MY EDITORIAL ON YOU TUBE

I am recapitulating on my research regarding cities and their role in our civilization. In the same time, I start preparing educational material for the next semester of teaching, at the university. I am testing somehow new a format, where I precisely try to put science and teaching content literally side by side. The video editorial on You Tube plays an important part here, and I sincerely invite all my readers to watch it.  

I am telling the story of cities once again, from the beginning. Beginning of March 2020. In Poland, we are going into the COVID-19 lockdown. I am cycling through the virtually empty streets of Krakow, my hometown. I slowly digest the deep feeling of weirdness: the last time I saw the city that inanimate, it was during some particularly tense moments in the times of communism, decades ago. A strange question keeps floating on the surface of my consciousness: ‘How many human footsteps per day does this place need to be truly alive?’.

Cities are demographic anomalies. This is particularly visible from space, when satellite imagery serves to distinguish urban areas from rural ones. Cities are abnormally dense agglomerations of man-made architectural structures, paired with just abnormally dense clusters of night-time lights. We, humans, we agglomerate in cities. We purposefully reduce the average social distance, and just as purposefully increase the intensity of our social interactions. Why and how do we do that? The ‘why?’ is an abyssal question. If I attempt to answer it with all the intellectual rigor possible, it is almost impossible to answer. Still, there is hope. I have that little theory of mine – well, not just mine, it is called ‘contextual ethics’ – namely that we truly value the real outcomes we get. In other words, we really want the things which we actually get at the end of the day. This could be a slippery slope. Did Londoners want to have the epidemic of plague, in 1664? I can cautiously say it wasn’t on the top list of their wildest dreams. Yet, acquiring herd immunity and figuring out ways of containing an epidemic outbreak: well, that could be a valuable outcome in the long perspective. That outcome has a peculiar trait: it sort of can be wanted only at the collective level, since it is a collective outcome par excellence. If we pursue an outcome like this one, we are being collectively intelligent. It would be somehow adventurous to try and acquire herd immunity singlehandedly. 

Cities manifest one of the ways we are collectively intelligent. In cities, we get individual outcomes, and collective ones, sort of in layers. Let’s take a simple pattern of behaviour: imitation and personal style. We tend to imitate each other, and frequently, as we are doing so, we love pretending we are reaching the peak or originality. Both imitation and pretention to originality make any sense only when there are other people around, and the more people are there around, the more meaningful it is. Imagine you have a ranch in Texas, like 200 hectares, and in order to imitate anyone, or to pretend being original, you need to drive for 2 hours one way, and then 2 hours back, and, at the end of the day, you have interacted with maybe 20 people.

Our human social structures are machines which make other social structures, and not only sustain the current humans inside. A lot of behavioural patterns make any sense at all when the density of population reaches a reasonably required minimum. Social interactions produce and convey information which our brains use to form new patterns. As I think about it, my take on collective intelligence opens up onto the following claim: we have cities in order to make some social order for the future, and order made of social roles and group identities. We have a given sharpness of social distinction between cities and the countryside, e.g. in terms of density in population, in order to create some social roles and group identities for the future.

We, humans, had discovered – although we might not be aware of what we discovered – that certain types of social interactions (not all of them) can be made into recurrent patterns, and those patterns have the capacity to make new patterns. As long as I just date someone, it is temporary interaction. When I propose, it takes some colours: engagement can turn into marriage (well, it should, technically), thus one pattern of interaction can produce another pattern. When I marry a woman, it opens up a whole plethora of new interactions: parenthood, agreement as for financials (prenuptial contracts or the absence thereof), in-law family relations (parents-in-law, siblings-in-law). Have you noticed that some of the greatest financial fortunes, over centuries, had been accumulated inside family lineages? See? We hit the right pattern of social interactions, and from there we can derive either new copies of the same structure or altogether new structures.

Blast! I have just realized I finally nailed down something which I have been turning around in my mind for months: the logical link between human social structures and artificial neural networks. I use artificial neural networks to simulate collective intelligence in human societies, and I have found one theoretical assumption which I need to put in such a model, namely that consecutive states of society must form a Markov chain, i.e. each individual state must be possible to derive entirely from the preceding state, without any exogenous corrective influence.

Still, I felt I was missing something and now: boom! I figured it out. Once again: among different social interactions there are some which have the property to turn into durable and generative patterns, i.e. they reproduce their general structure in many local instances, each a bit idiosyncratic, yet all based on the same structure. In other words, some among our social interactions have the capacity to be intelligent structures, which experiment with themselves by producing many variations of themselves. This is exactly what artificial neural networks are: they are intelligent structures able to experiment with themselves by generating many local, idiosyncratic variations and thereby nailing down the variation which minimizes error in achieving a desired outcome.

When I use an artificial neural network to simulate social change, I implicitly assume that the social change in question is a Markov chain of states, and that the society under simulation has some structural properties which remain consistent over all the Markov chain of states. Now, I need to list the structural properties of artificial neural networks I use in my research, and to study the conditions of their stability. An artificial neural network is a sequence of equations being run in a loop. Structure of the network is given by each equation separately, and by their sequential order. I am going to break down that logical structure once again and pass its components in review. Just a general, introductory remark: I use really simple neural networks, which fall under the general category of multi-layer perceptron. This is probably the simplest that can be in terms of AI, and this is the logic which I connect to collective intelligence in human societies.

The most fundamental structure of an artificial neural network is given by the definition of input variables – the neural stimuli – and their connection to the output variable(s). I used that optional plural, i.e. the ‘(s)’ suffix, because the basic logic of an artificial neural network assumes defining just one output variable, whilst it is possible to construe that output as the coefficient of a vector. In other words, any desired outcome given by one number can be seen as being derived from a collection of numbers. I hope you remember from your math classes in high school that the Pythagorean theorem, I mean the a² + b² = c² one, has a more general meaning, beyond the simple geometry of a right-angled triangle. Any positive number we observe – our height in centimetres (or in feet and inches), the right amount of salt to season shrimps etc. – any of those amounts can be interpreted as the square root of the sum of squares of two other numbers. I mean, any x > 0 is x = (y² + x²)^0,5. Logically, those shady y and z can be seen, in turn, as derived, Pythagorean way, from even shadier and more mysterious entities. In other words, it is plausible to assume that x = (y² + x²)^0,5 = {[(a² + b²)^0,5]² + [(c² + d²)^0,5]²}^0,5 etc.

As a matter of fact, establishing an informed distinction between input variables on the one hand, and the output variable on the other hand is the core and the purpose of my method. I take a handful of variables, informative about a society or a market, and I make as many alternative neural networks as there are variables. Each alternative network has the same logical structure, i.e. the same equations in the same sequence, but is pegged on a different variable as its output. At some point, I have the real human society, i.e. the original, empirical dataset, and as many alternative versions thereof as there are variables in the dataset. In other words, I have a structure and a finite number of experiments with that structure. This is the methodology I used, for example, in my paper on energy efficiency.

There are human social structures which can make other social structures, by narrowing down, progressively, the residual error generated when trying to nail down a desired outcome and experimenting with small variations of the structure in question. Those structures need abundant social interactions in order to work. An artificial neural network which has the capacity to stay structurally stable, i.e. which has the capacity to keep the Euclidean distance between variables inside a predictable interval, can be representative for such a structure. That predictable interval of Euclidean distance corresponds to predictable behavioural coupling, the so-called correlated coupling: social entity A reacts to what social entity B is doing, and this reaction is like music, i.e. it involves moving along a scale of response in a predictable pattern.

I see cities as factories of social roles. The intensity of social interactions in cities works like a social engine. New businesses emerge, new jobs form in the labour market. All these require new skillsets and yet those skillsets are expected to stop being entirely new and to become somehow predictable and reliable, whence the need for correspondingly new social roles in training and education for those new skills. As people endowed with those new skills progressively take over business and jobs, even more novel skillsets emerge and so the wheel of social change spins. The peculiar thing about social interactions in cities are those between young people, i.e. teenagers and young adults up to the age of 25. Those interactions have a special trait, just as do the people involved: their decision-making processes are marked by significantly greater an appetite for risk and immediate gratification, as opposed to more conservative and more perseverant behavioural patterns in older adults.

Cities allow agglomeration of people very similar as regards the phase of their personal lifecycle, and, in the same time, very different in their cultural background. People mix a lot inside generations. Cities produce a lot of social roles marked with a big red label ‘Only for humans below 30!’, and, in the same time, lots of social roles marked ‘Below 40, don’t even think about it!’. Please, note that I define a generation in sociological terms, i.e. as a cycle of about 20 ÷ 25 years, roughly corresponding to the average age of reproduction (I know, first parenthood sounds kind’a more civilized). According to this logic, I am one generation older than my son.

That pattern of interactions is almost the exact opposite of rural villages and small towns, where people interact much more between generations and less inside generations. Social roles form as ‘Whatever age you are between 20 and 80, you do this’. As we compare those two mechanisms of role-formation, in turns out that cities are inherently prone to creating completely new sets of social roles for each new generation of people coming with the demographic tide. Cities facilitate innovation at the behavioural level. By innovation, I mean the invention of something new combined with a mechanism of diffusing that novelty across the social system.

These are some of my thoughts about cities. How can I play them out into my teaching? I start with a staple course of mine: microeconomics. Microeconomics sort of nicely fit with the topic of cities, and I don’t even have to prove it, ‘cause Adam Smith did. In his ‘Inquiry Into The Nature And Causes of The Wealth of Nations’, Book I, Chapter III, entitled ‘That The Division Of Labour Is Limited By The Extent Of The Market’, he goes: ‘[…] There are some sorts of industry, even of the lowest kind, which can be carried on nowhere but in a great town. A porter, for example, can find employment and subsistence in no other place. A village is by much too narrow a sphere for him; even an ordinary market-town is scarce large enough to afford him constant occupation. In the lone houses and very small villages which are scattered about in so desert a country as the highlands of Scotland, every farmer must be butcher, baker, and brewer, for his own family. In such situations we can scarce expect to find even a smith, a carpenter, or a mason, within less than twenty miles of another of the same trade. The scattered families that live at eight or ten miles distance from the nearest of them, must learn to perform them- selves a great number of little pieces of work, for which, in more populous countries, they would call in the assistance of those workmen. Country workmen are almost everywhere obliged to apply themselves to all the different branches of industry that have so much affinity to one another as to be employed about the same sort of materials. A country carpenter deals in every sort of work that is made of wood; a country smith in every sort of work that is made of iron. The former is not only a carpenter, but a joiner, a cabinet-maker, and even a carver in wood, as well as a wheel-wright, a plough-wright, a cart and waggon-maker. The employments of the latter are still more various. It is impossible there should be such a trade as even that of a nailer in the remote and inland parts of the highlands of Scotland. Such a workman at the rate of a thousand nails a-day, and three hundred working days in the year, will make three hundred thousand nails in the year. But in such a situation it would be impossible to dispose of one thousand, that is, of one day’s work in the year […]’.     

Microeconomics can be seen as a science of how some specific social structures, strongly pegged in the social distinction between cities and the countryside, reproduce themselves in time, as well as produce other social structures. I know, this definition does not really seem to fall close to the classical, Marshallian graph of two curves, i.e. supply and demand, crossing nicely in the point of equilibrium. ‘Does not seem to…’ is distinct from ‘does not’. Let’s think a moment. The local {Supply <> Demand} equilibrium is a state of deals being closed at recurrent, predictable a price. One of the ways to grasp the equilibrium price consists in treating it as the price which clears all the surplus stock of goods in the market. It is the price which people agree upon, at the end of the day. Logically, there is an underlying social structure which allows such a recurrent, equilibrium-making bargaining process. This structure reproduces itself in n copies, over and over again, and each such copy is balanced on different a coupling between equilibrium price and equilibrium product.

Here comes something I frequently remind to those of my students who have enough grit to read any textbook in economics: those nice curves in the Marshallian graph, namely demand and supply, don’t really exist. They represent theoretical states at best, and usually these are more in the purely hypothetical department. We just guess that social reality is being sort bent along them. The thing that really exists, here and now, is the equilibrium price that we strike our deals at, and the corresponding volumes of business we do at this price. What really exists in slightly longer a perspective is the social structure able to produce local equilibriums between supply and demand, which, in turn, requires people in that structure recurrently producing economically valuable, tradable surpluses of physical goods and/or marketable skills.

Question: how can I know there is any point in producing an economically valuable surplus of anything? Answer: where other people make me understand they would gladly acquire said surplus. Mind you, although markets are mostly based on money, there are de facto markets without straightforward monetary payment. The example which comes to my mind is a structure which I regularly observe, every now and then, in people connected to business and politics, especially in Warsaw, the capital of my home country, Poland. Those guys (and gals) sometimes call it ‘the cooperative of information and favour’. You slightly facilitate a deal I want to strike, and I remember that, and later I facilitate the deal you want to strike. We don’t do business together, strictly speaking, we just happen to have mutual leverage on each other’s business with third parties. I observed that pattern frequently, and the thing really works as a market of favours based on social connections and individual knowledge. No one exchanges money (that could be completely accidentally perceived as corruption, and that perfectly accidental false perception could occur in a prosecutor, and no one wants to go to jail), and yet this is a market. There is an equilibrium price for facilitating a $10 million deal in construction. That equilibrium price might be the facilitation of another $10 million deal in construction, or the facilitation of someone being elected to the city council. By the way, that market of favours really stirs it up when some kind of elections is upcoming.

Anyway, the more social interactions I enter into over a unit of time, the more chances I have to spot some kind of economically valuable surplus in what I do and make. The more such social interactions are possible in the social structure of my current residence, the better. Yes, cities allow that. The next step is from those general thoughts to a thread of teaching and learning. I can see a promising avenue in the following scheme:

>>> Step 1: I choose or ask my students to choose any type of normal, recurrent social interaction. It can be interesting to film a bit of city life, just like that, casually, with a phone, and then use it as empirical material.

>>> Step 2: Students decompose that interaction into layers of different consistency, i.e. separate actions and events which change quickly and frequently from those which last and recur.

>>> Step 3: Students connect the truly recurrent actions and events to an existing market of goods or marketable skills. They describe, with as much detail as possible, how recurrent interactions translate into local states of equilibrium.

Good. One carryover done, namely into microeconomics, I try another one, into another one of my basic courses at the university: fundamentals of management. There is something I try to tell my students whenever I start this course, in October: ‘Guys, I can barely outline what management is. You need to go out there, into that jungle, and then you learn. I can tell you what the jungle looks like, sort of in general’. Social interactions and social roles in management spell power, hierarchy, influence, competition and cooperation on the top of all that. Invariably, students ask me: ‘But, sir, wouldn’t it be simpler just to cooperate, without all those games of power and hierarchy inside the organization?’. My answer is that yes, indeed, it would be simpler to the point of being too simple, i.e. simplistic. Let’s think. When we rival inside the organization, we need to interact. There is no competition without interaction. The more we compete, the more we interact, and the more personal resources we need to put in that interaction.

Mind you, competition is not the only way to trigger intense, abundant human interaction. Camaraderie, love, emotional affiliation to a common goal – they all can do the same job, and they tend to be more pleasant than interpersonal competition. There is a caveat, though: all those forms of action-generating emotional bonds between human beings tend to be fringe phenomena. They happen rarely. With how many people, in our existence, can we hope to develop a bond of the type ‘I have your back and you have my back, no matter what’? Just a few, at best. Quite a number of persons walk through their entire life without ever experiencing this type of connection. On the other hand, competition is a mainstream phenomenon. You put 5 random people in any durable social relation – business, teamwork, art etc. – and they are bound to develop competitive behaviour. Competition happens naturally, very frequently, and can trigger tacit coordination when handled properly.

Yes, right, you can legitimately ask what does it mean to handle competition properly. As a kid, or in your teenage years, have you ever played a competitive game, such as tennis, basketball, volleyball, chess, computer games, or even plain infantile fighting? Do you know that situation when other people want to play with you because you sometimes score and win, but kind of not all the time and not at all price? That special state when you get picked for the next game, and you like the feeling? Well, that’s competition handled properly. You mobilise yourself in rivalry with other people, but you keep in mind that the most fundamental rule of any competitive game is to keep the door open for future games.      

Thus, I guess that teaching management in academia, which I very largely do, may consist in showing my students how to compete constructively inside an organisation, i.e. how to be competitive and cooperative in the same time. I can show internal competition and cooperation in the context of a specific business case. I already tend to work a lot, in class, with cases such as Tesla, Netflix, Boeing or Walt Disney. I can use their business description, such as can be found in an annual report, to reconstruct an organisational environment where competition and cooperation can take place. The key learning for management students is to understand what traits of that environment enable constructive competition, likely to engender cooperation, as opposed to situations marked either with destructive competition or with a destructive absence thereof, on the other hand.

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