Showing posts with label Probability. Show all posts
Showing posts with label Probability. Show all posts

16 November, 2015

New Special Issue: Thinking About Thought



This work is part of a long study, primarily into Sub Atomic Physics, but also, necessarily, taking a detailed philosophical look at the trajectory of ideas over significant stages in its recent history, which have, finally and irrevocably, moved it over, bodily, from a steadfast materialist standpoint to an almost completely idealist one.

This initial preoccupation has led to further research into specific extra areas, which are not the usual ground for Philosophy, but here, in this truly, momentous Crisis in Physics, they have become absolutely paramount. The Ground of Science is addressed particularly in its underlying key – The Principle of Plurality, but also in its congenital feature of Pragmatism, and its beliefs, taken from Mathematics, as well as its many purely pragmatic tricks, always justified by “If it works, it is right!”

The trigger for this set of papers was a criticism by David Deutsch in his paper, “Definitely not Maybe” in the New Scientist magazine (3041), about the role of Probability in the Copenhagen Interpretation of Quantum Theory. And, this inevitably pulled in more general assumptions too. Clearly, this Special needs to be taken along with the whole extended body of work, by this philosopher, – all of which are available in the SHAPE Journal, Blog and Youtube Channel.

08 September, 2011

New Special Issue on Form & Probability




This Special was a commendable task!

It was intended to reveal the nature of statistical and probabilistic Law as a special type wedded indissolubly to experimental evidence, and the revelation of this was to be a plank in the final and complete criticism of the Copenhagen approach to Science, as put forward by Bohr and Heisenberg. And it is a contribution to that objective! But, it certainly isn’t, as yet, part of a comprehensive argument.

It got deflected into absolutely necessary component issues, and diligently followed various lines, that were revealed as having to be solved to have any hope of completing the full task. In such crucial reversals of methods a whole range of component issues have to be addressed prior to a final integration: The terminally ill but not yet dead semi-copse has to be seen to its final demise, before we bury it for ever!

I am sure that this offering will energise others, as it has this writer, for the task is essential, and the rewards will be prodigious. Sub-Atomic Physics was wrecked upon the rocks of real Qualitative Change and the emergence of Levels within the development of Reality. And such problems (in all areas of Science) will only be properly addressed when the problems raised in this area of Physics are finally solved for good!

05 March, 2011

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…..”

16 August, 2010

Review: The End of Incremental Evolution?

Accidental Origins (New Scientist 2751)


Yet another article has appeared but this time adding a rather different gloss to the usual consensus interpretation of Natural Selection, but instead of the usual cashing in on a world celebrated anniversary, this one does add something of real value.

In Accidental Origins published in a recent issue of New Scientist (2751), reporter Bob Holmes introduces us to Mark Pagel, who along with his colleagues, has uncovered a fatal flaw in the assumption of large numbers ofvery small, incremental steps which alone are supposed to deliver the crucial process of species change via Natural Selection. Though many others have questioned this tenet of Natural Selection, Pagel is different because he uses the same standpoint and methodology as his opponents to demolish their position. He uses a mathematical analysis of data derived from available evolutionary sequences to show that they could not have happened in the assumed way. But importantly, the significance of his results also, in fact, reaches well beyond Natural Selection to a whole range of “theories” based on the same sort of assumptions throughout present day Science, and so his contribution is significant for Science in general.

He reveals a significant hole in this form of explanation by showing that the concrete results do NOT have the actual “shape” that would be unavoidable from large numbers of small steps. Indeed, he goes on to demonstrate that the nearest idea that matches the analysis, is that species change is caused by a single accidental event rather than the assumed gradualist drift.

But, taking a step away from the individual problem Pagel addresses, we must more generally separate out quantitative derivation of formulae and its ability to accurately predict, from the usually following explanatory theory. Most scientists today feel that the initial stage is actually the “real nitty-gritty”, and the explanatory phase is merely some sort of rationalisation. Once a means of prediction is in their hands, the scientific process is presumed to be “complete”, and all sorts of questionable rationalisations are considered sufficient for the final “window-dressing”, explanatory phase. Returning to Pagel’s work, it is clear he has totally undermined this overall approach, at the same time as his contributions to Evolution, ALL other similar rationalisations in many other important areas of modern science must also be seen as subject to the same criticisms. The premise of vast interludes of time, and innumerable increments to totally alone produce ALL possible states can be demolished by such research as that delivered by Pagel. The flawed methodology is not a no-brainer, which everyone is bound to accept.

Indeed, many other scientists, including myself, have long disputed such forms of “explanation”, but our position has not been accepted as most cases were always completely beyond either experimental demolition or confirmation. Pagel’s method changes this seemingly permanent impasse, and such assumptions can be tested with certainty. Consider all the accepted methods, particularly in computer simulations, where, based upon “placeholder” theories, of the kind demolished here, involve similar thresholds, beyond which it is assumed that a new situation has been established (by incremental changes?), and new formulae can be employed. Such methods are now clearly revealed as cases with sufficient evidence for reliable data, yet having NO real Theory, and which therefore require invented, incremental-type placeholders which cannot be validated in the usual ways.

Mark Pagel (University of Reading) attempted to “quantify” species change by considering the effects of both random, incremental events and the time-gaps between adjacent species in an evident evolutionary sequence, BUT he came up with the result that the usual assumptions were inconsistent with the investigated data, and in considering a whole range of alternatives, the one that stood out as vastly more in tune with the data, was that only the emergence of a new species by a Single Accidental Event would do.

Now, as a scientist who cringes at the usual purely mathematical foundations for “theories” in much of modern science, I was primed to disagree with Pagel. But I was mistaken. He was using the science of Pure Form (Mathematics) as it should be used – to assess the formal implications of a methodology. His conclusions are formally unassailable!

But nevertheless, for my kind of Science, his revelations are only the beginning of absolutely necessary consequent scientific investigations.

NOTE: The criticised basic assumptions seem to be:-

1. That totally random and undirected accidents occur over vast periods of time, from which Natural Selection picks out only the most advantageous for continued survival.

2. And, that such increments can then gradually build up until a threshold is reached, beyondwhich a wholly new species (NOT a mere race or breed) is created.

The expression, “You cannot see the Wood for the Trees!” comes immediately to mind. A single isolated tree in an open space is a very different thing to one existing in established and continuing Woodland. The latter is part of a system working at a different level from the single tree. Component individual trees are different by being surrounded by other trees. In established Woodland, the growth patterns are very different, and the Wood affords a measure of protection too, while the involved ecological system is much richer there, so that all sorts of symbiotic and parasitic and even inter-species advantages can establish themselves. The question has to be asked, “Could the system of the Wood be determined solely by knowing about the properties of an individual, solitary tree?”And, of course, the same must also be true for other species of organisms. We cannot reduce their development and crucial change to incremental and undirected accident over vast periods of time.

Pagel’s work demolishes the usual placeholders, but the actual causal features of species-change are still requiring answers, which will NOT be solely formal, but will tackle exactly how such changes can occur; what is the biological content of species change? What significant qualitative events can deliver such innovation?

Now, to address this question, we must start by admitting that step-by-step selection does indeed take place, and can transform a species into a different Form – but that does NOT mean a switch to a different species: a Great Dane and a Chihuahua are still both just Dogs! The mechanism explains breeds but NOT speciation!

Something else must happen to result in what we correctly term a New Species: something which is NOT gradual and incremental, but immediate, qualitative & significant!

Now Pagel et al draw the conclusion that a single accidental event must be the cause, but that merely precipitates even bigger questions. What sort of single change could produce a new species at a single stroke? It must, surely, be impossible when seen as a single accidental mutation! We must replace both Pagel’s and the usual interpretation of such an “event” with something of an entirely different order.The Change must be brought about by a short but “revolutionary” Event, and such, of course, do indeed exist, and we have come to call them Emergences.

These cannot ONLY involve a single piece of genetic damage, which, by pure chance, causes sufficient changes to produce a wholly new and viable species. It must be some sort of general “system” change in which, in a relatively short period of time, via both avalanches of dissociation and swift erections of “the new”, produce, over a series of contained, see-sawing crises, a new synthesis, which is both viable and persists!

Now, such Events are not unknown! The greatest example of such occurrences must include the very first Star, then, much later, the Origin of Life itself, not to mention subsequent significant revolutions, such as those involving the birth of Consciousness, and that of Thinking too. Finally, such processes must even apply to Social Revolutions.

But such are not usually seriously addressed in academic circles. They are considered to be too much driven by ideological assumptions and indeed are often entirely discounted. But their reality is unanswerable by such purely prejudicial reasons for dismissal. The absolutely Key example of such a kind of revolutionary Event must be the Origin of Life on Earth from purely inanimate matter. And no-one could possibly put that down to a single accidental event, could they?

To respond to Pagel et al’s criticisms can only be addressed by a serious, scientific study of Emergences – the crucial, and indeed only, single events of qualitative change. Now, though these have NOT been pursued scientifically to any great degree to date, they have been available throughout history via fragmentary observations, artistic creations and persisting myths.

Around 2,500 years ago, two opposing, world-view conceptions were outlined almost simultaneously. These were Plurality and Holism.The former, concerned with seeing everything in terms of Wholes and their constituent Parts, was established in Ancient Greece, while the latter was formulated as a world view and guide to living for human beings by the Buddha – as “everything affects everything else” and “all is change” Nothing persists!” Thereafter, throughout the intervening period right up to the present day, many holistic gems were uncovered and delivered in sayings, stories, and many works of art, but it was not until Hegel (around 1800) that an attempt was made to formulise the study of Qualitative Change via his attempt to construct a “logic” of Change with his book The Science of Logic.

His main disciples, the Young Hegelians dramatically switched sides, not only abandoning Idealism for Materialism, but also by concentrating to a great extent on Social Change as their main purpose. Marx and his followers could not be stomached by the conservative occupiers of High Academia, and any serious research into Emergences and Qualitative Change was effectively deemed insupportable.

But, the wheel has turned full circle since that time, and Science is now constantly coming up against the contradictions inevitable from maintaining an entirely pluralist standpoint in a clearly holistic World. [The most significant and ever continuing crisis debilitating Modern Sub Atomic Physics is perhaps the clearest example, but many other cases with the same causes abound in many diverse areas of study].

Even from the very heart of Academia, scientists such as Murray Gell-Man have proposed the task of addressing Emergences, and the famed Santa Fe Institute was established with that as its main purpose. But, even the giants involved there could not negate what they and their predecessors had constructed over the last century, and their unbreakable marriage to Plurality has made any real progress impossible, and the purpose of the Institute has now shrunk into investigating yet another branch of Mathematics ONLY! Such philosophically unsound bases, and purely maths-led “theorising” is incapable of addressing this crucial area, and the contributions from Santa Fe have been decidedly poor.

AS scientific method and explanation is increasingly replaced by pure Form equations, applicable only in pluralist-demanded Domains, these researchers find themselves incapable of transcending the contradictions they encounter on all sides, such that they are now major “tenets” for their position and are “worn as badges of honour and superiority over the rest of uncomprehending humanity. So, like Pagel, they find flaws, but can only replace them with other flaws, dictated by their increasingly redundant methodologies and world views.

The errors, though, frequently switch to the opposite end of the spectrum and the “containing Wood” may well be recognised, but only as a summation of isolated trees producing overall and average collective features with matching probabilities. Instead of real understanding and explanation, almost arbitrary quantifiable features are monitored for a dependable, recurring Value (at Transition), so that when it is surpassed, new laws are brought into play to replace those possible before the threshold. Clearly the passing of the value at the threshold does NOT cause the change over, but is merely yet another symptom of the process which really does bring about the changes. AND these are not a simple switch but a kind of system revolution, involving significant dissociations and re-associations – more of an Emergence indeed, than a single accidental event.

No real answers will be produced without a major renovation of the by-now ubiquitous pluralist and maths-led methodology, and the general acceptance of such apposition is clearly proved by the very language of almost all scientists. They talk of natural laws determining the nature and evolution of Reality, which is clearly an abandonment of Materialism. How can a disembodied formalism produce and then drive Reality? That is naked Idealism! Laws are produced BY Reality, which changes and evolves, so that new laws appear at each new emerging Level. The revolution of the Origin of Life on Earth generated via concrete Reality, a whole new world of laws – subsequently gathered together by Mankind as Biology! Were there any eternal biological laws “before Life”? Of course there wasn’t!

Now, this short paper is not mere kite-flying. The author – a physicist/mathematician, philosopher and teacher of 50 years experience, has been writing on these very matters for over 10 years and has, in the last 12months, described his conception of the Inner Trajectory of an Emergence, as the first step to a world-wide investigation into scientific method and the necessary formulation of an holistic alternative. Such a purpose has already produced a reformulation of Miller’s brilliant and holistic experiment into the Origin of Life. And this would itself begin to define a whole new approach to such questions, and lay the foundations for a Holistic Sc
ience.