It is useful to distinguish between tool-first approach and problem-first approach in social science and natural science, since the focus of “PROBLEM” is different. Physicists would identify what is FUNDAMENTAL problem and what is Applied problem. For example, after Newton solved the fundamental problem of classical mechanics, we can apply it to solve the trajectory of a cannon ball or satellite trajectory, and quantum mechanics can be applied to study optical spectra and nuclear power. However, the fundamental problem in classical mechanics is the COPERNICUS problem and the origin of quantum theory was the problem of black radiation.
In social science, the fundamental problem is ORIGIN of ORGANIZATION and Dynamics of Social Evolution. For the case of nuclear waste, we do not need new mathematical tools. Nuclear physics has clear understanding of the physics mechanism. There are many ways to deal with nuclear waste in technology. For example, you can dumped it into a cave, ocean, or even space with varying costs and uncertainty. The issue in economics is cost and benefit analysis, how much price a society is willing to pay and how high of the standard of safety. The issue in politics and sociology is who make the decision. I don’t see any complexity in physics and mathematics, but a lot of issues in economics and politics rooted in conflicting interests and geopolitics. Social problem-solving are driven by events, not mathematics. We may not wait for a hundred year until a disaster or war occur and broke the dead-lock in parliament debate or geo-political balance.

Robert Delorme says: December 2, 2017 at 10:19 pm
“Dave Taylor’s many ideas and references make me appear quite down-to-earth”.

There is nothing NOT down to earth in the proven theory and ubiquitous practice of communication systems. It just that philosophers and social scientists have seemed oblivious to them. Apologies for being blunt, but is this the ostrich, sensing danger, burying its head in the sand? Or the “not invented here” syndrome: an arrogant aristocracy, happy enough to sell any products, dismissing the processes which produce them as vulgar “trade”?

Teaching is about learning the language, but education – of the teacher as well as his students – is achieved by posing questions. Thankfully, Professor Delorme has done just that. No need for him to defend himself.

problem

Historically, Plato advocated pursuing reality in the light rather than chasing shadows, but Aristotle didn’t; Christ was recognised as the Light, but Aquinas saw Aristotle brilliant in that light. The Catholic Descartes saw the light of abstraction, illuminating Newton’s physics, but the Protestant Locke generalised the shadows he saw, seeing existing things and their properties, so to use a phrase from process philosopher A N Whitehead, for whom all science was “footnotes to Plato”, the radical atheist Hume got hold of “the wrong end of the stick”, leaving the difficulties we see to this day in social science and economics. American librarian Dewey repeatedly subdivided his world of books, only to find his generalisations overlapped; Indian library scientist Ranganathan went back to what amounted to Cartesian abstraction, arousing my interest by wondering why it worked.[1] Indian philosopher Roy Bhaskar popularised C S Peirce’s term ‘abduction’ for the logic of abstraction, or often ‘retroduction’ to emphasise its being the inverse of ‘deduction’. Ranganathan’s acronym PMEST provides a simple way of visualising his Copernican revolution in library science, which in practice was used in a compromise forming a more complex UDC from the simple Dewey decimal classification. He didn’t simply divide up the Personality (here we might say phenomena) of a subject. By abstracting all the phenomena he left the Matter whitch formed the phenomena, if he abstracted that he was left with the Energy which drove it; if he abstracted that he was left with location in Space and/or Time. His Colon Classification is thus not a simple number indexing a subdivision of Phenomena but complex encoding at four levels.

Inverting the abduction of PMEST reveals deduction of progress in the evolution of complexity:

Nothing: METRIC COMPLEXITY: the mathematical null set; Complex Number formed geometrically by Cartesian coordinates differentiating four closed circuits on spherical surfaces

Time: BASIC COMPLEXITY with Phenomenological null [unchanging, freely diverging linear motion is undetectable and therefore non-scalar]. Emerging free linear energetic motion is symbolised by energy circulating within the four closed Cartesian circuits and Time is symbolised and measured by the four quarters of the clock swept out by ordered rotation through the areas so mapped out. Expressed algebraically, differentiation subtracts a dimension, so dt(1)/dt => t(0), adding local closure to free motion, i.e. static spray to dynamic currents and waves. Whatever the timescale of rotation, the dynamic ‘1’ reduces to Fourier sines and cosines by a simple transformation of Pythagoras’s Theorem.

Space: DIMENSIONAL COMPLEXITY. Particles of spray coalesce in a dimensional order of complexity: figuratively spray into drops, drops into one-dimensional streams, two-dimensional pools, three-dimensional falls, and these forming deeper pools: cells combining as trees growing up, animals also moving around the surface, humans also moving imaginatively into the future, what Levi- Strauss saw as forming the unit of societies being families of mothers, fathers, daughters and sons who would become uncles. Basically, two static dimensions suffice to map states, changes and terms for these.

Energy: INTERNAL COMPLEXITY. The coordinate system of four interconnected circuits is representing a system of physical channels directing all or any physical energy flows carrying encoded directional information. The laws of physics apply to the energy flows but the laws of communication apply to their time-ordered encoding: static aim, deviation correction now (i.e. before the information can become physically actual), correction of displacements accumulating from residual deviations in the past, and avoidance deviations as obstacles become apparent in the near future. Hence the PID information system in which, IF THE AIM IS INVERTED, avoidance diversion is interpreted as correction information, and uncorrected avoidance accumulates in the past, which experiments with navigation quickly show will produce chaos.

Matter: DEEP COMPLEXITY. Reminiscent of your quotes of von Neumann on the process-product pairing and von Foerster on the cybernetics of cybernetics (3.4.2) but contradicting the argument (3.5.1) that “Complexity is not inherent to reality but to our knowledge of reality” (The word ‘complexity’ is inherent to our ability to know it but so also is the structural architecture of the physical brain and patterning of synaptic growth which enable us to physically direct our senses so as to perceive what is there). In the above derivation, the root of real complexity lies in the difference between virtually mass-less free energy and captive. If Descartes was prepared to believe in his own reality because he was thinking, by the same token I am prepared to believe that energetic motion was self-captured in superconductive loops long before there were not just others but anyone to know it subjectively. What is true of all will be true of the reality of Descartes’ mind. Thus a process involving ionic particles as well as superfluid electronic or light energy will carry along material adjacent to the channels it is flowing in, depositing it elsewhere as a product, thereby changing the world it represented. (This is a practical reason for separating the two, as in PID servos using electronic logic to direct the energy needed for action). Godel said no language is rich enough to prove everything, but in the attempt to do so we change the material representation which programs the encoded flow directing capabilities of the language – Marx’s MCM’ – so we may become able to prove the specific point we initially could not. If mere garbage (noise, intractable data) goes into a real computer we get garbage out, but if the intractability of data is due to interlaced encoding of data, the computer minimally needs circuit logic able to distinguish data formats, storage addresses, types of encoding and procedures capable of doing the encoding/encoding, decoding and communication procedures: both during communication flows and in static storage. Deep complexity is thus material complexity in the encoded patterning of stores and communications: as in interpretation of both coin and internet transfers as monetary transactions.

Personality: SUPERFICIAL or APPARENT COMPLEXITY in empirical phenomena. Santa Fe have mired most people in PHENOMENOLOGICAL INTRACTABILITY by measuring the amount of Shannon’s noise as if it were his decodeable information. They have ignored the demonstration by Lorenz that its generation is simply explicable in terms of the dimensionality of feedbacks, so Shannon’ point that detectable effects of noise can be suppressed can be followed up by limitation of positive feedback and reduction of its deeply physical causes (as in moving the microphone away from the speakers) if and when chaotic phenomena arise. Instead we have seen Brian Arthur of the Santa Fe outfit praising positive feedback as the quick way to increasing monetary returns, ignoring the squeals as this sacrifices everything else.

[1] S R Ranganathan, “Hidden Roots of Classification”, Information Storage and Retrieval, 3(4), Dec 1967, pp.399-410.

Responding to Ping Chen, December 2, 2017 at 12:55 am

As the familiar terms “Technical” and “Social” correspond to my more abstract “process” and “material” (i.e. structural) complexity, I would be happy to adopt them in practical discussion. “Amen” (so be it) to the thank you to Professor Delorme.

So Frege’s research created the problem; A N Whitehead (1914) , originator of process philosophy as a response to Russell, famously saw how Ping Chen’s “Copernican Revolution” might have been needed to resolve it.

“The art of reasoning consists in getting hold of the problem at the right end, of seizing on the few general ideas that illuminate the whole, and persistently organising all subsidiary facts around them”.

Cit. W W Sawyer, “Prelude to Mathematics”, in the chapter on Transformations.

I chanced on “the right end” of ‘Deep Complexity’ back in 1983, while struggling with Thatcher’s undoing of the Keynesian revolution. But I’m a picture-drawer. When most people expect systematic writing my picture still needs to be spelled out by a systematic thinker like yourself.

My apologies if you feel I have been slighting your work, but perhaps you misunderstand me. What I actually wrote was “So that’s my solution to your academic problem. The answer to the practical problem is for authorities to be unambiguous and obviously reasonable.” The academic problem I had been discussing was why French road fatalities were so much higher than British, and “The practical answer” was fairly obviously mine. Of course I had understood that road safety is a real life problem, but also that your research was trying to get a handle on it because of its intractibility. It seems to me that this is the problem your paper is seeking to solve. Your paper spelled this out lucidly (see below), mentioning three lines of argument which mine parallel: the first very briefly in reaction to a comment by Steven de Canio about Santa Fe confusing noise with signal, (so that those who follow them cannot see the wood for the trees). The second is exactly what I have done, my frame of reference subsuming everything, not just economic phenomena. The third is where I end up, with theory unable to spell out the future, but able to direct us to where to look for it. You say:

“I attempt in this paper to move beyond the inevitable case specificity of these findings, and to model complex phenomenal intractability in a constructive way. I argue three things. First, there exist empirical, concrete manifestations of intractability closely connected with various complex phenomena in economics and social science more generally. Although these manifestations of a complex phenomenal intractability may be significant, they remain broadly unnoticed or neglected and trivialized, that is, made seem less significant than they actually are. Second, complexity with nontrivial phenomenal intractability can be modelled constructively. A model is developed on the basis of an alternative frame of reference which subsumes the classical frame of reference. Third, this modelling is encompassing. It may help avoid the overconfidence in the effectiveness of theory that economics and social science often harbour through a usual way of theorizing that deprives itself of, or excludes, the possibility of nontrivial phenomenal intractability.

“This modelling brings a toolkit for dealing with intractable empirical problem situations. It might open up a debate about its rather far reaching implications for the style of theorizing based on empirical research, in economics and social science, whenever the possibility of complexity with phenomenal intractability is not assumed away from the outset.”

I hope my comments will be helpful in opening up this debate. Empirical research I understand as merely the first and last phases in the scientific process, identifying problems for insight and experiment to resolve and providing quality control for deciding whether are residual problems needing a further cycle of investigation. Experimental engineering doesn’t deny intractable evidence, but tends to seek ways of avoiding rather than untangling or partitioning it, as in macro vs micro economics. While I understand the value of your cross-disciplinary team when you are trying to understand the problem, here’s a snippet from a fascinating history which conveys the ethos of the team I worked with:

” ALGOL 68 was a very new language at the time, and [Peck’s] book is the proceedings of an IFIP Working Conference on ALGOL 68 Implementation, held in Munich, July 1970. I was working with two people, Ian Currie and John Morison … [Currie’s] paper was accepted, and we all went to the conference. To say we made an impact wouldn’t be overstating it—because all these people were academics and in universities, and they had been defining this language, but nobody had been actually writing a compiler for it; so we found that when we turned up at this conference, we had the world’s first ALGOL 68 compiler—which absolutely thrilled the people who had written the language, because they hadn’t quite got that far. A different world from the commercial marketplace, of course, but it made quite a stir in those circles.”

http://ethw.org/Oral-History:Susan_Bond#Developing_the_World.E2.80.99s_First_ALGOL_68_Compiler

The deep complexity here lies in relations between government and industry. John Locke, in his Two Treatises on Government almost a century before Adam Smith, when the issue was land shares in the settlement of America, proposed the obviously sensible rule that a man could claim as much land as he could work, so long as there was as much left for newcomers. What went wrong was treating slaves as less than men, and slave owners forming the government, so the share became seen legally as being as much as a Man could work with the slaves at his disposal. Today we have organisations treated as corporate persons, growing by fighting over dead men’s shoes, for no longer is there “as much” left.

The ‘deep’ solution to the traffic problem, then, is for governments to make the law unambiguous about the nature of Man, so that ownership of firms and property is limited to what an individual can manage, not the gift of CEO’s and landlords; and not saleable, shares of it being the gift of individuals as such or as partners in a family or cooperative. Thus would be generated a tendency to form localised communities in which one can walk to work and learn to do what needs doing locally: much as can still be seen in Belloc’s (1900) central France, as envisaged in the Distributism of Chesterton’s (1926) ‘The Outline of Sanity’ and updated in Schumacher’s (1974) ‘Small is Beautiful’. Tendencies tend to work slowly, and sadly, the tendency operative with debt-based banking money is going against this, as the CEO’s of centralised banking groups are being allowed to close hundreds more local banks, eliminating queries and well-informed advice, automating the distributed accounting network and generating yet more commuting. Thus, deeper even than the traffic problem lies the root of all evil – love of money – generated by the misconception brought about by dishonest money, that personal credit is wealth. Operational Research thought suggests minimising traffic by concentrating mass production of materials along linear cities serviced by motorways and rail, with branches transporting materials, job-sharing commuters and parcel traffic to villages. In Britain that is happening along motorways, but production line rather than intercity rail has been an opportunity missed.

In my comment on November 29, 2017 at 4:55 pm I offered SSADM to Robert as a ready-made system of systems analysis. This, explained briefly as a process of exploration, (1) reduces real world objects to data objects, mapping the one-many relationships between them; (2) takes real world processes and reduces them to procedures necessary to generate the object’s data sets and relationships; (3) checks out the relationships statically by checking out their life histories: creation, modification, elimination; (4) makes provision for checking and correcting them in practice by adding an audit trail. This may be likened to creating a design specification. The four-level typed programming language Algol68 then enters in the system construction phase, where it is necessary to discuss types of procedure as an aim, before one has worked out how to construct them.

This raises a philosophical issue (how to decide?) requiring in practice a policy decision, this being analogous to that in Economic philosophy itself. Should programmers use this ‘complex’ Algol68 or stick to ‘simpler’ languages for familiar tasks like Fortran (formula translator), Cobol (common business-oriented language), Unix or Windows (which string together ready-made processes whose results one can see but whose operation one can neither prove nor check)? Economic Policy has decided this de facto by using Algol68-like languages (‘C’ and Ada) for scientific, system construction or safety-critical software, and ‘pre-packaged’ software for gaining economy at the expense of understanding and skills.

But Education Policy in Economics has been decided by mainstream economists trained in the ‘Fortran’ era of simple (Newtonian) science, to the disgust of non-mathematical accountants who prefer textual Cobol. Neither side seems to recognise that, since 1948, science has become complex, with Shannon’s information science adding a new dimension to it. (It is not mechanistic, so it is not simply added on). Mechanical science has aimed for know-how, simplicity and technical efficiency, hence economy. Information science showed how to achieve efficient information coding, but also the extent of (and how to increase) redundant information capacity, so it can be used to lay audit trails enabling mistakes to be located and automatically corrected before they have time to be acted on. Economy is effected by our not physically doing the wrong thing. In cybernetic (macro) form this arrangement is negative feedback, the recursively repeated steering function, the P of a PID servo. The reflexivity of George Soros is something different again: the observed effect of counter-logical corrections that I explained above as inversion of I and D feedbacks, as when a steersman mistakes the South for the North pole.

” ‘Deep Complexity’ for me means finding the same minimal form of complexity in the representation of change back in the depths of time, manifesting in evolving capabilities and the human concept of PID control via embodied or encoded information systems, given just the energy of the Big Bang”.

How this leads up to economics may be more easily understood by those familiar with the Biblical stories and Marxist theory, as its axioms represent a philosophical choice between taking process or product as prior: the Christian image of a Father dying in a Big Bang so that we might live, or what the philosopher Hume assumed: a ready-made universe. Marx’s version of this, applied specifically to the recursive process of Capitalism, distinguished MCM’ from CMC’, i.e. starting with money (in Keynesian terms liquidity), or starting with nature’s material capital; both aiming to end with more than they started with. Over its lifetime the evolution of a Big Bang universe would follow the pattern
MCMCMCMCMCM… as energy crystalises into material, whereas a capitalism exploiting its physical and living capital to reify money – CMCMCM – ends with no capital and merely monetising debt. Hence my preference – not its equivalence to the Creation story – for taking as axiomatic the existence of the energy of the Big Bang (defined as Bateson defined Information: “a difference which makes a difference”), and using Cartesian coordinates as a primitive measure of its spherical limits, scale-free like lines drawn on an expanding balloon. The universe is inside the balloon, so the lines represent circuits with energy flowing round inside them, as began to become obvious of blood and electricity.

And so, as the metaphoric hands of time sweep out the quarters of the successive eras, electromagnetic waves form as energy beaches at the end of the universe, break into particulate material form as electronic spray and distinct waves of magnetic energy (many still with bubbles inside) which coalesce in stable combinations to form the atomic spectrum mapped by the Periodic Table, which in turn combine into active acids, alkalines, salts and organic rings, whence initially cellular life growing upwards as plants, moving sideways as animals and venturing into the future as humans, the paths of whose activities can be traced in the PID systems we are discussing; and these in turn evolve into automata with goals of their own. Hence Deep Complexity, with humans the icing on Professor Delorme’s cake and the monetary PID of capitalism the froth on Marx’s beer.

We have been here before, but in literary usage a Type determining the way we look at things is presented not as an abstract structure but as a concrete example to help focus and direct our senses so they can see what is there. The localisation of energy in running circuits anciently suggested the possibility of God; Pythagoras added right angled triangles and Euclid proved a triangle was necessary and sufficient to define a circle. Hence the Christian concept of God as the dynamic Trinity of a Father whose circulating Spirit (the word means invisible breathe or wind, i.e. energy) is formed into the Word of his self-knowledge, this being released in the hope of having a family. The “critical experiment” demonstrating the reality of the conservation of his energy was his acting out his Word in the life, death and resurrection of Jesus.

In my childhood the church, called the Roman Catholic by its enemies, still used world-wide the obsolete Roman language Latin to symbolise the meaning of the word Catholic: that God’s love is “for everyone”. Every Mass ended with the Preface to St John’s Gospel (“In the Beginning was the Word …”) and we regularly sang a Latin hymn, written c.1250 by Aquinas, an early philosopher of economics, that captures beautifully the philosophical arguments for what is a philosophical choice: being prepared to take the meaning of the Christian story as real, as against the mere shadows in Plato’s story of the cave:

“Types and shadows have their ending, for the newer rite is here;
Faith, our outward sense befriending, makes the inward vision clear.”