Tuesday, August 20, 2013

Humanization and Objectification: Why the World Doesn’t Speak for Itself

In the Age of Reason, we usually think objectivity is better than subjectivity. When we speak subjectively, we say more about ourselves than about anything else, telling how something makes us feel or revealing unintentionally how our bias filters our perception. Either way, subjective thinking seems self-indulgent, since we assume that few people are interested in our emotional states, that we should save our personal confessions for those who are part of our private life. By contrast, we think objectivity is a noble, eminently practical and even selfless discipline. Critical thinkers, mathematicians, and scientists are the knights of rationality, circumventing their personal preferences to understand the real world, the one that doesn’t depend on how we feel about it.

Take, for example, our taste in politics, art, or food. In these cultural areas, there are no objectively correct answers. George Lakoff, Jonathan Haidt and others have shown that liberals and conservatives have different gut reactions to moral questions. Different kinds of people prefer different things, depending on environmental pressures and people’s past experience which affects the development of their neural circuits. So when someone who prefers Thai food speaks about it, she’s expressing herself rather than talking just about the independent reality of Pad Thai. In fact, when we think objectively, we usually think the real world is value-neutral, that how things seem to us, as interpreted and filtered by our memories and moods, is an illusion. Fundamentally, the world is very different from how it seems to us when we’re mentally processing it, because we project meaning, purpose, and value onto everything—unless we’re attempting to be objective. We anthropomorphize impersonal regularities and even random fluctuations like the shapes of clouds, because we normally prefer to be social even when there’s no one else in sight.

How, though, do we learn the objective facts? We might think that objectivity is a matter of quieting the internal noise we generate, to let the real world speak for itself, as it were, as though logic and science were comparable to Buddhist meditation. But this isn’t how objectivity works. Were you to silence your inner narrative, to ignore your intuitions and dispositions, and then to look around at the world, you wouldn’t suddenly behold the mind-independent facts. On the contrary, your brain would subconsciously process information carried in light rays and in the vibration of air molecules, for example, producing the apparent world you perceive. The brain automatically transduces ambient signals into neural patterns that stand in as mental representations of the world. These representations are so interconnected that we move easily from one thought to an associated one, and are able to overlay our value-laden mental map onto the real world, which is why quieting the mind is such a challenge. Moreover, without our concepts for classifying things, we wouldn’t understand our sensations.

This was the main point of Immanuel Kant’s philosophy of knowledge. We don’t deal directly with mind-independent reality, because wherever we go we carry with us ourselves and thus our filters, habits, methods, and so forth. Even objectivity is a kind of knowledge and knowledge doesn’t just fall out of the sky, but lies at the end of a mental process. There would still be a world were there no living things, but that world would differ even from how it’s objectively represented. The world doesn’t speak for itself, after all; instead, it speaks through us, regardless of whether we’re being subjective or objective.

Logic, Math, and Science

Let’s look closer at what we bring to the table with objectivity. The simplest way to be objective is to follow the rules of critical thinking, to argue rather than just to assert our opinions. When we argue, we prove not just to others but to ourselves that our beliefs are rationally justified. We fortify our inferences, thinking only along broad paths, as it were, paths which we’ve found to be highly reliable routes to reality. In fact, the rules of deductive and inductive reasoning reflect the most general patterns to which events seem to conform, although to the extent that natural systems are chaotic (nonlinear, unstable, involving feedback loops), some other form of logic might be needed. For example, the law of noncontradiction says that nothing at all can both have some property and also lack that property. At least in everyday experience, we don't observe a violation of this law, but this doesn’t mean that nature speaks our language, that everything follows this law.

At best, whatever nature is doing, its processes correspond with our best ways of thinking. There’s still a gap there, because logic is a set of rules for thinking, not for being. Logic governs our thinking, but only ideally so since we’re free to be irrational. Natural processes just happen and so at best they coincidentally rather than inherently follow the ideals we set for cognition. By the Anthropic Principle, we can surmise that if the world didn’t agree with our thinking, if we couldn’t make use of our sensory information, we wouldn’t be long for the world and so there would be no such coincidence to explain. Moreover, the world appears logical because our concepts are flexible. Although no two eggs are exactly alike, for example, we classify them all under the same heading, because their differences are negligible for our purposes. Thus, we can enter “egg” into a deductive argument and know for certain that if all eggs are small and that that thing over there is an egg, that thing over there is small. Conversely, when we think of a unique individual, we ignore the thing's interconnectedness to other things. Logic sweeps under the rug nature’s fundamental lack of rational divisions, as revealed by the infinite variety and interconnectedness of natural processes, so that, strictly speaking, all of our classifications and rational judgments are fictions.

A more advanced form of objectivity is mathematical problem-solving, which uses highly abstract concepts. Math began as a relatively crude means of keeping track of land and food ownership for tax and other bureaucratic purposes. Numbers, systems of counting, algorithms, and many other tools of calculation were invented to make this kind of thinking more efficient. As the physicist Eugene Wigner pointed out in 1960, math is unreasonably effective in the sciences. Even the most exotic mathematical idealizations have been applied in physics. For example, Bernhard Riemann’s work on non-Euclidean geometry was used in Einstein’s theory of general relativity, and string theory includes mathematically precise ways of conceiving of extra dimensions. The reason this usefulness of math is “unreasonable” or mysterious is that there are no mathematical entities in the apparent world. For example, we never encounter a perfectly straight line, so again the idea of one is as fictional and idealistic as Harry Potter.

The more abstract the idea, the more concrete details it ignores and so the more unrealistic the idea becomes. Math is full of such unrealistic, otherworldly ideas. Although people have put math to work for thousands of years, mathematical precision can also be misleading. From Plato onwards, philosophers, mathematicians, and religious people generally have wondered whether the abstract worlds we imagine are more real than the material domain through which our bodies slog. Neoclassical economists drew up idealized models of how markets work, ignoring a great many concrete realities, and faith in the utility of those models is largely to blame for the Great Recession of 2008, when the reality of the American real estate market was unveiled. And turning to physics, string theory is so remote from experience that the theory seems unfalsifiable. So contrary to Wigner, what we gain in precision from mathematical idealizations, we may ultimately lose in applicability. Objectivity can become so abstract and the rules for working with the tools of rationality so arbitrary, that our supposedly fact-based thoughts become hard to distinguish from fantasies.

Combining logic and math, we have the scientific methods themselves for pinning the world down and forcing it to reveal its hidden nature. Scientists divide and conquer: they break the world into parts to study simplified sections of the natural plenum and to test their hypotheses; that is, scientists isolate a process and control for what are assumed to be irrelevant background properties, and they check whether a suspected causal connection obtains. Causal relations are thus broken down into mechanisms, which are systems made of parts that work together to form larger systems, and a scientific theory lays out some of these interrelations. And so scientists famously bypass the evolutionary limits of our thinking and seem to let the world speak for itself, one fragment at a time.

But science is still a dialogue with the world, not a monologue. A scientific theory is partly a model which offers a simplified representation of some process, like a blueprint, and partly an algorithm for generating a predicted result. The Newtonian paradigm of explanation assumes some initial conditions and relevant forces, and uses equations to deduce how the system evolves to reach a certain state. In addition to both the model for separating the relevant from the irrelevant properties and the mathematical apparatus for measuring a phenomenon, there’s a tradition of interpreting the theory, of translating it into commonsense terms, using metaphors to bring our intuitions and everyday experience to bear. This kind of interpretation is a concession to subjectivity. Quantum mechanics shows us the difference between these aspects of explanation, since in that theory our ability to quantify takes precedence over our interest in assimilating the phenomenon.

In science, then, objectivity is paramount, but even scientific objectivity requires human labour which impinges on what scientists are trying to understand. The world isn’t really divided into mechanisms. Mechanistic models are simplifications made necessary by our inability to observe, let alone understand, everything at once. What scientists explain directly is how artificially-isolated parts of the world behave, and scientists infer that the observed patterns hold more generally, on the condition that the irrelevant properties—those in which we’re less interested—don’t interfere too much with the interesting ones. This is to say that scientific conclusions are probabilistic, because the procedures by which scientists achieve their objectivity perturb the phenomenon they’re trying to understand, and a natural setting can only approximate the artificial one they isolate. Again, this comes to a head in quantum mechanics, with the Uncertainty Principle, but all of science is similarly limited. As in quantum mechanics, it’s as though the scientist were using a microscope to observe a miniscule specimen on a slide, but she’s unable to use the instrument without placing part of her finger on the slide and obstructing her view. When scientists control for irrelevant variables, the scientists get in their way through their manipulations, but without that labour there would be no piecemeal learning about nature and thus no scientific objectivity.

So objectivity isn’t the suspension of our distinguishing features to let the world speak for itself; instead, it’s a synergy between us and the world. We ignore parts of ourselves and parts of the frontiers of experience, to learn to overpower a fragment of the undivided and thus inconceivable wilderness that is the whole universe. Our reliable generalizations, mathematical idealizations, simplifying models, and divisive experiments are tools that have to modify a natural process to extract the facts we want. Those tools engage with the world as we find it and by doing so they effectively brand the facts that they uncover, which ought to remind us of the sophisticated work we inevitably perform as we try to understand nature without the dubious aid of commonsense or of our evolved biases. We can learn about the real world, the one that doesn’t depend on our interpretations, but only by objectifying reality, which means breaking it down into manageable parts and using intermediary processes as tools to divine the world’s contours. Even when the pristine cosmos follows logical patterns and behaves as predicted by our theories, those fruits of objectivity are grown in part by the seeds we sow. Objectivity isn’t just a straightjacket for our personal preferences, but is a trick we play on Mother Nature to force her to reveal her secrets. As with any magic trick, we employ a hidden apparatus, but it’s a poor magician who—like her audience—comes to lose sight of the tools of her trade.

Why aren’t more scientists nihilistic?

We should think of subjectivity and objectivity as processes of humanization and of objectification. In a social context, we reinforce the uniqueness of our personalities and the partialities of human nature, making use of our tools and machines according to the functions we set for them, and when we encounter the untouched wilderness, we humanize it by transforming it into an artificial world that flatters us by making us feel central. By contrast, when we rationally inquire into the nature of something, we hedge it in, ignoring its concrete uniqueness and going over its head, as it were, with the guidelines we project onto the world. We isolate, manipulate, or dissect the object to judge where it belongs in the natural order. And when we encounter a subject rather than an object, we dehumanize it, using the objective mindsets of economics, government bureaucracy, market research, public relations, the military, the sex industry, and so forth.

Why, though, do the most objective people tend not to be cynical nihilists, despite their command of objectification which counteracts their instinct to humanize the world? To be sure, some elites in the more objective industries may well be nihilistic, but whereas scientists are the most famously objective persons, it turns out that in the U.S. at least, scientists are much more liberal than the average American. Far from worrying about the likelihood that cognitive scientists will thoroughly dehumanize us as they come to understand how exactly the mind fits into nature, American scientists are boldly progressive, holding to values that assume our dignity as persons. How can this be? The philosopher Alex Rosenberg, who calls himself a nihilist, wonders why scientists aren’t more up-front with the public about the implications of their naturalistic worldview. He offers a number of institutional reasons, such as the fact that scientists are trained to be cautious and they don’t want to alarm people and lose the public funding for their research. But these sorts of reasons don’t explain why scientists themselves retain commonsense notions of subjectivity and morality. Shouldn’t the suicide rate be relatively high among scientists? How, instead, do scientists so easily leave aside their objectifications as soon as they exit their laboratory? How can they be so adept at both humanization and objectification? Shouldn’t expertise in the latter make us embarrassed to engage in the former?

For a telling example, take the super-intelligent character Sheldon Cooper from the comedy TV show The Big Bang Theory. Why do the millions of fans of that show love to laugh at Sheldon? Clearly, because the combination of his autism and his genius for objectification makes him childlike and so despite his godlike intelligence, he can’t fit into adult society. But who are the viewers fooling? When we objectify, our consciousness, moral worth, and other personal qualities seem to disappear; they pass straight through our net of abstractions and quantifications. For centuries now, scientists have been undermining commonsense notions. Thus, it looks like objects are more real than subjects, like personhood is only an illusion and the universe is just the block of impersonal forces and chunks of matter that scientists have come to understand. If that’s a reasonable fear for scientists who spend their professional life confirming the universe’s materiality, given their methodological naturalism, the question is why more scientists aren't as impersonal and socially awkward as Sheldon Cooper. Isn’t the self-indulgent subjectivity of their private life hypocritical, given the undeniable power of their collective scientific work?

The reason that scientists in particular don’t see themselves as robotic nihilists is precisely because they’re most familiar with the nature of objectivity. Better than most people, they know that objectivity isn’t a matter of getting entirely out of the way to let the universe speak for itself. They personally perform all of the preparations for objectively engaging with the world, by isolating the variables, idealizing with mathematics, simplifying with models, carving out part of the world in their experiments and so arriving at their indirect knowledge about what would happen in the real world were that world to behave like the isolated part. Scientists know that objectivity is a peculiarly human practice that always reveals that we’re interested rather than neutral creatures, even as that practice does clarify the nature of the universe and afford us greater control. Scientists seem to know that objectivity depends on subjectivity, that if we no longer saw ourselves as persons, we’d lose our understanding of scientific practice. At least, for science to continue we have to think of ourselves as objectifiers, and it seems paradoxical that the creatures with apparently the richest inner life should also be capable of the greatest emotional detachment. If objectivity is real and crucial to the very scientific knowledge that threatens to dehumanize us, so too is that inner, subjective life which insists on juxtaposing itself against the impersonal expanse of material objects.  

24 comments:

  1. Hey Ben,

    " In fact, the rules of deductive and inductive reasoning reflect the most general patterns to which events seem to conform. For example, the law of noncontradiction says that nothing at all can both have some property and also lack that property. We never observe a violation of this law, not even in subatomic weirdness, but this doesn’t mean that nature speaks our language, that everything follows this law.

    At best, whatever nature is doing, its processes correspond with our best ways of thinking. "

    Are you saying that's an assumption we have or claiming it's true?

    Has our conversation about DST changed your mind about it's trueness?

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    1. I did write this article a couple of weeks ago, before you got me thinking about chaos and complex systems. But I'm not sure which assumption you're questioning. Are you saying chaotic processes are illogical? I think the next couple of sentences are important: "There’s still a gap here, because logic is a set of rules for thinking, not for being. Logic governs our thinking, but only ideally so since we’re free to be irrational."

      So to make sense of chaotic processes, I'd expect us to apply some rules for our thinking, whether deductive, probabilistic, or some other kind. But you're the expert here, so how does chaos sit with logic?

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    2. Well deductive logic is built on axioms that lead to universally true conclusions within the axiom set. However, it doesn't help select the axioms in the first place, so many logical people still have an extremely inaccurate worldview. Moreover, in deductive logic you cannot have feedback loops, so it is impossible to construct complex/fractal systems from deductive logic.

      Inductive logic can have feedback loops and is more conducive to observation, but it assumes stationarity and simple attractors (what we would call limit cycles). This is inherent because it takes X0, X1, XN+1 = X and then says it's valid for N->infinity. So again, it is a poor tool for real life, which operates on a level of disequilibrium.

      In fact, I'd go so far as to say that our main cognitive-social bias is to abuse inductive reasoning and this is a prime cause for many sociological and psychological phenomena.

      So yes, in that sense complex systems are illogical and many systems researchers are coming to the belief that we need a new form of logic and mathematics to accurately convey it.

      That said, there are two other points. #1 is that DST is more normative than pure logic, because it suggests how to select your base conditions and set up systems with different purposes. #2 is that logic can be used to evaluate the predicted consequences of a systems mindset.

      So for example, on global warming a pure logical/statistical point of view grossly underestimates the danger by many orders of magnitude, because the bulk of the danger comes from internal feedback that cannot be fully known. That said, there is strong evidence of certain types of feedback showing that catastrophic switching has happened in the past (http://www.aip.org/history/climate/rapid.htm) and from a DST point of view, it would be very very unusual if the climate DIDN'T display that behavior.

      Recent observations confirm that we are moving into this dynamic regime, with real world consequences occurring 80 years sooner than would be expected from a statistical model.

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    3. Therefore, once you look at it from a DST, then you realize that the correlated feedback causes a statistical distribution that is uncharacterizable, meaning that logic and statistics cannot be applied mathematically speaking!

      In essence, this means that any risk model is fundamentally invalid.

      I don't feel like finding it right now, but the author behind the economic risk report that is most commonly cited stated two years ago that he realized what I just said and has rejected the application of any economic risk model for climate change response.

      For some reason, his original report (saying that economically we shouldn't have a fast response) is cited often, but his existential change in viewpoint never is; I just accidentally ran across an interview while looking up the report.

      Anyway, in this sense complex systems are impenetrable to logic and so therefore any true acceptance is built on Faith in the Huxley sense.

      "Give us this day our daily Faith, but deliver us, dear God, from Belief.

      Faith is something very different from belief. Belief is the systematic taking of unanalyzed words much too seriously. Paul's words, Mohammed's words, Marx's words, Hitler's words---people take them too seriously, and what happens? What happens is the senseless ambivalence of history---sadism versus duty, or (incomparably worse) sadism as duty; devotion counterbalanced by organized paranoia; sisters of charity selflessly tending the victims of their own church's inquisitors and crusaders. Faith, on the contrary, can never be taken too seriously. For Faith is the empirically justified confidence in our capacity to know who in fact we are, to forget the belief-intoxicated Manichee in Good Being"

      I've spent so many hours recently explaining why we can't be ruled by quantitative means, but then turn around and work on my analysis framework that is going to be used to create control systems for our basic needs. This seems to be contrary, but it is not because instead of saying that the control system represents nature and will make things good, I instead am advocating a Faith based change in lifestyle, using the control system as an imperfect tool to help us when it works but not harm us when it doesn't. [Unlike say Fukushima]

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    4. I've added a point about chaotic systems to the article. The section on logic isn't really about any particular system of logic, although I might have generalized too much about deduction and induction, so if a new form of logic is needed to cover chaotic systems, as you say it might be, I think that section of the article would still apply.

      Still, deduction is really just a way of being clear about the meaning of conjunction, disjunction, conditionals, and so on. So if chaotic systems violate deduction, that means we can't use the words "and," "or" or "if, then" to talk usefully about them. But when you say that deduction doesn't allow for feedback loops, it still seems that plenty of deductive statements would be true of the systems in question. And are you saying that chaotic systems violate the law of noncontradiction?

      You seem to contradict yourself when you say that logic can't be applied because of feedback, since you also induce that because certain types of feedback showed catastrophic switching in the past, therefore the climate likely displays this behaviour.

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    5. Yes, "and", "or", "if", "then" are not fundamentally applicable -- this is why it's very hard to talk about complexity and fractals!

      As for your last point, that's why I said "#2 is that logic can be used to evaluate the predicted consequences of a systems mindset." Or at least we think it can.

      The reason goes back to a point I made on Scott's blog: while trajectories are not predictable after a certain period (dependent on the complexity of the attractor), the attractor as a whole is characterizable. Therefore, we can make logical statements about whole system behavior, including characterizing patterns and modes of operation.

      Donella Meadows has systemized a few.

      This leads to insights that desired behavior from a system should be systemic, and interaction with/design of the system should also be systemic. Like this link summarizes: "Note here that reports and their case studies typically describe specific solutions for specific challenges. What is needed is a way to describe general solutions to specific challenges, that can be followed again and again, leading to many sustainable results, that are successful, yet all different. This is what patterns are about."

      As you can see from the diagram, not only does complexity occur within each design step layer (dream, process, etc.) but between them. Thus, real physical processes and abstract cognitive/social processes are linked and feedback onto each other.

      Yes, "and", "or", "if", "then" are not fundamentally applicable -- this is why it's very hard to talk about complexity and fractals!

      As for your last point, that's why I said "#2 is that logic can be used to evaluate the predicted consequences of a systems mindset." Or at least we think it can.

      The reason goes back to a point I made on Scott's blog: while trajectories are not predictable after a certain period (dependent on the complexity of the attractor), the attractor as a whole is characterizable. Therefore, we can make logical statements about whole system behavior, including characterizing patterns and modes of operation.

      Donella Meadows has systemized a few.

      This leads to insights that desired behavior from a system should be systemic, and interaction with/design of the system should also be systemic. Like this link summarizes: "Note here that reports and their case studies typically describe specific solutions for specific challenges. What is needed is a way to describe general solutions to specific challenges, that can be followed again and again, leading to many sustainable results, that are successful, yet all different. This is what patterns are about."

      As you can see from the diagram, not only does complexity occur within each design step layer (dream, process, etc.) but between them. Thus, real physical processes and abstract cognitive/social processes are linked and feedback onto each other.

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    6. Oh and "And are you saying that chaotic systems violate the law of noncontradiction?"

      In most readings, yes they do. Chaotic systems can act in one way at one timescale, within a different pattern on a different timescale.

      I have incorporated these lessons into my own life with much success. I often do things that are seen as enormously contradictory to outside people; moving slowly the majority of the time but then rapidly at others. I seem to be very conservative, even though I speak of radical ideals; but then at certain times I act very radically for conservative aims.

      I do things that I deliberately believe will fail, just because if they succeed then it is more insightful than doing something I think will work. I am unphased by what most would think catastrophic, and am alarmed at what others think is simplistic -- even being alarmed at success.

      And so in this way, my being is consistent, but my persona is contradictory and mysterious, even to myself.

      Most people think I am the most complicated person they've ever met and either they are enchanted or actively repulsed (particularly if they are sociopaths! Sociopaths fixate completely until it destroys them). Yet, I am actually the most simple.

      Very few people understand this and most of the ones that do aren't intellectual, although they are very smart about people.

      Most people try to follow along with my logic and behavior and determine I am the space shuttle crossed with a nuclear plant; I am actually plain in all ways but faceted 10,000 times.

      It is astounding to me that apparently most people have an active inner monologue: my mind is (relatively) silent and that's what allows it to spring into life when needed. But it is still full of chattering monkeys compared to people that meditate deeply and often.

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    7. Well, I'm not sure context-sensitivity is the same as logical contradiction. The law is sometimes put a little more precisely as "Something can't have both P and not-P in all the same respects/ways/contexts." Thus, today can't be both Wednesday and not-Wednesday, where "today" is defined in terms of only one part of the globe.

      Maybe there would be a contradiction if the very same system, under the same initial conditions and governing laws could have evolved differently, making it inherently unpredictable. But because a chaotic system is deterministic, there would have to be some slight difference between the systems, right? Thus, the law of noncontradiction wouldn't be violated. We couldn't say the system S is liable to evolve along either trajectory T or not-T, since there would be two systems rather than one, and one of them would be counterfactual. Plus, we'd be dealing with a disjunction rather than a conjunction. The very same system wouldn't have opposing properties.

      At best we could say the system has some probability of going the T route and some other probability of following not-T, but that inductive statement wouldn't be contradictory.

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    8. " But because a chaotic system is deterministic, there would have to be some slight difference between the systems, right? Thus, the law of noncontradiction wouldn't be violated. We couldn't say the system S is liable to evolve along either trajectory T or not-T, since there would be two systems rather than one, and one of them would be counterfactual."

      Well now you're getting into argument about what "reality" is. It is true that in theory two systems with the exact same initial conditions would evolve the same way (given the same outside interactions) but there is a fundamental limit to observational accuracy. Thus, there are many systems that *appear* to be identical (measured out to infinite digits) that are actually different.

      Systems do not violate super positionality: they cannot occupy the same space; i.e. quantum position. But I still would state that they can have logical contradictions because you can't *know* what the state of the system is after a certain time period.

      Therefore, even though they cannot be in contradiction at time t=0, they can be in contradiction a t = x; where x > time ~ complexity but fundamentally unknown.

      Because of this, you cannot build a probability distribution and so therefore can't make a deductive statement.

      As for an inductive statement, you can do a bit better as long as you constantly update your a priori distribution (this is how people believe they can use Bayesian logic to unlock fundamental truths about reality; such as haig says Yudkowsky is trying. It is also how we can make 'practical' control systems that seem to work most of the time). However, if the system is operating in a disequilibrium state undergoing bifurcations, then it will reach a critical point where there is a mathematical discontinuity and the distribution falls apart. At this point the system can "jump" to a new point (even infinity) without any way to predict it.

      You have brought up an interesting point though, which is that continuous complex systems modeled through differential equations and iterative fractal systems both share a lot of commonality, but we haven't figured out how to create a system that is both dynamic and fractal (as far as I'm aware).

      This is important because some characteristics such as the criticality have only been formalized through fractal sets, while other characteristics such as strange attractors have been formalized only through differential equations: yet reality displays strange attractors that are also fractal.

      Characterizing systems is important because if you understand their general behavior then you can discover the points in the system that are more likely to respond to intervention. Thus, the best way to make a system predictable for a long time is to intervene in an intelligent way, but that intervention is built on belief about where the system will eventually end up.

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  2. Apologies to Ben and Mikkel for interrupting but I have to ask.

    Mikkel, I've read an inordinate amount of your words for encountering a novel personage a week ago; again apologies, but what exactly is DST?

    Perhaps, you highlighted it in some of the earlier comments on TPB or in the comments to the Dialogue here on RWUG but I can't seem to remember it.

    Thanks, cheers.

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    1. Thanks Mike.

      DST = Dynamic systems theory

      Ironically, even I did not know what DST stood for until starting this conversation. We always just say "systems" or "dynamic systems" or more generally talk about complexity and never DST. But when in Rome.

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    2. I might have introduced that term here, having encountered it in the philosophical debate about cognition. There's computationalism, a theory that traditionally assumes serial processing of mental representations; there's connectionism, a theory that's ambivalent about representations; and then there's DST, which leaves out representations and brings in the math of chaotic systems.

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    3. Thanks, Mikkel. Promises I'll come back and give this post some respectful attention, Ben.

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  3. "The reason that scientists in particular don’t see themselves as robotic nihilists is precisely because they’re most familiar with the nature of objectivity."

    Nihilists aren't robotic - they're dead.

    Nihilism is paradox, nihilism is paralysis, nihilism is the understanding that destroys understanding - even itself.

    Rationalists are no closer to nihilism than any other living human.

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    1. The mystery for me here is why scientists aren't more socially dysfunctional, because they should be unable to take seriously the subjective aspects of culture, including their intimate relationships. "Nihilism" is meant there as a shorthand for saying they shouldn't be able to care about anything, assuming values aren't part of the objective world of facts.

      I aim to write something specifically on nihilism, though, because I've had a lot of comments on it. I might consider the nihilism of Mitchell Heisman and Ray Brassier.

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  4. Logic sweeps under the rug nature’s fundamental irrationality, or lack of inherent order, as revealed by the infinite variety of nature’s particulars, so that, strictly speaking, all of our classifications and rational orderings are fictions.

    That isn't logic. That's the kludge point between senses and the practice of logic. The kludge point that'll fumblingly assume something is the case - and present it to logic AS the case. It's why we get so damn certain - by default, we are unaware of the distinction between the two.

    If one of your points is that logic just happens to kinda parralel repeating natural patterns but that's not really understanding nature, I'd agree. The practice of physics is alot like noting someone goes into a shop every day at 9.00am, then always leaves at 9.05am each day and declaring it 'knowledge' - when they have no idea what the person does in the shop during that time, but they'll make a big deal of pinning down the times. I could agree on that.

    But what you're describing isn't logic, Ben. That's not a fair evaluation.

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    1. I've actually added a sentence to that part, because I forgot to say something about logical constants which represent individuals. The prior point was about logic's use of concepts or generalizations, which ignore the uniqueness of particulars. But when we think of uniqueness, we ignore their interconnectedness.

      Either way, logical relations are like roads connecting buildings that hardly anyone occupies. Our thoughts are models, like mini scientific theories. We simplify and idealize the world, and the more abstract our thoughts, the more we ignore. There's our most careful way of thinking and then there's the way of the world, and the two aren't the same. But Callan, I think this is indeed more or less the point you're making about parallel patterns that don't entirely match.

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    2. I'm saying garbage in, garbage out. If you want to disprove logic's applicableness, it'll need to be by another method - not pointing to how we feed logic some garbage, then it spits out garbage, then trying to say logic is at fault for that garbage!

      Assuming something like logic (rather than the supernatural) is at the very spine of the universe, the only way to grasp every not actually straight line is to have a model of the universe so detailed that it itself would be a universe. I'd say this is impossible from the inside of the universe - it almost reminds me of Scott's blind brain theory in that manner. Anyway, when you're on the inside, you're dealing in garbage data. But that by itself does not prove logic to be inapplicable.

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    3. Hmm, it seems you have a platonic view of logic. You're saying that "on the inside," or on the material plane, we're stuck with garbage data from our senses, since we're trapped in our bodies, but logic is at the core of reality. So our most logical arguments can still only approximate the Formal Truth.

      I'm not really arguing against this view in this article. I'd be content to grant your point that our best form of objectivity in the here and now can only approximate the Truth, because we're stuck feeding logic that garbage, partial, and humanized data. Thus, I don't argue that logic doesn't apply to the world. I say only that logic doesn't apply in such a way that the world speaks to us for itself, without us getting in the way.

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    4. I don't know if logic is at the core of our reality. I'd say probably is. I'm just saying disproving the applicability of logic would take something other than pointing to the output of it that we are partly responsible for.

      I say only that logic doesn't apply in such a way that the world speaks to us for itself, without us getting in the way.
      It could just be my reading of it, but it doesn't read that way - it seems to focus on logic, instead of focusing on the focuser. It's not that logic acts as if there are straight lines in the universe. That's us. I would agree with Sheldon Cooper as an example of someone so entranced with logic they can't see the forest for the me's.

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  5. Great piece, though once again I would encourage you to look beyond traditional metacognitive dyads such as subjectivity/objectivity. The big reason scientists don't worry about the nihilistic implications of their work is that they simply don't think about them - or even care, really. I would that for the vast majority it's not that they have this wellspring of subjective affirmation at their disposal inclining them to infer dependencies, it's that this very way of thinking is unnatural, and even odious to them. Cognitive dissonance has to be recognized to be appreciated. I once spent weeks debating an evangelical Christian aerospace engineer who used Kuhn to rationalize her faith!

    The point is that subjectivity and objectivity are metacognitive posits, culturally entrenched, certainly, but not in any way 'given.' As such, the possibility that they are profound distortions is really not that far of a leap - I would argue that it means they HAVE to be screwed up somehow! The story you tell could be told without them, I think.

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    1. I think I see your point that not everyone will be interested in philosophical implications, but I think you're downplaying the mystery here. Apparently, most American scientists aren't just cheerful people, they're downright liberal. Have they just absorbed the values that are rampant in the academy, because they're much too busy doing science to think about the conflict between their ontology and their culture? Maybe, but I'd expect more of them to have a dark night of the soul once in a while.

      Some scientists are indeed more nerdy than average people, but what annoys me is when scientists just regurgitate the most naive, sentimental palaver as though their work poses no threat to ordinary people's preferences. For example, I once read a neuroscientist's report on the love hormones, but of course she's happily married and she has no trouble reconciling the fact that she has to ignore her knowledge to get on with her life. The mystery is that she appears to suffer no cognitive dissonance.

      Well, in this article, I offer scientists a bit more of a defense, since if they had to speak for themselves I doubt many of them could reconcile their naturalism with their lifestyle. I think they may not take their naturalism so seriously because they have firsthand experience of how science isn't as objective as nonscientists assume.

      The question of whether the subjective-objective distinction is culturally distorted would take us into familiar territory: is science factual in a way that religious myths and other fictions aren't? If so, how so? The difference is between how reason versus our raw emotions and the imagination connect to the world, I think.

      By the way, you might also be interested in my next article which will go up on Monday. I'll be taking on Ray Brassier's nihilism, which I believe I first heard about on your blog. I think you wound up taking him to task, but it seems you two agree on a lot. Would you call yourself a nihilist? Do you think the scientific image implies nihilism? This might be a good topic for another email exchange...

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  6. I think that you perhaps underrate the importance of subjectivity. If one were to actually look at objectivity objectively, one would find its importance to be vastly exaggerated. Certainly it is important, but not to an extent that could even compare to the importance of subjectivity.

    If I'm understanding you correctly, you're saying that scientists avoid nihilism by acknowledging the interdependence of objectivity and subjectivity.

    Isn't this perhaps an understatement?

    It would be better to say that scientists avoid objective nihilism because it is impossible (outside of serious hypocrisy). Were one to contrast the frequency, dependency and value of subjective vs. objective thought and behaviour, one would likely find the importance of objectivity virtually infinitesimal.

    Of course it depends on how strictly one applies the criteria of objectivity, but applied to the level approximating anything close to that of scientific standards, the significance of objectivity becomes almost nil.

    If you think about it, one could possibly live without objectivity. It likely wouldn't be a life most of us would consider worth living, but in contrast, a life without subjectivity is almost inconceivable.

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    1. Hmm, you might be right that I'm understating the matter, but I'm not sure the question I'm considering is which is more important to human life, objectification or humanization. That would be a very hard question to answer. You're surely right that subjective expressions of emotions and snap, intuitive judgments based on personal experience happen all the time, they make life worth living, and so forth. But then again, rationality, objectivity, and protoscience have been instrumental to our survival in countless ways for thousands of years as well. I think the safest judgment is that they're both needed for different reasons.

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