First, a disclaimer: if anybody ever tells you that an interpretation of a work is invalid because "that's not what the author intended," throw them off an overpass; they're better off coming back as a lobster.
Second, the opposite view is equally dogmatic and flawed. This is the harder point to make and I'll start by extolling some of the virtues of this view before kicking it down a notch.. A peer of mine once brilliantly said about analyzing Lolita "If we were to bring Nabokov back from the dead to ask him what he intended, he'd probably just pop out of his grave and start lying." This is quite true on many levels; on a quite literal level, there's no way you can guarantee an honest statement of intent; just because an author is saying it as opposed to writing it or phrasing it in a direct manner rather than an indirect manner (i.e. telling a story, what a concept!) that doesn't make it any more of a foundation since it isn't verifiable.
I can take this further by saying that intent simply isn't verifiable. It has no objective existence; you can tell your best friend what your intent about writing a story is and then lie to everybody else, but what you said to your best friend doesn't have any objectively verifiable basis; it only exists in your head! This seems somewhat banal, but it's a less metaphyiscal way of stating the fact that subjective ideas can only be mapped, they cannot be verified.* So it would seem that talking about intent is silly; it doesn't objectively "exist", it's something we can only infer in some unquantifiable way by privileging someone's "direct" statements or by looking at the biography of an author and using our idea of what their life was like to suggest how some events may have informed their work.
But this argument seems a bit weak. Is anything in literary interpretation ever objectively verifiable? Answering "yes" to that question seems absurd (if you think otherwise, feel free to speak up; I'm just saying that right now I really don't see any good argument.) So what are we doing then in analyzing literature? We're making sense of its impact and its relationship to the world by constructing a narrative of our own. While others may have strongly disagreed with me on the following point, I'll still make it: narratives are fundamentally about people and primarily reflect our existence as social creatures. When we read a novel or watch a TV show, we socially construct characters from the words on the page or the actors on the screen despite what's most likely a complete poverty of information; we may not know the entirety of their (imaginary) life experience, but just like a famous author, we construct a narrative from a limited biography (and body of canonical works; After the Quake isn't representative of Haruki Murakami, I swear!) and create a being with a life of its own.
One of the most important factors in our social construction of human beings is the idea of intentionality. We infer intentions when it comes to everything people do; perhaps as a way of masking all of the noisy details and deviations of a person's behavior or maybe because we really can learn who to trust and who not to.** Without ascribing intentions, we can't construct a picture of a person or empathize with someone; thus the reason why a heroic or tragic story on the news will captivate us but a statistic can only glance off the (somewhat) rational surface of our minds. The same goes for literature; not just in constructing characters but also in how we construct the story as a whole. There is always a narrative voice telling the story, however passive or indirect; and just as we listen closely to a personal story told to a trusted friend, we "listen" to a piece of literature in order to figure out what to make of the story it contains.
To put it another way, every story always has a storyteller; implicit or otherwise. Our idea of the storyteller is informed and constrained by many things; social norms, the conventions of genre, the idea that they're trying to entertain us (think about the last mystery/thriller you saw; you have a pretty good idea of why the most obvious suspect wasn't the traitor/murderer/villain,) and so forth. A former professor of mine rightfully responded to this point by bringing up the point that many of these ideas are different than a mere statement of intent because we can create a more objectively verifiable case about things like social customs and generic conventions. I agree with them insofar that making blanket statements about what someone intended isn't a good way to make an argument; our idea of someone's intention is as subjective as the author's own intent and an argument requires definite common ground. I still find it necessary, however, to acknowledge that we ultimately create an interpretation of the story that is itself a narrative and in order to do that we create an intent behind the storytelling. But I digress.
All storytellers are actually implicit; even if we know the author or are listening to an orator right in front of us, we don't know every last detail of that person's life, we've constructed a simplified version in order to relate them to the story that they're telling. The point is that this implicit storyteller informs our own effort to make sense of the story and in order to let such a storyteller inform us about the story we endow them with intentionality.*** Storytelling is fundamentally a social enterprise; it depicts complex social relationships (to the point that we can hate Nina Meyers for killing Teri Bauer) with very little information and it makes an impression on us by allowing us to read into how the story is told. From an evolutionary (and completely hypothetical) perspective, stories began as a means of communication about complex social relationships and so we're always scrutinizing the storyteller who must have borne witness to the events and who must have some motive behind telling us the story. But I (once again) digress.
We can't read a story without inferring something about the storyteller's intent and we can't have any understanding of a story without imagining a common ground between ourselves and the author. This is why Beyonce's songs will never do it for me. She talks about guys leaving her in so many of her songs (Single Ladies, Why Don't You Love Me, Say My Name...) but she's been dating Jay-Z for practically all of her adult life and is now married to him. I can't see veyr much authenticity in what she's saying. Jay-Z never left her and she started dating him when she was 21, so it seems unlikely that she has much to be going off of.
People have asked me why I continue to enjoy Lady Gaga despite the seeming artificiality of her songs about partying and seduction (she was a workaholic in school and is more of one now.) That's a good question. I suppose that most of Lady Gaga's songs in The Fame seemed somewhat reflexive and ironic to me. I know that's not a very sophisticated critique, but the difference is that Beyonce, for all of her singing and dancing talent and her picture perfect looks, just comes off to me as too damned earnest for her to have any implicit commentary in her lyrics. Of course, this is just the Beyonce that I've imagined for myself; the truth is that I don't know the first thing about her, and neither does anybody else outside of her personal life.
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*My amateur knowledge of phenomenology and semiotics causes me to think that this statement suggests the respective roles of both schools. Semiotics is the study of mappings whereas phenomenology is the study of where mappings come from.
**To be fair, narratives were much more reliable back in the Pleistocene when the world wasn't so damned interconnected. I take no credit for this idea; see The Black Swan by Nassim Taleb.
***A stronger argument that I'm tempted to make is that this idea of the implicit storyteller is necessary to create any sort of narrative context; generic conventions, social customs and even the specific language/dialect that we're reading in is some subjective phenomena independent of the physical text (how could it be a physical property of the text?) that we see as an act of communication between teller and listener. To put this in a more familiar perspective, Peirce concluded that all signs require three elements: a signifier, a singified and an interpretant. Without a social construction that binds the storyteller (imagined or not) and the listener, there's no code with which to link sign and signified.
Friday, October 22, 2010
Friday, October 15, 2010
Humans aren't Machines
To some, the answer may be "well, duh." To others, it may seem that I'm making a poetically admirable but superficial statement that's obviated by the fact that everything is a collection of small atomic parts that interact to form an emergent system.
As the title suggests, I'd like to make an argument against the latter; but I'd also like to ask the former group to read along. Why? Because this isn't based on a metaphysical defiance of science but in fact something of a declaration that science and spirituality are quite compatible; in fact, I will be saying that reducing human beings to machines is deeply un-scientific. But I digress.
First thing's first: yes, using a very loose definition of machine* you can argue that all living things are machines; but it's a pretty banal and in fact misleading definition. Why misleading? Because the word machine has a whole lot of connotations and when it comes to a word, you can change the definition without sufficiently changing the connotations of the word. Machines are seen generally as artificial, unthinking, heartless, cold and calculating (I could go on, but you get the point.) But could we really make these accusations at a phenomena so general and abstract as a system that emerges from interacting parts?
These misleading connotations have a particular moral hazard; they encourage a very mechanistic and quite possibly nihilist view of the world. I'd like to note that I'm not saying that a mechanistic interpretation existence is bad in itself; that's science and I happen to think like most people that science is a very good thing. But when we take the word machine, with all its implications, and slap it on everything we see regardless of the context in which we're talking about it, our world view starts to become an outright perversion of science. This isn't just some spiritual quibble; in many ways it leads our thinking to become deeply un-scientific. This may sound odd, but in order to make this point I need to touch upon the cultural properties of machines.
Machines were historically created as something to aid and simplify human labor, starting as tools in the hunter-gatherer period. Since then, we've gotten to the point of automated assembly lines and computers. When making a machine, one generally needs to specify the problem and the solution in a way that can easily be understood as separate parts; not only in order to come up with a feasible design before building it, but also for the sake of being able to figure out what went wrong if the machine fails. For the entirety of Civilization, machines have been understood as a configuration of parts that can be understood how each part contributes to fulfilling the machine's function and whose actions are predictable. This sounds like a loaded statement, but it only comes from the logic of why and how we create tools and machines; by the fact that it was necessary to produce a reliable outcome and that in order to do so the logic had to be sufficiently simple. Note that this even applies to machines like random number generators; we may not be able to predict the number, but we can fully understand and predict how each part will contribute to the process of creating that random number.
But humans are hardly like this (or any animal for that matter.) We may be able to derive general ideas about living things by discovering the most basic moving parts or performing some specific experiments, but the interactions between these parts and the emergent patterns that come from them are well beyond our current comprehension. Unlike machines, organisms are almost entirely unpredictable. In the paradigm of physics, this doesn't matter because physics is only interested in the simplest forces and smallest parts; no physicist has to actually come up with any predictions about the human condition. In this context, it's perfectly safe to define a machine as anything that converts energy from one form to another.
But what of the many other things that we're looking to understand? By taking this definition of machine from physics and glibly applying it to every other schema through which we look at humans, we've turned a blind eye to the fundamental randomness of organisms. By this, I am not making any metaphysical argument about free-will/chance/determinism, but using randomness in the mathematical sense, which simply states that if you can't predict it (due to a lack of information or otherwise), then it's random for all intents and purposes. It's no wonder then that we've failed to create AI that portrays humans in any life-like manner, that we still wonder why shamanism or religion is sometimes a better alternative to clinical treatment** or that a thousand economists with PhDs couldn't see the imminent collapse of the world financial system.
The mechanistic view of the world is appropriate for fields and paradigms in which its objects of study can be sufficiently understood in such a light. Once we let this view pervade the rest of our thoughts, we end up looking at the map and not the territory. Calling living things "machines" in a general sense does just this by implying that their parts and behaviors are comprehensible as such and gives the world a false sense of predictability. Reducing the complexities of life in this fashion isn't just offensive, it's moronic.
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*The formal definition of machine is an object that converts energy from one form to another. By this definition, anything that materially exists is a machine.
**For the record, I am not trashing clinical treatment of people in need of help. I am the son of a psychologist and a pediatric nurse. I believe that medical professionals are oftentimes helpful because they are usually very scientific in how they rely on data. I should also note that my complaint with the mechanistic view of the universe is not with empiricism; true empiricism acknowledges what we don't know and doesn't rely on representations. What I am suggesting is that in the face of randomness, clinical treatment doesn't always make sense.
As the title suggests, I'd like to make an argument against the latter; but I'd also like to ask the former group to read along. Why? Because this isn't based on a metaphysical defiance of science but in fact something of a declaration that science and spirituality are quite compatible; in fact, I will be saying that reducing human beings to machines is deeply un-scientific. But I digress.
First thing's first: yes, using a very loose definition of machine* you can argue that all living things are machines; but it's a pretty banal and in fact misleading definition. Why misleading? Because the word machine has a whole lot of connotations and when it comes to a word, you can change the definition without sufficiently changing the connotations of the word. Machines are seen generally as artificial, unthinking, heartless, cold and calculating (I could go on, but you get the point.) But could we really make these accusations at a phenomena so general and abstract as a system that emerges from interacting parts?
These misleading connotations have a particular moral hazard; they encourage a very mechanistic and quite possibly nihilist view of the world. I'd like to note that I'm not saying that a mechanistic interpretation existence is bad in itself; that's science and I happen to think like most people that science is a very good thing. But when we take the word machine, with all its implications, and slap it on everything we see regardless of the context in which we're talking about it, our world view starts to become an outright perversion of science. This isn't just some spiritual quibble; in many ways it leads our thinking to become deeply un-scientific. This may sound odd, but in order to make this point I need to touch upon the cultural properties of machines.
Machines were historically created as something to aid and simplify human labor, starting as tools in the hunter-gatherer period. Since then, we've gotten to the point of automated assembly lines and computers. When making a machine, one generally needs to specify the problem and the solution in a way that can easily be understood as separate parts; not only in order to come up with a feasible design before building it, but also for the sake of being able to figure out what went wrong if the machine fails. For the entirety of Civilization, machines have been understood as a configuration of parts that can be understood how each part contributes to fulfilling the machine's function and whose actions are predictable. This sounds like a loaded statement, but it only comes from the logic of why and how we create tools and machines; by the fact that it was necessary to produce a reliable outcome and that in order to do so the logic had to be sufficiently simple. Note that this even applies to machines like random number generators; we may not be able to predict the number, but we can fully understand and predict how each part will contribute to the process of creating that random number.
But humans are hardly like this (or any animal for that matter.) We may be able to derive general ideas about living things by discovering the most basic moving parts or performing some specific experiments, but the interactions between these parts and the emergent patterns that come from them are well beyond our current comprehension. Unlike machines, organisms are almost entirely unpredictable. In the paradigm of physics, this doesn't matter because physics is only interested in the simplest forces and smallest parts; no physicist has to actually come up with any predictions about the human condition. In this context, it's perfectly safe to define a machine as anything that converts energy from one form to another.
But what of the many other things that we're looking to understand? By taking this definition of machine from physics and glibly applying it to every other schema through which we look at humans, we've turned a blind eye to the fundamental randomness of organisms. By this, I am not making any metaphysical argument about free-will/chance/determinism, but using randomness in the mathematical sense, which simply states that if you can't predict it (due to a lack of information or otherwise), then it's random for all intents and purposes. It's no wonder then that we've failed to create AI that portrays humans in any life-like manner, that we still wonder why shamanism or religion is sometimes a better alternative to clinical treatment** or that a thousand economists with PhDs couldn't see the imminent collapse of the world financial system.
The mechanistic view of the world is appropriate for fields and paradigms in which its objects of study can be sufficiently understood in such a light. Once we let this view pervade the rest of our thoughts, we end up looking at the map and not the territory. Calling living things "machines" in a general sense does just this by implying that their parts and behaviors are comprehensible as such and gives the world a false sense of predictability. Reducing the complexities of life in this fashion isn't just offensive, it's moronic.
---------------------------------------------------------------------------------------
*The formal definition of machine is an object that converts energy from one form to another. By this definition, anything that materially exists is a machine.
**For the record, I am not trashing clinical treatment of people in need of help. I am the son of a psychologist and a pediatric nurse. I believe that medical professionals are oftentimes helpful because they are usually very scientific in how they rely on data. I should also note that my complaint with the mechanistic view of the universe is not with empiricism; true empiricism acknowledges what we don't know and doesn't rely on representations. What I am suggesting is that in the face of randomness, clinical treatment doesn't always make sense.
Tuesday, October 12, 2010
Data vs. Narrative
This is an odd topic for a post, since I don't think many people think about data and narrative as particularly contrasting with each other, but I think there are important differences and similarities that should be addressed. A narrative as we know is a story, something that's told to us to make a point, to amuse us or to help us make sense of something in general. Data is a collection of raw numbers or labels that links two or more things together; the amount of young adults that have jobs, the amount of reported car accidents in America in a given year, etc.
So, let's first take care of why I'm bringing up this question in the first place. What's the point of comparing and contrasting data and narratives? Well, a narrative is, generally speaking, a way of making sense of some series of events. It illustrates causality (note to literary theorists: please bear with my questionable simplification; part of the use of this is understanding narratives better, this is just a good starting point.) If narratives explain why something happened, then they may be able to tell us something about what's going to happen next. By this definition, it's really no different than a scientific hypothesis (literary theorists: just keep running with it). More simply, we can think of this as being given a bunch of data points and connecting them with a mathematical function of some kind; i.e. fitting them to a curve:
Some data...
And a narrative to explain it!
I should make a note that it's perfectly acceptable that these narratives could be wrong. A new data point could be shown that doesn't fit with the curve that I drew, thus forcing me to draw a new curve. In fact, there are an endless number of curves I could draw to fit those points; some of which may look exactly the same close up but wildly different when you zoom out. As an interesting side-note, this illustrates pretty well what Wolfgang Iser calls the inexhaustibility of the text. What I mean by this is that when reading a book, one creates a "world" inside their head that matches what they've read; but there are an infinite number of "worlds" that could match this, with any number of (currently) unnecessary ideas unconsidered. As the reader continues, they find new statements in the book that have to be accounted for either by changing previous assumptions or by adding new details to the "world" that they've created in their head.*
So why is a narrative not just a scientific hypothesis or some formula that matches a bunch of data points? The answer can be found in part of my digression; that as we read a text, we have to consider new details in evaluating what's going on and why. A more mathematical analogy is that we have to consider more semantic dimensions; we might read a book that takes place in a Castle, and at first we only have to know the general outline of a castle, but then when the book describes how it made the characters feel alone and vulnerable, we then have to think about ways in which that castle may look or be built that would invoke that kind of a feeling. This all might be very abstract, mind you, but it still works that way on a fundamental level. Also; and this is important, the details that we come up with in the future are going to depend on the details that we've imagined now; so the set of details to be considered are not just latently laid out in the text in some finite way, the details we consider are actually going to derive from each other. So the semantic dimensions (or types of detail, for the less pretentious) are not in any way pre-determined and there could be a potentially infinite amount of them.
Data, like the sample points I showed in my illustration, is different. There are exactly two dimensions to be considered when fitting a line to these points. We already know the entirety of the semantics. Data is entirely delimited; we don't consider things outside of the traits that are enumerated, and there are values specified for each of these traits on every point. Lines drawn to fit the data are ultimately built to fit a static sign system that never changes (I hoped not to have to use the word "sign system", but I don't know how else to explain that.) But once again, there's a catch that might pull data and narrative back together, which I believe to have unknowingly been the source of conflict in a debate I had on this subject with a good friend:
Even if the points exist in a single, unchanging sign system (unlike narratives, in which the sign system changes in unpredictable ways), there's still the question of the scientific hypothesis or the line that fits the curve. Scientific data and points on a chart may both be delimited, but the hypothesis or the function isn't really. Oftentimes, a scientific discovery is made by thinking outside of the conventional data analyzed and therefore the sign system of why the data points are generated in a certain way changes. Similarly, with a mathematical function, the way in which the data points are arranged may require you to add increasing amounts of complexity to the functions; you may add another degree to the polynomial or add a trigonometric function, or something else entirely. So the actual hypothesis/function actually does have a surprising amount in common with narratives in that there is a potentially infinite amount of semantics that can be added.
The difference is that whereas a text is unexhaustible, there isn't the case with a set of data; the hypothesis that's suggested doesn't change the attributes of the data that have to be accounted for. There is an argument from literary theorists, however, that essentially says that as you find these new hypotheses, you create a new paradigm in which the attributes of the data are better changed to fit it and that therefore you have the same intractability as solving a narrative. As tempting as it seems to accept this counter-argument, it still seems to be the case that while new paradigms might introduce new ways of formatting the data, scientific hypotheses still account for the old delimitations; or else it's just solving a straw-man for all intents and purposes. Personally, this argument doesn't interest me, so let's move on to something more important:
The question on my mind from the beginning of this has been one about hypotheses and it'll take a moment to explain. New hypotheses are constantly created from new observations that may have nothing in common with the data. For example, a theory in microeconomics may spring from something in psychology that is not in the paradigm of economics; so it wouldn't show in the data, but it may be the only thing that explains the economic data. Now, let's think about how we perceive the world. When we look at the world, everything is data; our senses send discrete electric imuplses to our brains that quantify our experience as data; the semantics of our sensory experiences are finite, so how do we experience narratives, how can things be inexhaustible?
The answer lies in our neurology. The many inputs and outputs of our brains are interconnected through webs or neurons; these connections being associations between observations. These create clusters of connected neurons we know as ideas. These new ideas which are formed from connections between observations (and also from other ideas) create new conceptions of meaning that we couldn't even hypothesize about before, therefore offering us a process akin to the text in which we can create a virtually unlimited number of narratives starting with the finite amount of data that we initially perceive; in other terms, we can now draw hypotheses from outside of our our original paradigm of experience. Add to this that changes in this web of neurons essentially changes the inputs and outputs into our system (we may still have the same sensory receptors, but they get processed differently as they go further through our cortex) and we've created the reading process in which we connect data with meaning and then re-define data according to that meaning, therefore creating new semantics from semantics that we ourselves had previously created; our experience becomes inexhaustible.
I wasn't sure if I'd get to the end of this one, *phew.* It got a bit obscure near the end (my ability to write clearly is waning with my focus), so if anyone wants me to clear anything up feel free.
-------------------------------------------
*For those interested in this concept, I talk more about it in my earlier entry about the movie Inception. You can also read Iser's original theory in his essay The Reading Process: A Phenomenological Approach.
So, let's first take care of why I'm bringing up this question in the first place. What's the point of comparing and contrasting data and narratives? Well, a narrative is, generally speaking, a way of making sense of some series of events. It illustrates causality (note to literary theorists: please bear with my questionable simplification; part of the use of this is understanding narratives better, this is just a good starting point.) If narratives explain why something happened, then they may be able to tell us something about what's going to happen next. By this definition, it's really no different than a scientific hypothesis (literary theorists: just keep running with it). More simply, we can think of this as being given a bunch of data points and connecting them with a mathematical function of some kind; i.e. fitting them to a curve:
Some data...
And a narrative to explain it!
I should make a note that it's perfectly acceptable that these narratives could be wrong. A new data point could be shown that doesn't fit with the curve that I drew, thus forcing me to draw a new curve. In fact, there are an endless number of curves I could draw to fit those points; some of which may look exactly the same close up but wildly different when you zoom out. As an interesting side-note, this illustrates pretty well what Wolfgang Iser calls the inexhaustibility of the text. What I mean by this is that when reading a book, one creates a "world" inside their head that matches what they've read; but there are an infinite number of "worlds" that could match this, with any number of (currently) unnecessary ideas unconsidered. As the reader continues, they find new statements in the book that have to be accounted for either by changing previous assumptions or by adding new details to the "world" that they've created in their head.*
So why is a narrative not just a scientific hypothesis or some formula that matches a bunch of data points? The answer can be found in part of my digression; that as we read a text, we have to consider new details in evaluating what's going on and why. A more mathematical analogy is that we have to consider more semantic dimensions; we might read a book that takes place in a Castle, and at first we only have to know the general outline of a castle, but then when the book describes how it made the characters feel alone and vulnerable, we then have to think about ways in which that castle may look or be built that would invoke that kind of a feeling. This all might be very abstract, mind you, but it still works that way on a fundamental level. Also; and this is important, the details that we come up with in the future are going to depend on the details that we've imagined now; so the set of details to be considered are not just latently laid out in the text in some finite way, the details we consider are actually going to derive from each other. So the semantic dimensions (or types of detail, for the less pretentious) are not in any way pre-determined and there could be a potentially infinite amount of them.
Data, like the sample points I showed in my illustration, is different. There are exactly two dimensions to be considered when fitting a line to these points. We already know the entirety of the semantics. Data is entirely delimited; we don't consider things outside of the traits that are enumerated, and there are values specified for each of these traits on every point. Lines drawn to fit the data are ultimately built to fit a static sign system that never changes (I hoped not to have to use the word "sign system", but I don't know how else to explain that.) But once again, there's a catch that might pull data and narrative back together, which I believe to have unknowingly been the source of conflict in a debate I had on this subject with a good friend:
Even if the points exist in a single, unchanging sign system (unlike narratives, in which the sign system changes in unpredictable ways), there's still the question of the scientific hypothesis or the line that fits the curve. Scientific data and points on a chart may both be delimited, but the hypothesis or the function isn't really. Oftentimes, a scientific discovery is made by thinking outside of the conventional data analyzed and therefore the sign system of why the data points are generated in a certain way changes. Similarly, with a mathematical function, the way in which the data points are arranged may require you to add increasing amounts of complexity to the functions; you may add another degree to the polynomial or add a trigonometric function, or something else entirely. So the actual hypothesis/function actually does have a surprising amount in common with narratives in that there is a potentially infinite amount of semantics that can be added.
The difference is that whereas a text is unexhaustible, there isn't the case with a set of data; the hypothesis that's suggested doesn't change the attributes of the data that have to be accounted for. There is an argument from literary theorists, however, that essentially says that as you find these new hypotheses, you create a new paradigm in which the attributes of the data are better changed to fit it and that therefore you have the same intractability as solving a narrative. As tempting as it seems to accept this counter-argument, it still seems to be the case that while new paradigms might introduce new ways of formatting the data, scientific hypotheses still account for the old delimitations; or else it's just solving a straw-man for all intents and purposes. Personally, this argument doesn't interest me, so let's move on to something more important:
The question on my mind from the beginning of this has been one about hypotheses and it'll take a moment to explain. New hypotheses are constantly created from new observations that may have nothing in common with the data. For example, a theory in microeconomics may spring from something in psychology that is not in the paradigm of economics; so it wouldn't show in the data, but it may be the only thing that explains the economic data. Now, let's think about how we perceive the world. When we look at the world, everything is data; our senses send discrete electric imuplses to our brains that quantify our experience as data; the semantics of our sensory experiences are finite, so how do we experience narratives, how can things be inexhaustible?
The answer lies in our neurology. The many inputs and outputs of our brains are interconnected through webs or neurons; these connections being associations between observations. These create clusters of connected neurons we know as ideas. These new ideas which are formed from connections between observations (and also from other ideas) create new conceptions of meaning that we couldn't even hypothesize about before, therefore offering us a process akin to the text in which we can create a virtually unlimited number of narratives starting with the finite amount of data that we initially perceive; in other terms, we can now draw hypotheses from outside of our our original paradigm of experience. Add to this that changes in this web of neurons essentially changes the inputs and outputs into our system (we may still have the same sensory receptors, but they get processed differently as they go further through our cortex) and we've created the reading process in which we connect data with meaning and then re-define data according to that meaning, therefore creating new semantics from semantics that we ourselves had previously created; our experience becomes inexhaustible.
I wasn't sure if I'd get to the end of this one, *phew.* It got a bit obscure near the end (my ability to write clearly is waning with my focus), so if anyone wants me to clear anything up feel free.
-------------------------------------------
*For those interested in this concept, I talk more about it in my earlier entry about the movie Inception. You can also read Iser's original theory in his essay The Reading Process: A Phenomenological Approach.
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