Tag: Universe

Reality, Process, and Mathematics

All the qualities of the physical world exist through the interrelations of things to each other. What Moleschott says is correct for physical existence: ‘All existence is an existence through qualities. But there is no quality that does not exist through a relation.’ Just as everything of a soul nature contains something in itself by which it points to something outside itself, so conversely, a physical thing is so constituted that it is what it is through the relation to it of something outer.
(Rudolf Steiner, Riddles of the Soul, Mercury Press, 1996, p. 69.)

For such a philosophy, the relations that connect experiences must themselves be experienced relations, and any kind of relation experienced must be accounted as ‘real’ as anything else in the system.
(William James, Essays in Radical Empiricism, Cosimo, Inc., 1912/2008, p. 20)

In aesthetic epistemology, notions of “reality” are replaced by “patterns in process.” “Things” are (ontologically) patterned processes. We mistake the nature of the universe when we presume that “things,” to be, must “be” from the bottom up: on the basis of some “substance,” which THEN interacts in processes to yield what we experience (the first coherent expression of this began with the atoms in the void hypothesis of Leucippus and Democritus in Ancient Greece). We assume that it is silly to speak of patterns of process without some kind of “thing” that we can point to as an indicator that the process is proceeding. Because of the way our senses are involved in cognition, we tend to count as “real” only what can be made apparent to us through our senses (or their extensions via instruments). This is a huge presumption on our part. What if we tried to conceive of “substance” as a secondary phenomenon? What if process (thing-less process) is more primary? In this view, things are precipitates (momentary nodes, relatively ‘still’ areas of patterned processes) of higher-order relations… not relations between THINGS but relations qua the activity of relating. This may sound abstract, but this is because we are trained to think of reality in terms of substances (sub-stances: the “underneath-standings,” the bits from out of which a universe gets built).

The best example of one way that this can look is given in the field of mathematics. Mathematics has no atoms, not even metaphorical atoms; it is entirely substanceless. Rather, mathematics has, at its base, processes and their relations. Even numbers aren’t the basis of mathematics, (more…)

January 22, 2012
how do you know what knowledge is?

It’s quite a dilemma – not being able to directly check much of what we are exposed to and presented as ‘knowledge’. Unless we begin to discover our own ways of knowing (a very difficult proposition, but I think possible), then we likely remain wanderers in the fog of our own (and other’s) unconsciousness.

Of course, at least in any near future, it doesn’t seem like subconscious situational effects can be avoided – nor do I think they should be. Much of what we enjoy as part of our everyday capacities for thinking, feeling, and willing are rooted deeply and complexly in unconscious processes. Indeed, what is normally conscious for us is perhaps one of the tiniest slices out of what can be potentially conscious, and perhaps the potentially conscious is just the tiniest slice out of the full depth and breadth of the universe as a whole – or not (because, in accord with what I just said, this is an impossible determination, requiring consciousness to take place).

In any case, pretty much EVERY modern study that follows the basic scientific practices is a study in obfuscation, requiring for its potential success a decided ignorance of as many ‘attenuating’, ‘circumstantial’, ‘probabilistic’, or ‘random’ factors as possible. The more willfully ignorant a study becomes, the more exact are its pronouncements, and the more its knowledge is sequestered from the whole. This is why all studies require additional work to be re-connected to the complex actualities of the world, necessitating interpretation, reframing, and recontextualization.

This suggests a different way of performing ‘studies’, discovered long ago by Goethe and others, in which the situatedness, the contingency, the circumstantial, are all necessarily included aspects of any attempt to work with and understand a phenomenon.

February 21, 2009
on why you will have trouble predicting what I say in this post

One of the things about complexity/chaos theory is that prediction submits to very specific limits, in the sense that with anything but a VERY simple system, we must give up the potential for long-term predictive certainty. This is because very small differences can lead towards extremely large differences later down the line, and we simply can’t account for the effects of these very small differences.

The problem is that one never knows whether a small difference will actually make a difference or not. And in any case, with any non-trivial system, the small differences are all complexly interrelated to larger scale changes, with much cross-feedback.

So SOME kinds of predictions are possible — it’s the RANGE that’s a problem. For example, we can predict with high certainty that certain climatic patterns will continue far into the future — but we can’t predict with any accuracy on any given future date whether it will be cloudy and raining or sunny, because those detailed specifics are precisely what are affected the most by the tiny shifts in today’s weather.

Then there is a completely separate but equally problematic blow to our predictive abilities. If the only problem was the butterfly effect, we might be able to make a computer powerful enough to predict far-future events with accuracy, because it could take everything into account — after all, the universe follows its own laws, right? We just tell the computer what those laws are, the initial conditions, and give it enough time to calculate and we should have an accurate and complete answer, right?

Nope. The problem is two-fold. On the one hand, we simply don’t know how to account for (measure) all the very small initial states that would be required for such a computer to have sufficient information to do its job. It’s simply too huge of a task in a practical sense. You would, for example, need to know (in the case of weather, a good chaotic system) the pressure and temperature of the air… but for WHAT air? Can you generalize and only look at average values for large volumes of air, say, those the size of a city? Or do you need accuracy to within a cubic meter of air, so you can have distinct values for every cubic meter of air on the planet? You see the practical problems associated with this. Other complex systems, such as the body, behave in the same way — measuring hormone levels in the blood, the distance between dendrites and axons, the thickness of their myelination, etc. etc. — there is no practical way to get the information needed.

BUT WAIT, IT GETS WORSE!
Unfortunately for our predictive abilities, it isn’t even just a question of the practical difficulties in obtaining such information, but rather that such information is IN PRINCIPLE, not gettable. This is because, as the quantum mechanics shows, we cannot help but disturb a system when we measure it, and that disturbance always introduces an uncertainty with respect to some other aspect of the system that we can never – IN PRINCIPLE – simultaneously account for so as to know the COMPLETE state of the system at any given instant. We have to do all our predictive work on the basis of PROBABILITIES, not certainties – at least when we are talking about the quantum level.

But here’s the rub: NOBODY knows when it might be okay to ignore quantum effects and stick with much more manageable ‘classical’ (and predictable) rules. It’s a real philosophical and practical problem, because we see more and more that the quantum world and the world of macro-scale qualities are not separate. Of course, it would be quite bizarre if quantum-scale effects simply occurred over a very well-defined set of limits, beyond which different rules took over that needed no reference to the quantum rules. Of course, this is precisely how most scientists actually do their work — they either work in particle physics or other fields that look at very small scales, in which case they use the rules that describe the quantum realm, or they work in engineering or biology and only worry about quantum effects when they have to, otherwise they use classical rules as much as possible.

Chaos theory itself is fractal – it’s laws span all scales. We cannot ignore the potential and actual effects that cross over from one scale to another, decreasing our certainty at each level. The change on one level of a phenomenon may very well cause a change on a completely different level — but in predicting that change to arbitrary accuracy we run into practical as well as principled issues which we cannot overcome. Thus, the built-in indeterminacy at the quantum level can, through the scalar linking effects described by chaos theory, can link single, quantum-scale processes to shifts at the macro scale.

We can always make predictions, and for many situations and circumstances, the above problems are ignorable. But for other situations–those near criticality, for example–the full effects of both quantum indeterminacy and chaos theory may make all the difference.

February 15, 2009