I keep digging. I keep revising that manuscript of mine – ‘Climbing the right hill – an evolutionary approach to the European market of electricity’ – in order to resubmit it to Applied Energy. Some of my readers might become slightly fed up with that thread. C’mon, man! How long do you mean to work on that revision? It is just an article! Yes, it is just an article, and I have that thing in me, those three mental characters: the curious ape, the happy bulldog, and the austere monk. The ape is curious, and it almost instinctively reaches for interesting things. My internal bulldog just loves digging out tasty pieces and biting into bones. The austere monk in me observes the intellectual mess, which the ape and the bulldog make together, and then he takes that big Ockham’s razor, from the recesses of his robe, and starts cutting bullshit out. When the three of those start dancing around a topic, it is a long path to follow, believe me.
In this update, I intend to structure the theoretical background of my paper. First, I restate the essential point of my own research, which I need and want to position in relation to other people’s views and research. I claim that energy-related policies, including those with environmental edge, should assume that whatever we do with energy, as a civilisation, is a by-product of actions purposefully oriented on other types of outcomes. Metaphorically, when I claim that a society should take the shift towards renewable energies as its chief goal, and take everything else as instrumental, is like saying that the chief goal of an individual should be to keep their blood sugar firmly at 80,00, whatever happens. What’s the best way to achieving it? Putting yourself in a clinic, under permanent intravenous nutrition, and stop experimenting with that thing people call ‘food’, ‘activity’, ‘important things to do’. Anyone wants to do it? Hardly anyone, I guess. The right level of blood sugar can be approximately achieved as balanced outcome of a proper lifestyle, and can serve as a gauge of whether our actual lifestyle is healthy.
Coming back from my nutritional metaphor to energy-related policies, there is no historical evidence that any human society has ever achieved any important change regarding the production of energy or its consumption, by explicitly stating ‘From now on, we want better energy management’. The biggest known shifts in our energy base happened as by-products of changes oriented on something else. In Europe, my home continent, we had three big changes. First, way back in the day, like starting from the 13th century, we harnessed the power of wind and that of water in, respectively, windmills and watermills. That served to provide kinetic energy to grind cereals into flour, which, in turn, served to feed a growing urban population. Windmills and watermills brought with them a silent revolution, which we are still wrapping our minds around. By the end of the 19th century, we started a massive shift towards fossil fuels. Why? Because we expected to drive Ferraris around, one day in the future? Not really. We just went terribly short on wood. People who claim that Europe should recreate its ‘ancestral’ forests deliberately ignore the fact that hardly anyone today knows what those ancestral forests should look like. Virtually all the forests we have today come from massive replantation which took place starting from the beginning of the 20th century. Yes, we have a bunch of 400-year-old oaks across the continent, but I dare reminding that one oak is not exactly a forest.
The civilisational change which I think is going on now, in our human civilisation, is the readjustment of social roles, and of the ways we create new social roles, in the presence of a radical demographic change: unprecedently high headcount of population, accompanied by just as unprecedently low rate of demographic growth. For hundreds of years, our civilisation has been evolving as two concurrent factories: the factory of food in the countryside, and the factory of new social roles in cities. Food comes the best when the headcount of humans immediately around is a low constant, and new social roles burgeon the best when humans interact abundantly, and therefore when they are tightly packed together in a limited space. The basic idea of our civilisation is to put most of the absolute demographic growth into cities and let ourselves invent new ways of being useful to each other, whilst keeping rural land as productive as possible.
That thing had worked for centuries. It had worked for humanity that had been relatively small in relation to available space and had been growing quickly into that space. That idea of separating the production of food from the creation of social roles and institutions was adapted precisely to that demographic pattern, which you can still find vestiges of in some developing countries, as well as in emerging markets, with urban population several dozens of times denser than the rural one, and cities that look like something effervescent. These cities grow bubbles out of themselves, and those bubbles burst just as quickly. My own trip to China showed me how cities can be truly alive, with layers and bubbles inside them. One is tempted to say these cities are something abnormal, as compared to the orderly, demographically balanced urban entities in developed countries. Still, historically, this is what cities are supposed to look like.
Now, something is changing. There is more of us on the planet than it has ever been but, at the same time, we experience unprecedently low rate of demographic growth. Whilst we apparently still manage to keep total urban land on the planet at a constant level (https://data.worldbank.org/indicator/AG.LND.TOTL.UR.K2 ), we struggle with keeping the surface of agricultural land up to our needs (https://data.worldbank.org/indicator/AG.LND.AGRI.ZS ). As in any system tilted out of balance, weird local phenomena start occurring, and the basic metrics pertinent to the production and consumption of energy show an interesting pattern. When I look at the percentage participation of renewable sources in the total consumption of energy (https://data.worldbank.org/indicator/EG.FEC.RNEW.ZS ), I see a bumpy cycle which looks like learning with experimentation. When I narrow down to the participation of renewables in the total consumption of electricity ( https://data.worldbank.org/indicator/EG.ELC.RNEW.ZS), what I see is a more pronounced trend upwards, with visible past experimentation. The use of nuclear power to generate electricity (https://data.worldbank.org/indicator/EG.ELC.NUCL.ZS) looks like a long-run experiment, which now is in its phase of winding down.
Now, two important trends come into my focus. Energy efficiency, defined as average real output per unit of energy use (https://data.worldbank.org/indicator/EG.GDP.PUSE.KO.PP.KD) quite unequivocal a trend upwards. Someone could say ‘Cool, we purposefully make ourselves energy efficient’. Still, when we care to have a look at the coefficient of energy consumed per person per year (https://data.worldbank.org/indicator/EG.USE.PCAP.KG.OE), a strong trend upwards appears, with some deep bumps in the past. When I put those two trends back to back, I conclude that what we really max out on is the real output of goods and services in our civilisation, and energy efficiency is just a means to that end.
It is a good moment to puncture an intellectual balloon. I can frequently see and hear people argue that maximizing real output, in any social entity or context, is a manifestation of stupid, baseless greed and blindness to the truly important stuff. Still, please consider the following line of logic. We, humans, interact with the natural environment, and interact with each other. When we interact with each other a lot, in highly dense networks of social relations, we reinforce each other’s learning, and start spinning the wheel of innovation and technological change. Abundant interaction with each other gives us new ideas for interacting with the natural environment.
Cities have peculiar properties. Firstly, by creating new social roles through intense social interaction, they create new products and services, and therefore new markets, connected in chains of value added. This is how the real output of goods and services in a society becomes a complex, multi-layered network of technologies, and this is how social structures become self-propelling businesses. The more complexity in social roles is created, the more products and services emerge, which brings the development in greater a number of markets. That, in turn, gives greater a real output, greater income per person, which incentivizes to create new social roles etc. This how social complexity creates the phenomenon called economic growth.
The phenomenon of economic growth, thus the quantitative growth in complex, networked technologies which emerge in relatively dense human settlements, has a few peculiar properties. You can’t see it, you can’t touch it, and yet you can immediately feel when its pace changes. Economic growth is among the most abstract concepts of social sciences, and yet living in a society with real economic growth at 5% per annum is like a different galaxy when compared to living in a place where real economic growth is actually a recession of -5%. The arithmetical difference is just 10 percentage points, around the top of something underlying which makes the base of 1. Still, lives in those two contexts are completely different. At +5% in real economic growth, starting a new business is generally a sensible idea, provided you have it nailed down with a business plan. At – 5% a year, i.e. in recession, the same business plan can be an elaborate way of committing economic and financial suicide. At +5%, political elections are usually won by people who just sell you the standard political bullshit, like ‘I will make your lives better’ claimed by a heavily indebted alcoholic with no real career of their own. At -5%, politics start being haunted by those sinister characters, who look and sound like evil spirits from our dreams and claim they ‘will restore order and social justice’.
The society which we consider today as normal is a society of positive real economic growth. All the institutions we are used to, such as healthcare systems, internal security, public administration, education – all that stuff works at least acceptably smoothly when complex, networked technologies of our society have demonstrable capacity to increase their real economic output. That ‘normal’ state of society is closely connected to the factories of social roles which we commonly call ‘cities’. Real economic growth happens when the amount of new social roles – fabricated through intense interactions between densely packed humans – is enough for the new humans coming around. Being professionally active means having a social role solid enough to participate in the redistribution of value added created in complex technological networks. It is both formal science and sort of accumulated wisdom in governance that we’d better have most of the adult, able bodied people in that state of professional activity. A small fringe of professionally inactive people is somehow healthy a margin of human energy free to be professionally activated, and when I say ‘small’, it is like no more than 5% of the adult population. Anything above becomes both a burden and a disruption to social cohesion. Too big a percentage of people with no clear, working social roles makes it increasingly difficult to make social interactions sufficiently abundant and complex to create enough new social roles for new people. This is why governments of this world attach keen importance to the accurate measurement of the phenomenon quantified as ‘unemployment’.
Those complex networks of technologies in our societies, which have the capacity to create social roles and generate economic growth, work their work properly when we can transact about them, i.e. when we have working markets for the final economic goods produced with those technologies, and for intermediate economic goods produced for them. It is as if the whole thing worked when we can buy and sell things. I was born in 1968, in a communist country, namely Poland, and I can tell you that in the absence of markets the whole mechanism just jams, progressively to a halt. Yes, markets are messy and capricious, and transactional prices can easily get out of hand, creating inflation, and yet markets give those little local incentives needed to get the most of human social roles. In the communist Poland, I remember people doing really strange things, like hoarding massive inventories of refrigerators or women’s underwear, just to create some speculative spin in an ad hoc, semi-legal or completely illegal market. It looks as if people needed to market and transact for real, amidst the theoretically perfectly planned society.
Anyway, economic growth is observable through big sets of transactions in product markets, and those transactions have two attributes: quantities and prices AKA Q an P. It is like Q*P = ∑qi*pi. When I have – well, when we have – that complex network of technologies functionally connected to a factory of social roles for new humans, that thing makes ∑qi*pi, thus a lot of local transactions with quantities qi, at prices pi. The economic growth I have been so vocal about in the last few paragraphs is the real growth, i.e. in quantity Q = ∑qi. On the long run, what I am interested in, and my government is interested in, is to reasonably max out on ∆ Q = ∆∑qi. Quantities change slowly and quite predictably, whilst prices tend to change quickly and, mostly on the short term, chaotically. Measuring accurately real economic growth involving kicking the ‘*pi’ component out of the equation and extracting just ∆ Q = ∆∑qi. Question: why bothering with the observation of Q*P = ∑qi*pi when the real thing we need is just ∆ Q = ∆∑qi? Answer: because there is no other way. Complex networks of technologies produce economic growth by creating increasing diversity in social roles in concurrence with increasing diversity in products and their respective markets. No genius has come up, so far, with a method to add up, directly, the volume of visits in hairdresser’s salons with the volume of electric vehicles made, and all that with the volume of energy consumed.
I have ventured myself far from the disciplined logic of revision in my paper, for resubmitting it. The logical flow required in this respect by Applied Energy is the following: introduction first, method and material next, theory follows, and calculations come after. The literature which I refer to in my writing needs to have two dimensions: longitudinal and lateral. Laterally, I divide other people’s publications into three basic groups: a) standpoints which I argue with b) methods and assumptions which I agree with and use to support my own reasoning, and c) viewpoints which sort of go elsewhere, and can be interesting openings into something even different from what I discuss. Longitudinally, the literature I cite needs, in the first place, to open up on the main points of my paper. This is ‘Introduction’. Publications which I cite here need to point at the utility of developing the line of research which I develop. They need to convey strong, general claims which sort of set my landmarks.
The section titled ‘Theory’ is supposed to provide the fine referencing of my method, so as to both support the logic thereof, and to open up on the detailed calculations I develop in the following section. Literature which I bring forth here should contain specific developments, both factual and methodological, something like a conceptual cobweb. In other words, ‘Introduction’ should be provocative, whilst ‘Theory’ transforms provocation into a structure.
Among the recent literature I am passing in review, three papers come forth as provocative enough for me to discuss them in the introduction of my article: Andreoni 2020[1], Koponen & Le Net 2021[2]. The first of the three on that list, namely the paper by professor Valeria Andreoni, well in the mainstream of the MuSIASEM methodology (Multi-scale Integrated Analysis of Societal and Ecosystem Metabolism), sets an important line of theoretical debate, namely the arguable imperative to focus energy-related policies, and economic policies in general, on two outcomes, namely on maximizing energy efficiency (i.e. maximizing the amount of real output per unit of energy consumption), and on minimizing cross sectional differences between countries as regards energy efficiency. Both postulates are based on the assumption that energy efficiency of national economies corresponds to the metabolic efficiency of living organisms, and that maxing out on both is an objective evolutionary purpose in both cases. My method has the same general foundations as MuSIASEM. I claim that societies can be studied similarly to living organisms.
At that point, I diverge from the MuSIASEM framework: instead of focusing on the metabolism of such organically approached societies, I pay attention to their collective cognitive processes, their collective intelligence. I claim that human societies are collectively intelligent structures, which learn by experimenting with many alternative versions of themselves whilst staying structurally coherent. From that assumption, I derive two further claims. Firstly, if we reduce disparities between countries with respect to any important attribute of theirs, including energy efficiency, we kick out of the game a lot of opportunities for future learning: the ‘many alternative versions’ part of the process is no more there. Secondly, I claim there is no such thing as objective evolutionary purpose, would it be maximizing energy efficiency or anything else. Evolution has no purpose; it just has the mechanism of selection by replication. Replication of humans is proven to happen the most favourably when we collectively learn fast and make a civilisation out of that learning.
Therefore, whilst having no objective evolutionary purpose, human societies have objective orientations: we collectively attempt to optimize some specific outcomes, which have the attribute to organize our collective learning the most efficiently, in a predictable cycle of, respectively, episodes marked with large errors in adjustment, and those displaying much smaller errors in that respect.
From that theoretical cleavage between my method and the postulates of the MuSIASEM framework, I derive two practical claims as regards economic policies, especially as regards environmentally friendly energy systems. Looking for homogeneity between countries is a road to nowhere, for one. Expecting that human societies will purposefully strive to maximize their overall energy efficiency is unrealistic a goal, and therefore it is a harmful assumption in the presence of serious challenges connected to climate change, for two. Public policies should explicitly aim for disparity of outcomes in technological race, and the race should be oriented on outcomes which are being objectively pursued by human societies.
Whilst disagreeing with professor Valeria Andreoni on principles, I find her empirical findings highly interesting. Rapid economic change, especially the kind of change associated with crises, seems to correlate with deepening disparities between countries in terms of energy efficiency. In other words, when large economic systems need to adjust hard and fast, they sort of play their individual games separately as regards energy efficiency. Rapid economic adjustment under constraint is conducive to creating a large discrepancy of alternative states in what energy efficiency can possibly be, in the context of other socio-economic outcomes, and, therefore, more material is there for learning collectively by experimenting with many alternative versions of ourselves.
Against that theoretical sketch, I place the second paper which I judge worth to introduce with: Koponen, K., & Le Net, E. (2021): Towards robust renewable energy investment decisions at the territorial level. Applied Energy, 287, 116552. https://doi.org/10.1016/j.apenergy.2021.116552 . I chose this one because it shows a method very similar to mine: the authors build a simulative model in Excel, where they create m = 5000 alternative futures for a networked energy system aiming at optimizing 5 performance metrics. The model was based on actual empirical data as for those variables, and the ‘alternative futures’ are, in other words, 5000 alternative states of the same system. Outcomes are gauged with the so-called regret analysis, where the relative performance in a specific outcome is measured as the residual difference between its local value, and, respectively, its general minimum or maximum, depending on whether the given metric is something we strive to maximize (e.g. capacity), or to minimize (e.g. GHG).
I can generalize on the method presented by Koponen and Le Net, and assume that any given state of society can be studied as one among many alternative states of said society, and the future depends very largely on how this society will navigate through the largely uncharted waters of itself being in many alternative states. Navigators need a star in the sky, to find their North, and so do societies. Koponen and Le Net simulate civilizational navigation under the constraint of four stars, namely the cost of CO2, the cost of electricity, the cost of natural gas, and the cost of biomass. I generalize and say that experimentation with alternative versions of us being collectively intelligent can be oriented on optimizing many alternative Norths, and the kind of North we will most likely pursue is the kind which allows us to learn efficiently how to go from one alternative future to another.
Good. This is my ‘Introduction’. It sets the tone for the method I present in the subsequent section, and the method opens up on the fine details of theory.
[1] Andreoni, V. (2020). The energy metabolism of countries: Energy efficiency and use in the period that followed the global financial crisis. Energy Policy, 139, 111304. https://doi.org/10.1016/j.enpol.2020.111304
[2] Koponen, K., & Le Net, E. (2021): Towards robust renewable energy investment decisions at the territorial level. Applied Energy, 287, 116552. https://doi.org/10.1016/j.apenergy.2021.116552 .
