Epistemology & Being III

Our Understanding of Reality and the Consequences for Theory

The Emergence of an Alternative?

True scientific thinkers were always aware of the patchy nature of their studies, and determined to go beyond what had been extracted, to attempt an Explanation of why things were the way that they were.

This was a significant development! Essentially, Mankind had been using his Knowledge of Reality, without understanding its causes. His techniques were descriptive rather than explanatory, and knowing what-happens-next was sufficient for a successful intervention.

But, by asking, “Why?”, he was requiring a great deal more!

He was impelled upon this path, because, if he could “understand” the reasons for things, he could apply them elsewhere in analogous situations and build a coherent, comprehensive structure of explanations, which would certainly truncate the long-winded process dependant ONLY upon inexplicable description alone.

And, for a while, these Explanatory scientists were highly successful (if only in very limited areas), and their explanatory contributions did make significant contributions.

But, of course, they had to be insufficient or even downright wrong! Depending, as they did upon a framework of “do-able” studies, their attempts at explanation were too narrowly based to ever deliver the “full Truth”.  Each and every Theory was always compromised, and could be no other. But, these scientists soon realised that though their contributions were incomplete, they necessarily contained significant “objective content”.

They were NOT mere fictions, but always delivered something of real value.

These real scientists expected their Theories to be superceded by better ones, and indeed embraced the approach, which came to be called The Scientific Method, wherein hypotheses (probable theories) were purposely subjected to attempts at disproving them by experimental testing “to, and beyond, their limits”.

This led to the demolishing of clearly incorrect theories, but also stretched some theories to extended areas of applicability, and even led to improving modifications where the evidence merited them.

They approached a much deeper understanding of the relation of their Theories to the “Truth”. All “truths” achieved by the normal, pluralistic methods were clearly “relative”, “partial” truths, and subject to updating, or even total replacement.

But, sadly, even this improvement turned out to be insufficient. All this work was still based upon other long established assumptions that were intrinsically flawed, and THE most profound flaw appeared in the occurrence of cataclysmic Events of Change, which came to be called Emergences.

Indeed, these were precise Events, as were mentioned earlier, such as the Origin of Life on the Earth!

The Bottom-Up approach could NOT deal with Emergences.

Why was this?

The whole method, being pluralist, depended upon the identified “constituent Parts”, which made up a given situation, but these were destroyed as such in an Emergence. They simply ceased to exist, and the laws relating them meant nothing any more. The very things we would need to “explain” the new situation were no longer available. We had NO bases for explaining the turnover. Our methods did NOT deliver the real Truth, but instead a truth relative to a particular set of circumstances that now NO LONGER APPLIED.

New forms, entities, relations and, indeed, laws appeared “out of the woodwork” – at least as far as our “understanding” was concerned.

The new Level that appeared could NOT be dealt with purely in terms of our Lower Level entities, relations, processes and laws. What had occurred was NOT explicable in terms of our current Knowledge, because it was, and always had been, INCOMPLETE.

Now, if that was not enough to scupper an investigation of the newly emerged Level, there was a further complication. The new Level actually began to constrain, if not determine, those prior, lower-Level processes. There was an irrefutable top-down mediation of “now contained” lower level processes.

How on earth could our current assumptions cope with that?

There are millions of examples of this, but I must at least mention one.

On the pre-Life Earth NO free Oxygen could exist in the atmosphere. Oxygen is very reactive, and any that became available, by any means whatsoever, was immediately taken up in what are called oxidation processes, and ended up as solids embedded in the geological accumulations of the ground itself. The atmosphere, replenished by natural, non living processes, was mainly of volcanic origin. There was NO free Oxygen at all.

But, early living things changed all of that. Photosynthesis, in plants, using sunlight and available Carbon Dioxide, produced Oxygen as a waste product in their cell building processes, and this proliferated to such an extent that, in spite of continuing oxidising processes, the amount of free Oxygen in the atmosphere increased until it became a substantial and transforming proportion. There is even clear evidence that it, at times, was much greater than it is now (currently about 20%). And this process was ongoing. Any reduction, due to other processes, was continually offset by new productions by the plant biomass.

For the first time in the history of the Earth, free Oxygen was maintained at a substantial level in the atmosphere. This revolution had changed its own context. Situations emerging due to a given context had then proceeded to change that context substantially. And, this meant that new things could happen that were impossible previously.

Indeed, Life, which caused the situation, could thereafter develop in entirely new ways. Oxygen breathing animals could evolve and fill the empty Land areas without the need for what had been essential before – the ocean environment.

This tale reveals the significance of Emergences. Following such an Event, entirely new forms appeared which could NOT be explained in terms of the pre-Emergence processes.

Emergences were, and are, Creative!

The Necessity of Holistic Science And a wholly New Methodology

Now, these profoundly important Events could NOT continue to be ignored. And an alternative approach to Reality, based on Holism, also had to be resurrected. Not, obviously, the old impenetratable Holism of antiquity, but one based on the recognition of its paramount role in the Evolution of Matter – the development of Reality.

Plurality had to be relegated to a purely pragmatic methodology that took the obvious unevenness of Reality, and constrained its more amenable areas for detailed study, and the subsequent construction of initial, obviously, limited models of these areas, as a first step towards a more general understanding.

To complement this scheme of work, it has become evident that the complementary study of Emergence is the most important direction to take in revealing the imperatives of a holistic world.

Certainly, the significant failures of pluralistic science were revealed by Emergences, and also have significantly redirected our conception of the nature of Reality, AND, importantly, of our understanding of Reality.

This paper was written in response to an article – Essence of Thought by Gregory T. Huang - in New Scientist (2658) about the Human Brain. The scientists involved were undoubtedly and unconsciously, pluralist, as described above, and could not see that their methods were incapable of transcending the mechanisms of Lower Level systems. They believed that they could find their “Theory of Everything in the Brain” via Neural Nets and brain localities, but because they are as mistaken as the Physicists, who expect to find their Theory of Everything in Strings of Pure disembodied Energy (or some other purely mathematical forms), they too must fail.

Soon as we look at Human Understanding in its present state, we see the products of past Emergences in ALL subject categories, be they Physics, Biology or Chemistry, or in Neurology, Psychology and Psychiatry. Each and every area is determined by its own Emergent Event, and no-one can, no matter how hard they try, use their current, pluralist methods to bridge the gaps.

Obviously, this paper is but a preface to one that takes the positions expressed here into a critique of the article that precipitated this reaction.

Back to Part 2

Understanding Intelligence?

If I was going there, I wouldn't have started from here!

Photograph by Mick Schofield

The expression "You can't see the Wood for the Trees!" is ever resonant in the ways that we usually consider the World. I never realised it before, but it relates to our profound belief (our assumption) that Plurality is the way of the World; that the essence of all phenomena is contained within their "constituent Parts", and the converse of this - that properties of the Whole can be totally reproduced by means of the mere provision and juxtaposition of all these Parts.

Indeed, the major criticism of Plurality is that it exactly equates the Parts revealed, isolated and extracted by artificial erection of Domains, with its "brother" relation, as it exists, in the coherent real World Whole.

But, of course, that is NOT the case! It is merely a "useful" simplification used by scientists.

No matter how much we learn about the specimen forms of trees, grown in splendid and perfectly arranged isolation, such knowledge can never reveal, from that alone, the full full qualities of the Wood or Forest.

Yet, this assumption is ubiquitous (hence the saying above to counter it), and once you realise it, clear cases of it appear absolutely everywhere, and then stick out like sore thumbs, where previously they were "invisible". In a recent New Scientist (2784) there is an article entitled The 12 Pillars of Wisdom which is introduced in the very first sentence with:

 

    "Can we ever understand intelligence? Only by building it up from its component parts"

The point is proven, is it not?

Now I could belabour the point throughout the whole length of that contribution, but I won't. The key point necessary has been made! Clearly the writer believes he is going to bring together as many aspects of "intelligence" extracted by various pluralist means, in order to deliver the nature of intelligence. But that is impossible. Many new things may be there, and the article will be worth reading for those things alone, but they will not, and indeed cannot deliver the secret of intelligence!

That would certainly involve a very different approach grounded soundly upon some understanding of the episodes of revolutionary qualitative change known as Emergences. For only when we begin to grasp how all such changes emerge, NOT as the consequence of the mere juxtaposition and summation of only small incremental changes, but as the reality-changing result of dramatic revolution.

I, Algorithm

(or Artificial Intelligence with Probabilities)

This article in New Scientist (2797) by Anil Ananthaswamy describes how the old (and now dead) Artificial Intelligence based on Formal Logic and Neural Networks has been re-vamped by the inclusion of Noise and Probabilities. It is, I’m afraid, not a new and great step forward, but an old “solution” to the unanswerable problem, “How do you improve upon a purely formal and pluralistic, and hence totally unchanging, artificial system, which is intended to deliver some sort of machine- based intelligence?”

So, instead of strict determinism only, you merely need to add a bit of random chance, and then deal in the probabilities of various alternative outcomes.To put this new system into the language of the participants, these new systems of Artificial Intelligence “add uncertainty to Formal Logic – in order to reason in a noisy and chaotic World”. It is a proposed “new” application of the same standpoint as was used in the Copenhagen Interpretation of Quantum Theory almost a century before. But the real world is NOT basically deterministic PLUS “noise”! It is holistic! And to attempt to analyse it pluralistically is doomed to failure. So the trick, as usual, is to continue with that old methodology, but to heighten the “flavour” with the added “spice” of Random Noise and the coherence of Statistical Methods – using averages and probabilities on top of a still wholly deterministic basis.

Now, to echo the revolution that occurred in Sub Atomic Physics may appear to be an important development, and in the same way may allow better predictions in this sphere as it did in Physics, but in BOTH areas it certainly does NOT deliver the Truth! In this particular instance it seems to apply very well in the area of infectious diseases, but we have to be clear why it works there, but also, and most importantly, why it isn’t the general solution that it is claimed to be.

It works when many factors are acting simultaneously, and with roughly equal weights. In such circumstances many alternative diagnoses are available, and hence various distinct results are possible. The important question is, “What is the correct diagnosis in a given particular case?”

Now Neural Networks had delivered a system that could be modified to more closely match real weightings of various alternative situations, but they were crude to say the least: absolutely NO indication of why and how these changes were effected were revealed. It was merely data without a cause!
Now this new version of AI returns to such ideas, but adds the 1764 ideas of Bayes embodied in the Theorem which carries his name:- which is,

if the conditional probability of Q implies the conditional probability of P
then
the conditional probability of P implies the conditional probability of Q - [Bayes Theorem]

And this was for the first time a basis for being used with Causes and Effects, not only in the usual direction but backwards too (that is diagnostically).

The constructed systems were so-called Bayesian Networks, where the variables were initially purely random, that is of equal weight, BUT thereafter dependant on every other involved variable. Tweak the value of one and you alter the probability distribution of all of the others. Now, this, on the face of it, appears to be very close to Holism, but has a clearly fictitious starting point, where all are equally probable. The “saving grace” was then that if you knew some of the variables you could infer the probabilities of the other contributions. Now, when you think about it, it doesn’t seem likely. Starting from a wholly fictitious starting point, why should the inclusion of some reliable data move ALL of the probabilities in the right direction? Clearly such systems and associated methods would have to be very close to Iterative Numerical Methods, and hence dependant on a convergent starting point for a useful outcome. And, as with such numerical methods, these too needed to be refined and improved until they began to become much more reliable than prior methods.

Even so, it is clear that such methods are full of dangers. How do you know whether you are considering all the necessary factors? Gradually researchers began to produce models in certain areas which were much more reliable. The key was to build them so that new data could be regularly included, which modified the included probability distributions.

But, as it did not deal with answering the question, “Why?”, but only the question, “How?”, it was still dependant on the old methodology, even if it was overlaid with Bayesian add-ons.

Indeed, to facilitate such programs, new languages began to be developed specially designed to help construct such self-modifying models.
To give some idea of their powers AND limitations, it is worth listing the principles on which they were based.

1.Equal likeliness of all contributing factors must be the starting point
2.Algorithms must be very general
3.New data must be straightforwardly included to update the probabilities.

Now, this is clearly the ONLY way that the usual pluralistic conceptions and analyses can be used in a holistic World. The basis is still Formal Logic, but real measured data can modify an initial model in which everything affects everything else, but as to how they do it, there are NO revelations. The ever-new data merely adjusts less and less arbitrary figures, and, by this alone, the model improves. The model learns nothing concrete about relations, but improves as a predictor, based on regularly updated data.

Nevertheless. There could be no guarantees. It is a pragmatic method of improvement and NOT a scientific one.

Also experience has shown that the gathering of new data can be altogether too narrow, and the seriousness with which it is collected much too slight for the methods to always be depended upon. Behind the robot diagnostic program, a very experienced “doctor” would certainly come in handy!
There is also the problem of ”current ideas” guiding the actions of the data collectors, and hence “tending” to confirm those current ideas. You cannot discover a new cause, if you are not measuring for it, can you? The method is NOT a genuine holistic one!

And the most important omission has to be that Time and Trajectory are not part of the schemas. Miller’s famous Experiment was indeed holistic, and produced amino acids from a modelled holistic system, but it too lacked Time and Trajectory information. This author’s (Jim Schofield) redesign of Miller’s Experiment has the same core set up as in the original, but surrounded by a time-triggered set of diagnostic sub-experiments, regularly sampling what was present at crucial positions throughout the set up and throughout the whole time that it was running. The results would then have to be laid out on a series of related timelines, showing WHAT was present and WHEN. The relationships over time and place would then be available and sequences and even cycles of processes could be revealed and interpreted.

The half-cock nature of the latest version of model based on Neural Networks but involving Bayesian principles, though it will produce ever better simulation-type computer programs, is still immovably grounded on pluralist principles, and so will be limited in its applications, and most important of all, will REDUCE the amount of real analysis and explanation to the Lowest Common Denominator of “the computer says that…..”