-processed food systems with poor nutritional value	Cheap calories, but often at long-term health cost
7	Alcohol products associated with substantial social and health harms	Costs extend beyond the individual consumer
8	Fossil-fuel products where lower-impact alternatives are viable	Climate, pollution and long-term systemic costs
9	Monoculture agriculture dependent on ecological simplification	Soil depletion, biodiversity loss and systemic fragility
10	High-pesticide agricultural systems	Ecological and potential human-health externalities
11	Products designed for premature obsolescence	Waste, resource depletion and forced consumption
12	Disposable products where durable alternatives are practical	Externalised environmental costs
13	Extractive business models dependent on depletion of natural capital	Creates present wealth by reducing future capability
14	Services that monetise harmful misinformation	Reduces informed autonomy and social trust
15	Digital products optimised primarily for compulsive engagement	Can capture attention without increasing wellbeing
16	Predatory lending and exploitative financial products	Monetise vulnerability rather than create capability
17	“Symptom management only” products where prevention is deliberately neglected	Potentially sustains demand rather than addressing root causes
18	Products that deliberately create dependence or lock-in	Reduce consumer freedom of movement
19	Ecologically destructive extraction and land-use practices	Damage resilience and impose costs on others and future generations
20	Products whose profitability depends on shifting significant hidden costs onto society	The meta-category: privatised benefit, socialised cost

20 activities/products/services that tend to increase flourishing

#	Product / service / activity	Why it tends to increase flourishing
1	Regenerative agriculture	Rebuilds soil, resilience and ecological capacity
2	Biodiversity-enhancing land and water management	Increases ecosystem resilience
3	Preventive healthcare	Avoids problems rather than merely responding to them
4	Root-cause medical and health interventions	Increases long-term capability and reduces recurring harm
5	Mental-health prevention and effective treatment	Supports agency, relationships and quality of life
6	Nutritious, minimally harmful food systems	Supports long-term physical capability
7	Clean energy and low-impact energy systems	Meets needs while reducing systemic externalities
8	Durable, repairable and upgradeable products	Deliver value with less forced replacement
9	Circular-economy products and services	Retain material value and reduce waste
10	Products that restore rather than merely reduce environmental damage	Creates net-positive effects
11	Education that increases genuine capability	Expands future autonomy and opportunity
12	Tools that increase human agency rather than dependence	Help people do more for themselves
13	Products and services that strengthen meaningful relationships	Build social capital and belonging
14	Housing and infrastructure that improve long-term community resilience	Creates enabling conditions for flourishing
15	Products that save people time without merely transferring work elsewhere	Creates capacity for other meaningful activity
16	Arts, culture and experiences that increase meaning	Flourishing is more than health and consumption
17	Technologies that augment rather than replace human capability	Increase what people are able to achieve
18	Open knowledge and genuinely useful information systems	Increase collective capability
19	Products that improve accessibility and inclusion	Allow more people to participate fully
20	Businesses that demonstrably create more social/ecological value than they consume	The positive meta-category: private success aligned with public benefit

When I was in my twenties I decided I would become a bit of a Francophile. Mainly wine related. Mainly Chateauneuf du Pape related. Because it was fashionable, and I thought I’d give that a go too, I also got sucked into the Beaujolais Nouveau game. For those that don’t know, the Beaujolais region of France came up with the idea of speed-wine making. Harvest the wine at the end of the summer, and then bottle it and ship it out to gullible consumers by the third Thursday of November. The first year I joined the game it tasted like cat-piss. I figured it was a bad year. The next year, fighting every red-wine-is-supposed-to-be-served-at-room-temperature instinct i possessed, I chilled the bottle to a lower temperature. It also tasted like cat-piss. I began to become suspicious. The third year I bought a bottle of Beaujolais Villages. I think it had been bottled the same year of my first Nouveau experience. It was an object lesson in recognising that some things take time. Sure, it’s possible to pour a bunch of chemicals into a bottle of wine and speed the maturing process, but why? If you’ve been making wine for hundreds of years and accepting that you need to store the wine for a couple of years before selling it, the inventory in effect costs you almost nothing. Not totally nothing, of course, and I suppose that’s where the accounting department comes along and says they know how to save the vineyard a bit of money. That’ll be the people tasked with knowing the cost of everything and the value of nothing. Last time I looked, 13.4 million bottles of Beaujolais Nouveau are sold each year. That’s something like 20% of the total grape harvest of the whole Beaujolais region. If that’s what the customer wants, I suppose, you’d be a fool to not satisfy the demand. If the customer demands cat-piss, give them cat piss. I’m not sure that counts as contributing to human flourishing though?

I mention this, because earlier this week I became aware of a distant connection who had invented an equivalent way to accelerate the process of ‘maturing’ whisky. The lack of ‘e’ in the word whiskey tells you he’s based in America. The invention was about a decade ago. My recent update revealed that he’s now selling enormous quantities of his product. Forget fifteen-year, twelve or ten year matured whiskey, his process needs a few weeks. Not that you’ll see that fact written on the bottle. Rather, the bottle has had some top-notch brand design work done on it. It looks like a very expensive bottle of whisky, and hence fits the classic form of the money-making powerhouse that is the US ‘food’ industry – great marketing, ultra-consistency, ultra-addictive, and lowest-possible-cost ingredients and processes. AKA also the opposite of human flourishing.     

I’ve not had an opportunity to taste the product. I don’t know, it might be amazing. But I’m not sure that’s the point. Rather like the scary statistic that 97% of listeners can’t tell whether a piece of music has been generated by AI or a human. The meaningless, it seems, beats the meaningful. When the Emperor’s New Clothes marketing fades, the price of 80proof brown liquid tends to zero. Johnnie Walker Green Label, meanwhile, wants to be expensive. In the short term, well marketed muzak beats artistic struggle. If the function is background noise, who cares? Ditto, if the function is inebriation and escape from a vapid existence, who cares? Either way, as a species, it feels like the slippery slide to idiocracy is rapidly turning into a cliff-edge. Gluttons for our meaningless doom.

These trends will bottom out eventually. I know that. I hope that. I hope we don’t all hit the rocks at the bottom of the cliff before the direction of travel reverses. We’ve been predicting an Age Of Meaning for some time now. An age where we collectively come to realise there are problems that shouldn’t be solved. That the distillers pouring twelve years of their love into a bottle of Laphroaig Islay single-malt Scotch will be fully appreciated again. That we collectively opt for flourishing. Sláinte.

(Predicted shift in flourishing – adapted from the 1%ers, How New Things Get Done’ book.)

I have to admit this one surprised me. Many years ago, I happened across one of those websites offering advice for solving some of life’s trivial problems. The trivial problem in question being the indent marks left in carpets after heavy furniture has been stood on it for a prolonged period of time. The solution involved placing an ice cube into the indent and leaving it to melt. Hey presto, the website claimed, tomorrow the indent will have disappeared.

Finally, this week, after moving a piece of extremely heavy furniture and seeing the four rather depressing indents it had left behind, I knew something would have to be done if I was going to avoid having to move the extremely heavy furniture back again. After exhausting all traditional remedy routes – fingernails, wire-brush and catnip (cat claws having had a significant effect elsewhere on the carpet, albeit not in a good way) – it felt like time for an experiment.

One that I figured would best be done by trying one ice-cube in one of the indents. So that, if the experiment went horribly wrong, I’d be able to place a plant pot or something equivalent over one bit of worse-than-before carpet rather than four.

There was an immediate problem. The cat thought the ice-cube was a cunning new game. Meaning that, when I returned to look at what was happening to the carpet an hour after placing the ice-cube in the first indent, the ice cube had magically moved itself to a completely different, non-indented part of the carpet. The cat was duly instructed on the ways of science, and the need to not tamper with experiments. This mainly involved bribery of a prime chicken breast nature.

And so to the following morning. A carpet with three indents. Here’s a photo of the two of them. Or rather, one of the non-ice-cubed indents and – no longer there – the indent that had been subject to the ice-cube remedy. If the indent had still been there, it would have been on the left-hand side of the photo. It no longer existed.

Time to sacrifice another three ice-cubes, and another kilogram of chicken breast. And also time to see what TRIZ might have to say about the problem and solution. A classic conflict: I want to get rid of the unsightly furniture-caused indents and I can’t do it because the weight of the furniture has placed too much pressure on the carpet fibres and ‘irretrievably’ compacted them. Here’s what the Contradiction Matrix had to say about how others had solved similar conflicts:

And there was the surprising bit. Inventive Principle 36, Phase Transition. Melting ice-cubes. Principle 36 is one of the least frequently used of the forty. But there it was. Telling me I should have listened all those many years ago when I first saw the dumb ice-cube trick. It wasn’t dumb, it was what the world’s smartest problem solvers did.

I can sense a whole new series of dumb-ancient-remedies-that-aren’t-dumb-at-all case studies on the horizon. Next up, rhubarb and my collection of burnt pans…