Author: Psybertron

I mentioned in my review of Anatoly Levenchuk’s “Systems Thinking 2020” having some subsequent dialogue about common ground in other areas of the Psybertron agenda. A significant overlap is the work of Karl Friston (Free Energy Principle / Markov Blankets / Emergent Organism / Active Inference) in my reading of Mark Solms, and in Levenchuk’s case, where he and Friston are both members of the advisory board of “The Active Inference Lab”.

[Small world in itself – and yet in the days since, the concept of “systems thinking” is everywhere, from politics and biology, to consciousness and metaphysics. This is not going away. It was xxxx noticed back in January? I’d slipped into systems language quite naturally into ongoing dialogues. And, I made quite a thing of “systems architecture” considerations when interpreting both Solms and McGilchrist (independent) work in terms of (say) anatomical and functional brain architecture.]

In the dialogue above, Levenchuk shared a paper appearing to cast doubt on Friston’s use of Markov Blankets – “The Emperor’s New Markov Blankets” – ENMB (2021) for short here. Full refs:

• • • Bruineberg, Jelle and Dolega, Krzysztof and Dewhurst, Joe and Baltieri, Manuel (2021) The Emperor’s New Markov Blankets. Behavioral and Brain Sciences 1-63. [Preprint] doi:10.1017/S0140525X21002351
      or
    • Bruineberg, Jelle and Dolega, Krzysztof and Dewhurst, Joe and Baltieri, Manuel (2020) The Emperor’s New Markov Blankets. PhilSciArchive [Preprint]

(More dialogue below in the Post Notes.)

START

It’s a substantial paper, 48 pages with some pretty heavy maths as well as arguments of principle. In fact when I read the parts of Solms where, amongst other things, he used (Freudian) mathematical notation additionally developed with Friston, I noted that it was perfectly possible I wasn’t properly understanding Friston’s arguments. Whilst it chimed intuitively with my own understandings, I wasn’t well placed to say whether it was formally right, one way or another – an occupational hazard in this kind of multi-disciplinary research.

“I’ve also kept in [my reviews] lots of technical specifics which I probably don’t understand as Solms intended, primarily to allow me later checking against other resources” (Myself, earlier.)

Well here is an opportunity 🙂 to respond to the “ENMB Paper” quoted directly below:

“This web of formalisms (Free Energy Principle, Markov Blankets, Active Inference) is developing at an impressively fast pace and the constructs it describes are often assigned a slightly unconventional meaning whose full implications are not always obvious. While this might ironically explain some of its appeal, as it can seem to the layperson to be steeped in unassailable mathematical justification …”

“We will argue that although this approach might have interesting philosophical consequences, it is dependent upon additional metaphysical assumptions that are not themselves contained within the Markov blanket construct.”

“In our view the FEP literature consistently fails to clearly distinguish between the ‘map’ (a representation of reality) and the ‘territory’ (reality itself). This slippage becomes most apparent in their treatment of the concept of a Markov blanket.”

“… a broader tendency within the FEP literature, in which mathematical abstractions are treated as worldly entities with causal powers.”

“[Friston’s is] a new and largely independent theoretical construct that is more closely aligned with notions of sensorimotor loops and agent-environment boundaries.”

“Inference within a model, as opposed to inference with a model, seeks to understand inference as it is physically implemented in a system, and places literal Markov blankets at the boundary between the system and its environment. The ‘model’ within which these Markov blankets are used is usually understood ontologically: here the map is the territory – the system performing inference is itself a model of its environment, and its boundary is demarcated by  Markov blankets.”

“This procedure of attributing to the territory (the dynamical system) what is a property of the map (the Bayesian network) is a clear example of the reification fallacy: treating something abstract as something concrete (without any further justification) … we propose to distinguish between ‘Pearl blankets’ to refer to the standard ‘epistemic’ use of Markov blankets and ‘Friston Blankets’ to refer to this new ‘metaphysical’ construct. While Pearl blankets are unambiguously part of the map (i.e., the graphical model), Friston blankets are best understood as parts of the territory (i.e., the system being studied).”

“As a general rule, one should not mistake the map described by a model for the territory it is describing: a model of the sun is not itself hot, a model of an organism is not itself alive, and so on.”

[ENMB Paper]

OK, so again, without going through any of the mathematical rigour – itself unassailable by me – an important issue is indeed covered by the extract above, that there are metaphysical (ontological) premises possibly unstated in the work of Friston (and  Solms), that might “appear to break this general rule without any further justification”. However these are quite explicit here.

Solms’ own response is categorical without any further metaphysical justification.

I have read [the paper]. I don’t think the Markov blanket formalism is a map of a territory but a description of the causal dynamics that actually exist in a territory. The territory in question is the (monist) functional organization of both brain and mind.

The ‘territories’ are the observable mental and neural phenomena. What they are calling the ‘map’ is, for me, the underlying functional system that explains those phenomena. This explanatory level (the functional organization of the system) cannot be observed; it must be inferred.

It is a dualist position. The formalism describes the actually causal ontology. As Galileo said: the book of Nature is written in the language of mathematics.

(Solms in Twitter exchange.)

I don’t buy the Galilean / Platonic argument as definitive, but it reinforces that this is not an accidental error in this school of work, but a deliberate act that needs to be understood as such. Sure the “book” of nature may be written in maths, but maybe not “nature” itself?

Good question, from any small boy not seeing the emperor’s clothes.

But it’s not necessary to analyse exactly what Galileo, or Plato before him, was asserting in any specific detail. That general rule of not confusing the map with the territory – not falling for the reification fallacy – is good advice and indeed is ancient advice. A Buddhist might point out that “the finger pointing at the moon is not the moon”. In science generally, our models in mathematical constructs used to represent, analyse and predict data about the real world are contingent approximations to the behaviour of that real world, but they are not it. Physics isn’t the real world, it’s our best current model of it. In any number of more mundane engineering applications, especially those that get implemented in analytical and operational computing applications, we constantly have to remind ourselves that the model is only a model, not the real thing, however seductive the virtual reality might be.

Dennett (much cited here) is among those acknowledged as providing advice to the ENMB paper, without any specific reference and, given his views on disembodied information and computation (**) – independent of any physical layer – in his own “evolved consciousness” story, I’d be interested to know his actual views on this argument. I’m pretty certain he uses very similar arguments to Friston and Solms, as I do too.

What we are saying is that in this model, the computation (**), the sensing of information and algorithmic processes of the systems and subsystem components, with and without Markov-blankets, is quite literally happening. These information entities and processes are more fundamental than the physical models which self-organise and emerge from them. This is indeed a metaphysical claim, whether or not explicitly stated as such by every user.

In these theories, in my own metaphysics as well as Solms says above, the information processing (**) is the territory, the foundation of the territory itself not just a map of it. Though obviously like any model we have also plenty of other information representations used to describe and present (map) the model and its processes to human audiences.

Friston and Solms (and myself) are not unique here, as the ENMB paper acknowledges, there are many philosophers and cognitive scientists with information-and-computation-based ontologies of reality. Integrated Information Theory (IIT after G Tononi) is one well developed example, but these are part of a wider movement. One corollary of these foundational (metaphysical) information-based ontologies is that both the physical (body) and mental (mind) worlds and their causal relations are explained by the same underlying metaphysics. A credible monism where dualism has stubbornly continued to exist. (Also a lot of new interest in various versions of pan-psychism in the 21st C, and again these theories provide an information-based “pan-proto-psychism” that may better support these.)

In many ways it’s good that the ENMB paper exists, because it is ringing an important alarm bell that more people in both science and philosophy should wake-up to how radically important these not-so-new theories are.

Thanks for the warning ENMB, but what you are describing is exactly what we’re doing.

END

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In a similar critical vein to the ENMB Paper, this newer one on FEP

(**) And Yogi Yaeger’s paper. “Natural Information Processing” as opposed to formal “Computation”. Not be confused – the formal term “computation” associated with the “computability” of Church, Turing, Shannon et al and the natural language term for “processing information”.

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Post Notes:

One source here on Psybertron that I’ve not really developed yet is John C. Doyle, a control systems guru I’ve mentioned being impressed with before – he’s written the text-books and is much cited in papers – but he hasn’t written for a generalist public so he’s quite low profile if it’s not your field. He’s very much a systems thinker looking for architectural abstractions yet using very real-life examples to illustrate. In this 30 minute talk – very dense / terse / rushed, packed with content easy to miss if you’re not concentrating – the last 15 minutes is very interesting. Very clearly joining up issues of multi-layer systems optimisation and evolution (Levenchuk) with human situational awareness and responses based around the visual field and the speed of saccade eye-movements (Solms)?

Anatoly Levenchuk Comments:

2. There are not only “map-territory” distinction and representation relation that may be confusing. There are functional object — physical object distinction with implementation/realization relation. And you should decide: what type of relation each of authors mentions.

IG: Ah, yes. Not always explicit in every discussion, but pretty fundamental that the systems / architecture view is functional – you maybe saw my comments on trying to get a Brain Atlas that held to this schematic view. See later comments on process-based relations.

3. A day ago I did post about phys-math-modeling and compactification/universalization of knowledge. It suggest more long chain of ontology modeling: physical object from domain that is classified/annotated by type of physical object (ToPO) from physics textbook and then this ToPO is represented (or classified/annotated, if you prefer it) by mathematics/abstract object. I am not mention about functional object option here, it is enough complicated with this. Mathematics is foundation and upper ontology, physics is middle ontology, domain objects is working ontology.

Thus you can parse phases like “As the locus of molecular, thermodynamic, and bioelectric exchange with the environment, the cell membrane implements a Markov Blanket (MB) that renders its interior сonditionally independent of its exterior (Pearl 1988; Clark 2017); this allows the cell to be described as a Bayesian active inference system (Friston 2010, 2013; see also Cooke 2020 for a variation on this approach)” — this “implements” means classification relation (but easily you can go along 3D extentionalism and try functional-physical object “implementation/realisation”).

Phrase I took from https://chrisfieldsresearch.com/min-phys-NC-2021.pdf
My text (sorry, in Russian) here: https://ailev.livejournal.com/1621997.html

IG: Excellent. The chain of causality, with emergent layers separated by Markov blankets is the model I’ve had in mind all the way through – even before I’d consciously heard of Markov blankets 😉 As you know my interest is going back to metaphysical foundations, but yes, even with a functional bias / preference we must get to the functional-physical realisation in the real world. Think I’ve come across Fields and Glazebrook before but yes … at root in my model, “(All) physical interaction is information exchange”. (That’s precisely why information is more fundamental metaphysically 🙂 )

4. “, the information processing is the territory, its foundation not the map of it, though obviously we have plenty of other information representations used to describe and present (map) the model and its processes to human audiences” — you refer here to “information processing” and I can point you to:

— “Integrating information in the brain’s EM field: the cemi field theory of consciousness”, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507405/ — “I describe the conscious electromagnetic information (cemi) field theory which has proposed that consciousness is physically integrated, and causally active, information encoded in the brain’s global electromagnetic (EM) field. I here extend the theory to argue that consciousness implements algorithms in space, rather than time, within the brain’s EM field”.
— “Types as Processes, via Chu spaces”, We match up types and processes by putting values in correspondence with events, coproduct with (noninteracting) parallel composition, and tensor product with orthocurrence. We then bring types and processes into closer correspondence by broadening and unifying the semantics of both using Chu spaces and their transformational logic. Beyond this point the connection appears to break down; we pose the question of whether the failures of the correspondence are intrinsic or cultural. — https://www.sciencedirect.com/science/article/pii/S157106610580475X?via%3Dihub (и дальше по этой линии Information flow in context-dependent hierarchical Bayesian inference, https://chrisfieldsresearch.com/contextual-pre.pdf)

IG: Thanks for these. I’m sceptical of “CEMI” and I don’t consider it necessary – it’s an information field, whatever the physical substrate, EM or otherwise – but I may follow-up, since Chris Fields is someone I have time for. Thanks.

Hope I paid my debt of commenting your posts )))
Sorry, but I am not sure that tell you something substantional about Markov blanket. Your post show that you already understand difference between abstract MB и physical one, I can only add complexity of ontology choices with functional object variant )))

IG: Actually – I was hoping you’d comment on the two prior posts on Solms – but YES – we have effectively covered the same ground. I appreciate your confidence I’m understanding this – or that at least we’re both misunderstanding it the same way 😉 Many thanks for the dialogue.

In my view “process” (something that flow, functional diagrams always with some flow/current in it) is good heuristic that we deal with functional (run-time) objects, not physical/product/module (construction time) objects.

I often have talks with “only process” people (e.g. category theory or other “transformations first”). Common thinking is about objects (of attention!) and relationships (processes) and IMHO this is supported by wetware in a brain. To the thinking you need both, but with only objects it became metaphysical (especially if you have no at least 3 timescales — evolution, learning/adapting and run-time) but with processes only you have absence of attention anchors for wetware. Therefore both but things first, process second.

4D dimentionalism is good for integration of object vs. process false dichotomy. Process is related not only time and function, but also space and physical objects!

IG: Yes understand that 4D model and that in the real day-to-day world we interact with space and “things” – but I am (after Whitehead) being quite radical here – metaphysical again 😊. (These “things” only emerge from networks of “events” at the information level … longer story).

Yes, works of John Doyle is relevant here — https://scholar.google.com/citations?hl=en&user=C6DtGmMAAAAJ&view_op=list_works&sortby=pubdate

IG: In my more general public dialogues – as opposed to researching technical papers – I find very few who have heard or or understand Doyle’s multi-layer architectural-optimisation. Once we accept layers (Markov blankets) as REAL, then I think his view is VERY IMPORTANT to so much evolution / self-organisation of ALL systems. This is amazing convergence from the practical engineering level right back to fundamental physics – as information and computation 🙂 Many thanks again.

Another brief “hold that thought” post.

My own metaphysics is based around atomic quantum points that I think of as truly Democritan atoms – genuinely indivisible, inconceivably divisible “a-toms” – without any parts or even properties of their own. Everything of any significance in the world – everything full-stop – is about relations between these.

What I know now, thanks to a question in the University Challenge final last night, is that Euclid defined his conception of a point as

“a point is … that which has no part”

‘Twas ever thus. Nothing hew under the sun.
(Democritus preceded Euclid but was still living when the latter became active?)

Just a brief note – to recommend this edition of BBCR4 Positive Thinking. Citizens’ Assemblies and a rolling Citizens’ Convention are an idea I bought into over a decade ago. My logic is this:

Democracy appears broken.

Democracy of some kind (after Churchill) is nevertheless the best – or least worst – system available.

Therefore we need to fix democracy, not reject it, not throw democratic babies out with the bath-water.

We need to add more representation that works.

Mostly we already have two or three level systems – Head of State / Lower House / Upper House, two of which are “executive” – but the most directly representative of these consider public representation on fixed election cycles – cycles which are too long for changing world events, but too short for proper long-term values and investment in priorities.

Rather than tinkering with these established institutions and their election / voting arrangements directly (see “babies & bathwater”), the proposal here is to add another one or two levels of Citizens’ Assemblies underneath these. To increase public engagement between election cycles and to manage & maintain priorities beyond these.

Now, there are arguments against – about the self-selection of those that actually get engaged – partisan / activists – vs the professional knowledge and commitment needed, that the fact that any influence may be toothless even though placed on record. We already have standing “parliamentary committee” systems that partly address the same issues? So clearly it’s important they’re not allowed to become redundant box-ticking activities, that engagement is supported by genuine commitment and resources, and so on.

BUT whatever their drawbacks, the increased engagement is encouraged – never a bad thing – AND, most importantly it properly recognises and reinforces a multi-layered, self-organising, Systems Thinking approach to the most complex problem facing humanity. Governance.

The Belgian approach described in this programme has several innovations – clearly two-time-scale / two-level ongoing convention and periodic assemblies and some quality thinking on how arrangements can avoid the pitfalls. Recommended. Worth a listen.

Definition as a Coffin?

“Hold your definition” is a plea by philosopher Daniel Dennett, often cited here on Psybertron, when dealing patiently with his scientific friends. Any discourse that starts with apparently clear definitions, manipulated solely by logic, is inherently limited by the fit between the history of those definitions and future of reality. At best, definitions are tentative outcomes from any discourse of any complexity.

My mind was caught this week by the idea of definition as a coffin for what Anatoly Levenchuk calls “dead-think” in his book which forms the basis of this Systems Management School course on “Systems Thinking 2020”.

[Aside – an important post of mine from 2015 discusses the temporary / contextual / contingent nature of objective identity-based definitions, anywhere from physics to politics.]

More on that later, but first, how did we get here?

The Circle from Cybernetics to Systems Thinking

The “Cyber” root has been behind the Psybertron project since I started it 22 years ago, with the rhyming “Psy” prefix emphasising the psychological over physical perspective, and the “tron” alluding to the increasing electronic automation context of our 21st century journey into “What, Why and How do we Know?”. A project triggered by the increasingly despairing sense that what is “known” has a much more significant psychological aspect than the received wisdom of the objective “STEM” sciences had us believe in the previous 20th century. That, and the sense of the inevitable, that algorithmically automating this stuff – without first addressing this problem – could only make it worse.

The 21st century experience of free, ubiquitous, electronic communications certainly bears-out those fears, but little did I know. Garbage in, more extreme garbage out, as they say, even in machine-learning / AI?

I’ve recapped the place of Cybernetics and Systems Engineering / Thinking in the project several times over the years. It was July 2002 I first made the Cybernetics connection explicit and noticed that lo-and-behold the original intention of those that invented it – the 1946 Macy conference with Wiener and von-Neumann – was that it concerned human decision-making and human systems of governance from the start. I was taking this human psychology angle for granted (above) in my own philosophical researches. It was January 2012 before I was prompted to go back and read Wiener’s original 1948 Cybernetics. And even later in January 2018 before I noticed that this human cybernetics had been dubbed the Second Cybernetics as long ago as 1963 since those first working with it in early systems engineering and electronic computing applications had clearly forgotten what the human originators intended by “kybernetes”, the root of governance.

Anyway, as I say, it’s not the first time I’ve recapped this story, most recently with this (March 22) reference and this (August 2021) reference in which I made the Systems Engineering to Systems Thinking connection explicit here. Having been an engineer working in systems of many kinds my whole career since the 1970’s “systems engineering” was informally central to everything anyway, implicit even as I was working the day job in the engineering of electronic information systems explicitly.

In that post I acknowledged …

Anatoly Levenchuk, the then chair of the INCOSE Russian chapter, and his colleague Victor Agroskin, still the smartest people I ever met anywhere in any context.

… as the people that first made the Systems Engineering (now Systems Thinking) explicit for me, as the topic under consideration. The English text of Anatoly’s latest book, mentioned in the introduction, is intelligently browsable on-line here, once you’ve registered for the Systems Thinking course. There is also a downloadable PDF of the December 2021 text. (Personally, anything over a few pages, I still prefer to read and review actual books, but let’s see how we get on. This is a 358 page book.)

Initial Review

As I write this I’ve only read and skimmed parts of Systems Thinking 2020, but given this and given the above, it is already recommended.

Firstly, the 358 pages are all content. Apart from the Table of Contents, there are no “end materials”; index, bibliography, references or notes to give any clues. All additional resources – and there are many – are linked within the text. (I often prefer to compare notes on these before I read any non-fiction book in full.)

Also, in my experience, idiomatic Russian is handled very badly by things like Google Translate and working with smart people like Agroskin and Levenchuk in on-line text and blogs has proven too hard except where they were doing their own real-time translation of their Russian thoughts into oral English for me. The good news is the English translation of the book is human (by Ivan Metelkin) and whilst additional native-English speaking editing will no doubt further improve the read and clarify intent, this text is entirely intelligible.

Details, Details.

I picked-up early on Levenchuk’s focus on pragmatism and practicality. One of the earliest philosophical things I wrote (2006) after more than a decade of modelling dictionaries of terminology for systems engineering purposes was a recognition that, whilst many of the problems with meaning (epistemology) involved more philosophical abstractions, that project was primarily pragmatic – for use by engineers on deliverable projects.

The principle concerns were ontology, a model of what existed, based on pragmatic interpretations of classification and set-theories, avoiding over-reaction to such anomalies as Russell’s Paradox, so that anything useful could be said about anything. That work was of course primarily pragmatic.

At first sight this looks like the age-old “perfection is the enemy of the adequate” which can endanger the delivery of any project, but in fact Levenchuk points out that this is a misunderstanding about levels of thinking that need to be recognised as distinct. In very much the same way that Systems Engineering might appear to have morphed into Systems Thinking, in reality these are distinct areas (layers) of consideration:

• • • Systems Project Engineering
    • Systems Engineering Thinking
    • Systems Thinking

Levenchuk’s style is to provide the reader / trainee / user with a “cheat sheet” – a prescriptive procedure and advice for practical use, as well as providing rationale and background on development of the methodologies and the supporting education and training resources. But it is vitally important the right cheat sheet is applied to the right task. Systems Thinking is not a substitute for engineering project execution best-practices. What it is, is a methodology for helping shape, define and prioritise aspects of a complex project, or architecting a programme or system of future activity. Deepening understanding and knowledge of such activities, quite distinct from simply “doing” them. Knowledge and understanding whose value materialise should that doing meet unexpected issues and future opportunities. (Significantly “surprise” – the sensed gap between expectations and reality – is fundamental to the “Active Inference” school of Systems Thinking – more later.)

Quite recently here, I speculated on a more sinister take on the “devil in the details”, but Levenchuk provides clarity on the distinction between:

The devil in the details and
an angel in the abstractions.

We need both in different places. The architecting requires knowledge and understanding of the abstractions and which details should be ignored and which are insignificant to that task. The execution requires practical knowledge of more of the details. (In my own post above, the last line acknowledged that when it comes to details what we’re missing are relevance and appropriateness to the matter in hand. Systems Thinking addresses this.)

This is a book about the thinking in advance of the doing. Shaping or architecting a plan for the doing, but neither the plan nor the doing per se.

[I recall many examples of working with planners and project engineers who didn’t get this and forced inappropriate detail just because they could. eg “I know from experience and documented best-practices that our plan will need to include this, this and this, so I’m not going to let you ignore them now.” – sigh!]

Complexity

Complexity is an explicit topic from the outset, in the opening sentence of the introduction:

Systems thinking helps to solve complexity in a variety of projects: it makes it possible to think one at a time about everything important, temporarily discarding the unimportant, but without losing the integrity of the situation, the interplay of these separately thought-out important moments, systems thinking manages attention in complex collective projects.

The idea discussed above, of managing attention to which details are appropriate and relevant where and when are in that first sentence – it’s intractable to think about everything, everywhere all of the time in a complex situation. It’s why, in my own work, I think architecturally. There’s a whole section On Thinking in complex situations generally, which prompted my attention on “definitions” when I first skimmed the book.

Having everything well defined is really only a feature of closed systems where the scope and complexity is relatively simple and amenable to consideration of all details being known in advance. (ie no surprises)

Real projects, real-life human endeavours on any scale are not only complex but because of that complexity they are also effectively open systems. Systems some of whose sub-systems and components will arise from considerations outside the intended scope of the endeavour.

There is a tendency to think of definitions of objects of interest / within scope of any endeavour in terms of establishing well-defined terminology, as critical or fundamental to that endeavour. In fact data dictionaries and class libraries would appear to be predicated on that presumption.

Definitions

Levenchuk has sections on Terminology in his On Thinking chapter, entitled

• • “Words-as-Terms Are Important and Unimportant”, and
  • “Definition: as a Coffin for a Dead Think”

The latter is a play on (or mistranslation from?) Russian philosopher Shchedrovitsky who said “A definition is a coffin for a dead thought”. As noted above, I’d like to think US philosopher Dan Dennett would agree. So long as there is still thinking to be done, a definition of a term referring to the concept of an object in the real world, is little more than a placeholder. In systems thinking, there is always thinking to be done. So much so that Levenchuk even recommends proceeding without using the term to refer to the object, but using language about the object and it’s properties and relations to its real world activities, functions, roles and processes for as long as possible.

In the former, the paradox that terminology is both important and unimportant is first introduced. Despite best intentions, assuming that well defined terms mean well defined concepts and objects ignores that fact that within all but the simplest closed systems – in any real complex system – there are many sub-contexts of sub-systems and multi-discipline divisions of real world knowledge and understanding. Levenchuk says:

The meanings of terms (and any other words, even if they are not called “terms”) are determined statistically, not precisely—and this is done by using them in different contexts. Guesses about the meaning of terms are constructed by studying extended texts describing different situations, by studying different relations of the concepts denoted by these words with other concepts denoted by other words used side by side. When determining the meaning of terms, we do not read definitions, but we examine diagrams, texts, and sets of expanded statements containing the term of interest.

Here he highlights relations, particularly at the level of thought, something that could in fact apply to an ontology of what exists in the world at a fundamental level, being defined in terms of relations, but here we are being more practical. When creating formal dictionaries – say in class libraries for systems integration – it is common to focus on relations to neighbouring types. This is partly for efficiency (it’s always easier  – necessary  – to build on concepts that already appear to have understood working definitions), and partly because avoidance of ambiguity demands that definitions at least distinguish one item from another with which it might be confused. As a result, formal library definitions often take on the very repetitive form of “a B is an A where X applies” however we mustn’t overlook the paradox that despite appearances such formal definitions can never be as precise as we might hope to achieve in a simple closed system.

When discussing definitions more generally, beyond this systems thinking context, where identity may be based on definitions, I often cite “good fences (make good neighbours)” (after Robert Frost) or “think before opening and always close the gate in a fence in the forest” (after G. K. Chesterton). It’s an adage I learned from Magne Valen-Sendstad – the most experienced creator of library definitions I ever worked with. Essentially, bearing in mind the paradoxes that Levenchuk describes above, a good – formal logical – definition is always worth documenting even if it inevitably turns out to be inadequate later in the real world. Boundary disputes are easier to resolve if both neighbours know where they stand and the boundary is a fence rather than a fortress battlement. And also, if you bump up against an existing boundary – a definition – you don’t know much about and it stretches off out of sight into the forest of real world complexity, assume the principal of charity, that whoever put it there had good reason when they did.

On a lighter note, Oxford physicist David Deutsch tweeted agreement this very day:

“The trouble with definitions is that although they can be illuminating, witty, amusing, original and even revolutionary, there is one thing – and perhaps one thing only – which they cannot do: define a thing” George Mikes (English Humour For Beginners)

— David Deutsch (@DavidDeutschOxf) April 3, 2022

Or in our context here:

“The trouble with definitions is that although they can be practically useful, the one thing which they cannot do, is definitively define a thing”

Contingent Conclusion

As ever, anything said is contingent on the future. I have so far read less than 10% of “Systems Thinking 2020“, but I can say it has very valuable content, recommended for anyone wanting to understand why Systems Thinking is important and why it is distinct from Systems Engineering or Systems Project Engineering.

As the author acknowledges, and as confirmed here, the English translation will benefit from native-speaker editing, but is nevertheless accessible.

Gratifying to this reviewer, to find so much real shared experience reflected in an obviously valuable textbook. Recommended, even on this limited review.

(I will read to completion and may extract a list of references and sources?)

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Post Notes:

In a messaging exchange with the author we discover more common ground not included in the current publication, but which is to be part of his forthcoming book.

The idea of “boundaries” which emerge between distinct things in an evolving, self-organising world – using fundamental entropy<>information models – are “Markov Blankets”. My most recent reference on this is Mark Solms in a consciousness context and, although these theories have developed over several decades in Information Science / Theory domain, Solms’ immediate source is Karl Friston. And, Friston is someone with whom Levenchuk and Metelkin already have a working relationship. Small world.

A good deal of my own research – which takes information theories as more fundamental than physical science – is primarily about human knowledge & decision-making (epistemology & cybernetics) in the complex politics of science & psychology, living in the real world.

In his forthcoming work Levenchuk intends to use a more biological / evolutionary paradigm, although he still intends to follow “the pragmatic turn” – whilst I still pursue a metaphysical bent 😉

Levenchuk’s sources include:

• • Clarification of Markov Blankets in Friston context (*)
    http://philsci-archive.pitt.edu/19726/
  • Agency and Homeostasis generally https://plato.stanford.edu/archives/win2021/entries/biology-individual/
  • Open-ended evolution of multi-level systems
    https://arxiv.org/abs/2110.14602

(*) See Follow-up post on review the “Emperor’s New Clothes” paper.

HOLD: One key thing for my areas of interest about the self-organising “individuals” topic and defining their boundaries in words – is that such things can be defined by “categorical” (good / bad / subjective) classifications – whereas most people expect “objective / logical” clarity in definitions – hence important AND not-important.

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Gary Moore would have been 70 years old today.

Every time I see a reference to him, it brings back various memories starting with the (1971) Skid album with Skid Row, and probably a John Peel session or two? Don’t believe I ever saw him live with Skid Row (or Thin Lizzy). 72/74 I was a 6th former, 74/79 I was a student in, and working local to, London. Also had his (1973) Grinding Stone solo album, and 74 was the year he was helping out – regular music press speculation – but not really becoming part of Thin Lizzy. Most of 74/75/76/77 I was following pub-rock band Scarecrow several nights a week (!) with whom Gary jammed every couple of months, when he was in the bar watching them. Later, after 75, I saw him several times across London with Colosseum II and a whole fresh set of guitar-groupies. I had their (1976) Strange New Flesh album.

Most recent memory was being in Ryan’s Bar in Cobh, Dublin port at New Year 2016/17, 5 years after his death. There were two enormous monochrome photo prints behind the bar, one of Gary and one of Rory Gallagher (and no others) so their significance was an obvious conversation starter. Apart from the reminiscences above, I heard about his early times living in Cobh and frequenting that bar.

The memory that always comes up is the night he got the dreadful scar on his face. (Searching the blog it seems this is the first time I’ve documented this memory.) I was always pretty certain it happened in the spring of 75 in the upstairs bar of the Western Counties pub in Paddington where Scarecrow had a weekly residency. I didn’t witness the attack itself. I was downstairs watching the band, but the upstairs bar was an open horseshoe balcony with a wide staircase that swept down right in front of the stage. We certainly heard the commotion and I vividly recall his girlfriend and the blood as people scattered down the stairs. Now it’s possible I’ve conflated two memories – a bloody fight in the Counties and seeing Gary close-up before and after his recent scar. However the details are so consistent with the recollection of Eric Bell – the only documented reference all others seem to depend on – that it happened in Dingwalls, which was certainly a “cooler” hangout than the Counties. Guess I’ll never know now, although Scarecrow guitarist and luthier to the stars, Bill Puplett, could surely disconfirm or otherwise?

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[Post Note: I see why I’m not finding some old references in the blog search. Some of my old pages on musical memories and photographs were on a domain I retired and only temporarily re-implemented. I’d need to rebuild content. In the old days, whilst blog posts were withing the blogging tool DB (WordPress now for many years) pages were most hand-crafted HTML. I’d need to reconstruct that content. The 22 years of blogging remains intact.]

Never actually attempted Kant yet, despite lots of secondary references.

I happen to be reading “Prince of Princes – The Life of Potemkin” by Simon Sebag Montefiore. A bit of Russian history – after a little Russian literary fiction – given today’s interest in historical borders of Ukraine, Poland et al. Not to mention Austro-Hungary, Prussia and the Ottomans. Famously the Russian court of (German) Catherine the Great favoured enlightened culture of French fashion – Gallomania – over neighbouring Germanic influences, and she was particularly involved with the likes of Voltaire, D’Alembert, Diderot and Montesquieu.

The significance I hadn’t noticed was the dates. The mid-to-late 1700’s whilst the Russian court was focussed on the French philosophes, Immanuel Kant was beavering away in Konigsberg, Prussia (Kaliningrad, Russia-ish today) developing his own enlightenment in the midst of all this.

Someone posted this modern rendition of his 1784 paper:
AN ANSWER TO THE QUESTION: WHAT IS ENLIGHTENMENT?

It’s very good. Notice it’s about the process of people – individually and collectively – becoming enlightened, not “The Enlightenment” as a thing per se. This quote:

“The public use of one’s reason must always be free, and it alone can bring about enlightenment among mankind; the private use of reason may, however, often be very narrowly restricted, without otherwise hindering the progress of enlightenment.”

It’s about usage. Publicly you may – must – communicate thought freely, but your own actions, decisions to act on such thoughts expressed, are bound by rules of society. In fact, all the way through he majors on public order. Those maintaining order may be criticised and questioned, but their current authority needs to be “obeyed”. Of course he’s talking in a time when rules are set by priests and princes (and empresses), but nevertheless:

“Argue as much as you want and about what you want, but obey!” Here as elsewhere, when things are considered in broad perspective, a strange, unexpected pattern in human affairs reveals itself, one in which almost everything is paradoxical. A greater degree of civil freedom seems advantageous to a people’s spiritual freedom; yet the former established impassable boundaries for the latter; conversely, a lesser degree of civil freedom provides enough room for all fully to expand their abilities.

Thus, once nature has removed the hard shell from this kernel for which she has most fondly cared, namely, the inclination to and vocation for free thinking, the kernel gradually reacts on a people’s mentality (whereby they become increasingly able to act freely), and it finally even influences the principles of government, which finds that it can profit by treating men, who are now more than machines, in accord with their dignity.

The principles of governance – of individuals within collective systems  – aka Cybernetics.

After several reprints, the latest publication of Dr James Willis (1995) “The Paradox of Progress” is as an e-Book (2022) here at PayHip.

I first reviewed and recommended it back in 2003. At that point I was only a couple of years into my own quest for “a better world model” and Willis as a practising GP was one of the few (non-academic) professionals I found making positive reference to Robert Pirsig “Zen and the Art of Motorcycle Maintenance” in his day job.

The paradoxical perspective we shared was that despite ever more science-led technology and management practice, there was a real sense that we humans were in fact coming off worse.

When I started work at the Middlesex Hospital my senior medical registrar told me that our job in life was to make sure the patients died with their electrolytes balanced. Joking apart, when doctors work to rule there is a grave danger that the rules will do better than the patients.

Here we are at the crux of the paradox. We want to define clear solutions to the problems we can see in the world. But as we do so we progressively destroy the essence of life itself. It seems to be an unavoidable rule that the precise definition of human affairs has the effect of killing humanity itself.

According to Pirsig: “The crisis is being caused by the inadequacy of existing forms of thought to cope with the situation. It can’t be solved by rational means because the rationality itself is the source of the problem.”

Rather than treating rules as “tablets of stone” to be enforced by technological implementation it was clear in human terms that rules really were there to be broken, with care. That “rules are for guidance of the wise, and the enslavement of fools” has become a mantra of mine. That, and the fact the problem lies in the received wisdom of our own rationality, misunderstanding ourselves, has been a driver of my own research and writing ever since.

The seriousness and scale of that problem for humanity as a whole has done nothing but grow in the two intervening decades. Yet Willis book is highly readable & witty and, with a career’s worth of practical learning through anecdotes between doctor, patients and caring colleagues, both moving & funny. Still highly recommended.

I am at last re-reading Mikhail Bulgakov (1929 / 1966) “The Master and Margarita”. The first time I started (and failed to complete) reading it in April 2017 I said this:

All I can say so far is M&M’s seriously weird and compelling. Some cross between Salman Rushdie’s “Satanic Verses” and Neil Gaiman’s “American Gods” but written in 1930’s Soviet Russia!

Mentioned it in October 2019 again in a Salman Rushdie context, but still had never read it. Strangely my first mention of it was back in December 2007 on a singularly unimpressive recommended book list. (Note: it was only published in 1966, first translated into English in 1967, mine is a 1995 Picador version of a 1993 translation, but it was originally written and constantly revised under censorship from 1929 until his death in 1940. The published version is stitched together from multiple credible drafts. Wikipedia.)

I’m beyond where I got to before, and recognising the humour amidst the weird “Russian Gods” ghost story. Wish me luck.

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[Spoilers alert.]

OK, so having read the whole over ~5 days, I have to say it is very good, even though I’m ultimately disappointed in terms of gleaning much new for my own agenda.

It’s clever and witty, and easy to see why it was subversive and blasphemous under Soviet political constraints, not to mention the ladies regularly divested of their underwear?

As I read it, the real hero in this alternative reality is Pontius Pilate who had the empathy and nous – and power and connections – to save the vagrant philosopher from his crucifixion and avoid the need for supernatural (ie. it never happened) reincarnation and ascension, though the writing of this possible outcome remains unfinished within the plot. Art & Literature is full of variations on how the good prophet would have done better without his supernatural ending. Anyway, as the epilogue points out most of the satanic back-magic of the plot never happened either, almost all can be explained by trickery. Slightly annoying over-use of the multiple accidental and deliberate fires meme to destroy documentary evidence (or not?) along the way. Lots of allusions to Faust and Dante. The perspective of flying over the scenes. Fairly obvious tension in the recurring “the devil must exist” – how can there be good without evil, etc. Everyone reporting the supernatural risking being carted off to the asylum, etc. The historical, political and cultural satire in the characterisation and naming of the cast of cats and ghosts, and in the locations from Yalta to St Petersburg via Kyiv and Moscow, is apparent.

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Reading the commentary notes afterwards, I don’t think I missed many?

As a cult novel, you can also see the use of the location names and quotations from the text in popular culture. “Sympathy for the Devil” being the most quoted. Many dramatisations exist.

Here an interesting BBC R3 Forum discussion. – actually a very comprehensive discussion of all the main themes with lots of spoilers – skip the trailers and news at 23 to 26 mins – highly recommended listen.)

The devil in the details may be the only aspect I can take away into my own agenda. It being literally true that:

“The devil is in the details,
the angels are in the abstractions”

What did I miss? Not much it seems.

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The night before last, I completed
Mark Solms (2021) “The Hidden Spring
– A Journey to the Source of Consciousness“.

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The Preamble / Previously on Psybertron

• • • April 2021 – I first mentioned receiving The Hidden Spring, but maybe not having enough bandwidth to read it. It didn’t stop me recommending it on the strength of the index and references, and the title of the appendix “Arousal and Information”. [I had previously mentioned hearing Solms speak and ordering the book (in a link to a “Social Autism” post inside the one above) but I had also made a link to Solms, Friston and Markov-blankets in a post-note to this “Identity Politics / Good Fences” post. It’s all connected.]
    • July 2021 – I’d started reading it here in this “Brain Architecture” post. I recall now why – aside from other priorities – I stalled. Brain anatomy is necessarily complex at many levels of detail and abstraction in 4D space-time, even for a practicing neuroscientist I suspect. For generally informed science readers, we really do need a more general-purpose Brain Atlas – and it absolutely must have a systems architecture perspective?
    • December 2021 – I remembered that I had it unfinished, alongside my readings arising from Iain McGilchrist “The Matter With Things”. (And again here, though in fact there is no reference to Solms (nor Friston!) in TMWT. Just me making connections.)
    • 1 March 2022 – I finally got stuck in to reading The Hidden Spring.
    • 4 March 2022 – on completion of Chapters 1 to 6. The Mid Brain Decision Triangle. The evolution of consciousness in key mid-brain structures.
    • 6 March 2022 – on completion of Chapters 7, 8 & 9. The Homeostasis / Information model of the subjective experience of consciousness. Plus “crossing the Rubicon” needed for sceptical scientists.
    • 8 March 2022 – Today – This post on completion of Chapters 10, 11, 12 & the Postscript (a neat summary in fact) and the Appendix (Arousal & Information). Repairing the cortical fallacy, addressing the hard problem and yes, given the architectural solution, artificially constructed minds are indeed possible in principle.

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The Review

That Conscious Feeling

Human exceptionalism? I’m not one of those that deny the human species being special. We are very special in terms of our roles and responsibilities in the cosmic ecosystem. However, what has tended to happen, even amongst those scientists that see humanity as a temporary local difficulty amidst their gods-eye view of the whole of objective reality, is that we get blinded by the obvious fact that the ascent of man has been accompanied by development of the relatively enormous cerebral hemispheres in our great-ape lineage.

This has led to a prejudice – the cortical fallacy – that all the important aspects of our undoubted higher intelligence, rational capabilities and social complexity as a species must be primarily associated with these hemispheres, or at least as the default place to start to look for explanations. It’s not that modern neuro-scientists don’t actually understand this, simply that this perspective is baked into so many resources. Some of the alternatives are equally caricatures – that our animal instincts are built into lower / animalian / limbic / reptilian brain structures – and that these emotions are therefore somehow inferior (bad) relative to our “higher” (good) rational cortical capabilities.

The first six chapters of Solms’ book thoroughly nail this:

Our intelligent consciousness, on which we rightly focus as key to our highest intellectual capabilities and our models of how we work as intelligent beings, is thoroughly embedded in our mid-brain structures. Specifically Solms identifies the Mid-Brain Decision-Making Triangle (after Merker) – the “periaqueductal grey” (PAG), the “superior colliculi” (SC) and the “reticular activating system” (RAS) in the “mid-brain locomotor region” as the very source of our sentient being (after Panksepp). This subsystem is constantly processing a three-way Bayesian appraisal and orchestration of priorities of inputs (in SC), with feelings (in PAG), with available options (in RAS). Where of course, the great majority of component inputs are actually the results of our internal simulations of the options, and the great majority of the processes are subconsciously (semi-)automated. The elements brought to our conscious attention are the exceptions (surprise departures from prior expectations a la Bayes) which we sense as feelings – qualitative / categorical / good / bad – and which guide those decisions.

Consciousness “is” affect.
It’s feeling all the way down.

How do I feel
about what I know
and what, if anything,
should I do about it?

For the science – the biology, the neuroscience and the psychology – that really ought to be it.

[Post Note Jan 2024 – this Dr James Cooke video conversation with Mark Solms is a pretty comprehensive summary of his position. Cooke’s own summaries “absolutely pivotal” says Solms.]

All Solms’ empirical resources and rational arguments follow the orthodox and thoroughly referenced considerations of those sciences over several decades. Now, having demoted the hemispheres and promoted the subjective, there a quite a few corollaries and loose ends he goes on to resolve.

The Point of Life Itself

The first avenue is that whilst the whole of the above stands fine with neuroscience and psychology as biological sciences, it is fully supported by the more fundamental sciences of physical systems generally. How life itself arises from the self-organisation of non-living systems and how the basics of conscious intelligence are a natural part of that evolution. Prompted by the work of Karl Friston (since 2010) and working together with him (since 2017) Solms elaborates in this biological neuroscience domain the arguments rehearsed over many decades in the information science domain. (For that reason I can only skim over the topics here, but if the terms are not already meaningful to you, Solms provides as good a case as I’ve seen outside information science.)

Life as the battle against entropy.
Entropy as an informational property.
Consciousness as part of the armoury in that battle.

Homeostasis: The efficient minimisation of free-energy. The self-organisation of a system, an organism, as an entity bounded by a so-called Markov-blanket, with as many sub-systems as may similarly emerge ad-infinitum. The independence of each system / sub-system processing its internal resources yet “sensing” external information at its boundary. The irony of this information processing line of thinking – a computing machine with algorithms –  which appears to reduce life and consciousness to mechanistic processes and yet it is these Markov-blankets separating the levels which ensure the qualitative categorical existence of the emergent entities.

Solms provides an excellent extended metaphor of an engineering organisation set-up to maintain a leaky dam protecting a local community – the little Dutch boy (girl in Solms’ case) comes of age.

If that weren’t impressive enough, having emphasised the “feeling” nature of consciousness as affect in the first half of his book, Solms shows that – considered as such a subsystem – the mid-brain decision triangle providing these intentional, intelligent capabilities of consciousness is itself our subjective experience of it. It’s worth dwelling on that.

We have an explanation of
how our consciousness works
and
we have an explanation of
our subjective experience of it.

Having effectively disposed of qualia and the hard-problem en-passant, he does pay much respect to David Chalmers influence on his earlier thought journey throughout as well as spending a full 30 pages on arguments arising from Chalmers’ work.

The Home Straight

He sets the record straight on the cortical fallacy and this from the opening of Ch10 probably says all that needs to be said:

“As we have seen repeatedly throughout [the book], the cortical fallacy has a lot to answer for. Had the pioneers of behavioural neuroscience not been so impressed by the large expanse of our cortex or been so blinded by the philosophical idea that mental life arises from associating memory images, we might have discovered the real source of consciousness a good deal earlier. It is a tantalising irony of the history of mental science that Freud possessed so many pieces of the puzzle more than a century ago. The clues, both neurological and psychological, were staring him in the face. But when it came to consciousness, even he fell prey to our collective fixation with the cortex – an obsession whose cost, in case we forget, may be measured in more than just wasted time.”

This reminder of how much damage has been done by misunderstanding and misapplying our own received rationality in the past century or more is similarly echoed in Iain McGilchrist’s recent work “The Matter With Things”. Like Solms, McGilchrist also documents the damage caused by the cortical fallacy. Entirely complementary to Solms’ focus on the higher(newer)-lower(older) distinction, McGilchrist’s focus is on the left-right brain differences mediated by the lower(older) structures. Both bring a fundamentally systems architecture perspective to understanding how our minds work and how our misunderstandings of our minds’ subsystems are leading us astray.

Given the scale of such a change in human understanding, it is perhaps un-warranted icing on the cake that Solms also demonstrates that the same arguments can be applied to the creation of artificial minds. However, I can only echo the existing blurbs for “The Hidden Spring”

“A remarkable book.
It changes everything.”
– Brian Eno

Solms’ vital work has never ignored  the lived, felt experience of human beings. His ideas look a lot like the future to me.”
– Siri Hustvedt

The big challenge is precisely there, and Solms acknowledges it.

Crossing that Rubicon

He calls it inviting the scientific sceptics to “cross the Rubicon” with him. Without that it will change nothing and the future will look the same as the past.

“[Mind is primarily affective, felt subjectively.] To rule the subjective perspective out is to exclude from science the most essential feature of the mind.”

Solms (and I too, having called this hurdle “Catch-22” for decades) invite you to take that perspective of subjective self-hood, the one you already “have in mind” into your scientific considerations of mind.

“I am asking you to replace the third-person objective perspective we have taken so far on the dynamics [of the neuro-science] with a first-person one: with the subjective perspective of the self-evidencing system itself. I am asking you to adopt the system’s point of view, to empathise with it.”

Without accepting that shift of perspective, we are indeed ruling out scientific progress in understanding our minds.

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[Post Note (May 2023): In response to a thread where otherwise intelligent people were simply denying in ignorance that Solms could possibly have any explanation of such things as consciousness and pain / colour / qualia, Solms interjected this:

“Dual-aspect monists (like me) don’t believe that these correlated subjective & objective phenomena *cause* each other, in either direction. Rather, they’re the products of two observational perspectives upon one & the same part of nature. Nociceptive neural transmission and neural responses to it are one perspective; feelings of pain are another perspective.”

Me too. End.]

Just completed Chapters 7, 8 & 9 of the Hidden Spring, having been looking forward to 7 when I finished 6, here. Wow, this is good stuff from Solms.

The contents / subjects …

• • Free Energy Principle – Homeostasis, “self-evidencing” in self-organising systems, statistical thermodynamics, entropy and information, efficiency. Markov-blankets between self-organised layers, two-way / circular causality.
  • Predictive Hierarchy – exploits these layers – more efficiency. The emergent objects (wrapped in their blankets) really are part of the functional / causal processes, without elemental reductionism. The contents of any Markov blanket are highly self-contained. (As an engineer myself, this is pure systems thinking.)
  • Consciousness Arises – subjective consciousness too(!) – *BOOM* – how could it be any other way?

So much to agree with just a few meta / detail points & questions:

Efficiency as a driver? (Tim Kueper was sceptical about this in a previous exchange. The kinematic teleology is in the self-organisation, the homeostasis, free-energy efficiency is simply the mechanism. Does that help Tim?) “All the ‘quantities’ in a self-organising system that can change will change to minimise free energy”.

That “self-evidencing” is so important – counter intuitive like the directions of information flows in the first 6 chapters – most “information” about the outside world comes from inside our heads. It really does.

This is all very recent from Solms. Up to Ch6 it is mostly his career experience in “neuro-psycho-analysis“. But these chapters all arose out of seeing Karl Friston give a “Life as we know it” presentation at Wellcome / UCL in 2017, working with him on a joint paper thereafter and creating / publishing this book in 2021. Astonishing how quickly things fit into place. Even starting with an information systems bias I’ve been navigating this minefield for 20 years. (I’ll come back to the minefield / Rubicon / catch-22 / leap-of-faith element later. It never goes away.)

As well as dedicating the whole book to Panksepp, Solms credits Friston by prefixing his name to several of the effects he names here (eg “Friston’s Free Energy Principle”, Friston’s Law, etc).

Having been aligned on so much up to Ch7 he reports that Damasio parted from the mechanistic / reductionist implications of “algorithms” that flow through 7, 8 & 9 (& the Solms-Friston paper itself). It’s a common fear.

QUESTION to Mark Solms :- I wonder if Damasio might reconnect with this thesis if he sees the qualitative / categorical nature of the algorithms (p193) as opposed to long causal reductionist chains of classical objects? More heuristics than formal algorithms?

As well as Friston & Damasio – every other source in there. Markov (& Tolstoy), Shannon, Sacks, Wheeler (it from bit), Kant, Darwin, Wiener (cybernetics), W Ross-Ashby(!), Gibbs, Helmholtz (but not Boltzmann or Mach), Freud (but not Maslow), Varela. Wonderful stuff.

Ergodicity – it’s been my favourite concept since 2017 – he uses ergodic and non-ergodic a couple of times in a long  Friston quote (p162/3) without any definition or clue to intended meaning. (2017 a coincidence, no parallel connections). Mentions it again in another Friston quote (p170) with “An ergodic system occupies limited states”. And then relies on this to conclude that all (biological) self-organising systems:

• • 1. are ergodic
    2. have a Markov blanket
    3. exhibit active inference
    4. are self-preservative

Apart from questioning whether that is the whole intended meaning of ergodic here (?) the active inference is absolutely key. Internal models / algorithms are constantly checked against external sense data, to improve the ongoing model (as well as fix the current homeostatic error)! (This is taking me back to 1989-ish.)

(Whether that’s all there is to ergodicity may not matter here, the key thing is it supports the limited qualitative / categorical options available to our sub-system rather than quantitative resources from across an entire population of all fine-grained options over the map.)

Anyway, joining up these free-energy / homeostasis arguments with the previous six chapters:

“The mistake most cognitive scientists make is that they assume most incoming data is ‘exteroceptive’. They forget that expectation errors (sensory inputs) that matter most to us come from within.

These signals generate ‘affects’ not perceptions. As Freud said, the forebrain is a ‘sympathetic ganglion’. Confusion on this score is the perennial price most cog-sci’s pay for adopting the cortical fallacy. Consciousness is endogenously generated, all of it. Consciousness at source is affect.”

“Affective valence – our feelings about what is biologically ‘good’ and ‘bad’ for us – guides us in unpredicted situations. We concluded that this way of feeling our way through life’s problems using ‘voluntary’ behaviour is the biological function of consciousness.”

That leaves me with one clarifying thought

QUESTION to Mark Solms: – those feelings of affective valence are about what is good or bad for us biologically including psychologically / mentally? ie Useful work for free energy includes thinking (feeling) about our thinking as well as as thinking (feeling) about our acting in the world?

There’s a good deal of rehabilitation and building on Freud – beyond the usual caricature of dreams and parental influence (where Solms started in fact) – in areas where he really was ahead of his time on how brains / minds work. Solms (and Friston) developed formal set of equations (using Freudian notation) to describe the algorithmic information behaviour between the various brain states in play, neatly summarised in “Fig 17” where that “mid-brain decision triangle” behaviour is laid bare. It does look bonkers to “reduce” mind to such a simple graphic information flow diagram of a few equations(!) no less – see eg Damasio’s reaction earlier – but with the right perspective on the affective categorical variables in play, and accepting the infinite sub-divisibility of the reality of sub-systems within any Markov-blanketed system we choose – it really is credible and convincing (it’s the delegated / permissive supervisory control system I described at the end of the previous post.).

(c) Mark Solms.
(I need to create a slide version of that with more labelling in the graphic itself.)

THE PROBLEM, as Solms elaborates in the closing pages of Ch9, is what he calls inviting scientific sceptics to cross a Rubicon. As noted earlier this tricky step never goes away from this debate, philosophical or scientific. I’ve been calling in Catch-22 for two decades, but whatever language you choose:

“[Mind is primarily affective, felt subjectively.] To rule the subjective perspective out is to exclude from science the most essential feature of the mind.”

Solms (and I) invite you to take that perspective of subjective self-hood, the one you already “have in mind” into your scientific considerations of mind.

“I am asking you to replace the third-person objective perspective we have taken so far on the dynamics [of the neuro-science] with a first-person one: with the subjective perspective of the self-evidencing system itself. I am asking you to adopt the system’s point of view, to empathise with it.”

DO NOT PASS GO.

(A little under 100 pages to go.)

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Post Notes:

In that year-old post where I first referred to Mark Solms – as something that looked important even if I didn’t find time to read – I was clearing out lots of bookmarks that were choking off any sense of making progress. One of those book marks was to this piece by Karl Friston et al on the switch from Cartesian Dualism to “Markovian Monism” – and it includes variations on that Fig 17 above. It’s all connected!

Also had a response overnight from Solms on the two questions above:

Excellent. Thanks for your response.

Having now completed it, I find my second question is thoroughly answered in the next chapter. Will compile a fuller review.

— What, Why & How do we know? (@psybertron) March 7, 2022

That later Damasio reference:
Man, K. and Damasio, A. (2019) “Homeostasis and Soft Robotics in the Design of Feeling Machines”. In Nature Machine Intelligence, I: 446-52, doi.org/10.1038/s42256-019-0103-7
If he’s OK with “feeling machines” it sounds like he’s lost his aversion to the risk of reductionism in mechanistic algorithms 🙂 Yay!

(Earlier 2010 Friston reference in there too – unfortunately the Nature Reviews – Neuroscience papers are not free access.)

On to a fuller review of Solms.

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