I have again revisited my initial post, once more editing for clarity and better balance of content. This continues to be a major purpose for this blog, as it is going to be hard for me to gain much academic leverage if the arguments I am trying to present here fail to make coherent sense.
I will try to generate new content as well - I promise! - but I am terribly pressed for the right sort of thinking time just now. In the meantime, I think I have finally unburied my lede... 8-)
Please check out the new version, if you are so inclined.
Saturday, September 5, 2009
Wednesday, July 29, 2009
This blog is coming out of hibernation!
Sorry for the long absence. The more prosaic reasons for my prolonged silence include a move of over a thousand miles and an impending (and perhaps overdue) return to school, but I have also been wrestling with fundamental organizational questions as to the structure of what I am trying to present here. Progress is being made on all fronts, however, and I expect to post more substantively in the near future. Thanks for your patience!
-The Management
more: I've apparently celebrated by tweaking the first paragraphs of the thesis again...
-The Management
more: I've apparently celebrated by tweaking the first paragraphs of the thesis again...
Sunday, May 3, 2009
Slow Posting
Apologies for the slow posting! My workload is currently running at an insane pace, so the next substantive blog post will probably have to wait until things ease up a bit in a couple of weeks.
Sunday, April 19, 2009
More Tweaks
Another round of clarifying edits has been inflicted on the opening of the thesis proposal, thus paving the way for the post currently under construction to continue.
Thursday, April 9, 2009
Housekeeping
As the next two posts are taking longer than I expected to assemble themselves, I have tried to buy some time for myself this week (between concerts) by making minor edits to the blog.
I have added content to the Working Outline, which now includes current editing dates and short introductions, tweaked the wording of most of the other posts to solidify my groundwork, and begun incorporating Amazon links into the References/Reading List post. I have also subtly reshuffled the Table of Contents and appropriately reconnected the affected interpostal links.
If Concerts and Taxes allow, I hope to have another post up within about a week...
-P
I have added content to the Working Outline, which now includes current editing dates and short introductions, tweaked the wording of most of the other posts to solidify my groundwork, and begun incorporating Amazon links into the References/Reading List post. I have also subtly reshuffled the Table of Contents and appropriately reconnected the affected interpostal links.
If Concerts and Taxes allow, I hope to have another post up within about a week...
-P
Sunday, March 29, 2009
Tuesday, March 24, 2009
Working Outline (04/15/09)
The material I have in mind divides naturally into three parts:
I. Introductions-the core structure of the argument
II. Implications-what does it mean?
III. Applications-how can it be used?
It may also prove valuable to set the table with a general philosophical framing of the need for this thesis. For now I intend to begin with the meat of the argument.
The thesis proposal has taken several layers of rewrites to achieve a stable wording (as of 06/03/09), but it finally says more or less what I want it to say. The conceptual structure it establishes will be elaborated in a series of separate posts aimed at the general reader. Hopefully, this piecemeal approach will enable more frequent posting as well as more precise targeting of comments.
Active links in the outline below will go to finished posts, and the dates indicate the most recent revisions.
Part I:
STRUCTURE OF INTELLIGENCE: The first half of Part I will be taken up with a nontechnical introduction to the structure of intelligence, thus setting the conceptual stage for the presentation of the emotional core of the thesis in the second half.
Intelligence I: Representations (04/07/09) A general definition of intelligence as pattern-recognition, retention, and use, together with a short introduction to the neurological basis of this pattern representation.
Intelligence II: Prediction (04/03/09) If I start counting "one, two, three, ...," your memory supplies the next term easily even though it hasn't yet occurred. This post introduces the central role of prediction in intelligence.
analogy An equally significant staple of human intelligence, as indicated by the ease with which "wubbun, tooboo, threebee, ...," can be decoded despite the lack of a specific memory match.
internalized concepts what confers the ability to execute complex learned behaviors (like driving) without paying attention?
computational approaches links to (and possibly an overview of) various efforts in this end of the science
INSTINCTS AND EMOTION: Once a conceptual framework for intelligence has been established, it becomes possible to lay out the heart of the thesis, which proposes that the logic of intelligence can be extended into an elegant but powerful explanatory theory of emotion. Possible subheadings include:
the biology of instincts v reflexes; types of instinctive drives
explanation and development of thesis, with examples and thought experiments
moods v emotions
connections to other theories of emotion (neuroscience, psychology, philosophy)
valence
somatic
judgement
perceptual
other
etc.
More subheadings will emerge, of course. Perhaps philosophical interludes which foreshadow several connections of eventual importance will appear between some of the Part I posts, or perhaps not. Too early to tell.
Part II will most likely deal with corollaries and logical extensions of the unfolded definitional thesis of part I, examining implied integrations, connections, and limitations. It may be organized into broad categories like science, politics, and philosophy, or may be more highly interconnected. We'll see when we get there. A placeholder post has already been set up to get things started, but it must be written with great care and is therefore on hold until a large enough block of uncluttered thinking time emerges. Its structure will be informed by the flow of the arguments in Part I and will guide the eventual shape of the outline of Part II.
Part III will look at actionable policy recommendations and general strategies for applying the ideas found in parts I and II, as it appears that there will be some of a fairly profound and systemic nature. Again more details when they become practical.
Your input is solicited!
I. Introductions-the core structure of the argument
II. Implications-what does it mean?
III. Applications-how can it be used?
It may also prove valuable to set the table with a general philosophical framing of the need for this thesis. For now I intend to begin with the meat of the argument.
The thesis proposal has taken several layers of rewrites to achieve a stable wording (as of 06/03/09), but it finally says more or less what I want it to say. The conceptual structure it establishes will be elaborated in a series of separate posts aimed at the general reader. Hopefully, this piecemeal approach will enable more frequent posting as well as more precise targeting of comments.
Active links in the outline below will go to finished posts, and the dates indicate the most recent revisions.
Part I:
STRUCTURE OF INTELLIGENCE: The first half of Part I will be taken up with a nontechnical introduction to the structure of intelligence, thus setting the conceptual stage for the presentation of the emotional core of the thesis in the second half.
Intelligence I: Representations (04/07/09) A general definition of intelligence as pattern-recognition, retention, and use, together with a short introduction to the neurological basis of this pattern representation.
Intelligence II: Prediction (04/03/09) If I start counting "one, two, three, ...," your memory supplies the next term easily even though it hasn't yet occurred. This post introduces the central role of prediction in intelligence.
analogy An equally significant staple of human intelligence, as indicated by the ease with which "wubbun, tooboo, threebee, ...," can be decoded despite the lack of a specific memory match.
internalized concepts what confers the ability to execute complex learned behaviors (like driving) without paying attention?
computational approaches links to (and possibly an overview of) various efforts in this end of the science
INSTINCTS AND EMOTION: Once a conceptual framework for intelligence has been established, it becomes possible to lay out the heart of the thesis, which proposes that the logic of intelligence can be extended into an elegant but powerful explanatory theory of emotion. Possible subheadings include:
the biology of instincts v reflexes; types of instinctive drives
explanation and development of thesis, with examples and thought experiments
moods v emotions
connections to other theories of emotion (neuroscience, psychology, philosophy)
valence
somatic
judgement
perceptual
other
etc.
More subheadings will emerge, of course. Perhaps philosophical interludes which foreshadow several connections of eventual importance will appear between some of the Part I posts, or perhaps not. Too early to tell.
Part II will most likely deal with corollaries and logical extensions of the unfolded definitional thesis of part I, examining implied integrations, connections, and limitations. It may be organized into broad categories like science, politics, and philosophy, or may be more highly interconnected. We'll see when we get there. A placeholder post has already been set up to get things started, but it must be written with great care and is therefore on hold until a large enough block of uncluttered thinking time emerges. Its structure will be informed by the flow of the arguments in Part I and will guide the eventual shape of the outline of Part II.
Part III will look at actionable policy recommendations and general strategies for applying the ideas found in parts I and II, as it appears that there will be some of a fairly profound and systemic nature. Again more details when they become practical.
Your input is solicited!
Sunday, March 22, 2009
Intelligence II: Prediction (04/03/09)
Understanding the world through abstract neurological representations (as discussed in the previous post) is a wonderfully flexible adaptive strategy which makes all kinds of learning possible. However, in order for the strategy to be viable it must somehow produce information that is accessible in real time, or at least at biologically relevant speeds. According to Christof Koch, experimental psychology suggests that the amount of time necessary to consciously resolve a visual percept is on the order of a quarter-second (the pre-conscious processing of intelligence begins to react on much shorter time frames, and lies behind such concepts as "subliminal marketing," but is also by definition non-conscious). How then can the representational platform of intelligence make it possible for humans to execute cognitively complex tasks in real time, like hunting a deer, driving a car, or performing Dvorák's magnificent cello concerto?
The answer has to do with architecture. The reason intelligence is able to effect conscious control of events on short time scales is that it confers the ability to plan ahead, thus overcoming its own inherent neurobiological speed limits, by making predictions of future events based on information already received. Very roughly speaking, consciousness can stay one or more steps ahead of the situation by using the predictive machinery of intelligence and the storehouse of memory to set goals, and then modify or extend those goals based on what is actually happening.
This is most probably achieved through some biological analogue of an architectural property known to neural network enthusiasts as autoassociation, in which the full retrieval of a stored informational pattern (in this case a neurological representation) is triggered by the input of a partial but matching subset of the full pattern, given an appropriately configured network. This allows the complete perception of a learned pattern before it has finished unfolding in time or space, and it is why you can recognize partially occluded objects or anticipate the progress of familiar sequences. The cascading of this predictive effect upwards through the layers of representations (with each layer adding its own predictions) results in more and more sophisticated predictions spanning longer and longer time frames, ultimately pushing the operation of entire subsets of successful lower-level predictive representations below the threshold of awareness.
On a fundamental level, prediction is central to intelligence.
The clearest articulation of this predictive principle I have yet come across is the "memory-prediction" framework presented by Jeff Hawkins (video link courtesy zenpundit) in his 2004 book "On Intelligence," written with Sandra Blakeslee. "On Intelligence" provides a valuable overview of a number of topics related to the general problem of intelligence, including chapters on Artificial Intelligence, Neural Networks, and the Human Brain, in order to better argue the key roles of Memory and Prediction in what intelligence does, all on its way to expressing a more specific theory of how intelligence might actually work which is based on cortical architecture. While I am not yet well equipped to critique the specifics of his proposed theory, I find the resonances between his argument for intelligence-as-prediction and my extensive teaching, practicing, and performing experience as a professional cellist to be compelling.
From chapter 5 of "On Intelligence":
The above excerpt emphasizes the way parallel predictions across sensory modalities can be combined into rich representations. Let me offer two loosely paraphrased examples to illustrate the way Hawkins believes serial combinations might work.
1) When you learned to read, you started (like all of us) by learning to recognize letters. Once your letter recognition models became sufficiently reliable, your brain was able to use their output as the basis for constructing new predictive models that could recognize entire words. This reliability is why it is no longer necessary for you to consciously process every single letter when you read, although you can, if you focus your attention appropriately. Extending the example, we can say that further modeling of phrase units, sentence structure, and the rules of grammar and composition are the subjects of yet higher layers. Your memory-predictive mastery of lower-level tasks such as letter and word recognition frees up enough processing power to employ higher-level representations, and your resulting knowledge of vocabulary and grammar actually allow you to predict what you will read before you finish each word or senten (see?)
2) The expression "muscle memory" is often used to describe deeply learned complex movements, especially those of musicians and other performing athletes. The speed and relaxed precision of their movements are due to the layers of highly accurate predictive neurological representations of body structure and function (I expect my elbow to be here when I do this), integrated with equally well developed predictive models of the execution of the task at hand, whether it's meeting a ball with a diving catch or playing a cello concerto from memory. The unconscious ease of a physical talent at work bespeaks entire subsets of accurate models pushed below the threshhold of consciousness, whether they were discovered quickly and "naturally" (a great definition of intuition!) or learned and refined more slowly and painfully through extended trial and error.
By now it should be clear that the notion of intelligence as prediction is powerfully illuminating. Before turning to the equally powerful role that analogy plays in dramatically extending the reach of the predictive representations of intelligence, I'd like to add more of my own thoughts about how it is that representations become reliable enough to build into layers in the first place. These "internalized concepts" will be the subject of the next post.
The answer has to do with architecture. The reason intelligence is able to effect conscious control of events on short time scales is that it confers the ability to plan ahead, thus overcoming its own inherent neurobiological speed limits, by making predictions of future events based on information already received. Very roughly speaking, consciousness can stay one or more steps ahead of the situation by using the predictive machinery of intelligence and the storehouse of memory to set goals, and then modify or extend those goals based on what is actually happening.
This is most probably achieved through some biological analogue of an architectural property known to neural network enthusiasts as autoassociation, in which the full retrieval of a stored informational pattern (in this case a neurological representation) is triggered by the input of a partial but matching subset of the full pattern, given an appropriately configured network. This allows the complete perception of a learned pattern before it has finished unfolding in time or space, and it is why you can recognize partially occluded objects or anticipate the progress of familiar sequences. The cascading of this predictive effect upwards through the layers of representations (with each layer adding its own predictions) results in more and more sophisticated predictions spanning longer and longer time frames, ultimately pushing the operation of entire subsets of successful lower-level predictive representations below the threshold of awareness.
On a fundamental level, prediction is central to intelligence.
The clearest articulation of this predictive principle I have yet come across is the "memory-prediction" framework presented by Jeff Hawkins (video link courtesy zenpundit) in his 2004 book "On Intelligence," written with Sandra Blakeslee. "On Intelligence" provides a valuable overview of a number of topics related to the general problem of intelligence, including chapters on Artificial Intelligence, Neural Networks, and the Human Brain, in order to better argue the key roles of Memory and Prediction in what intelligence does, all on its way to expressing a more specific theory of how intelligence might actually work which is based on cortical architecture. While I am not yet well equipped to critique the specifics of his proposed theory, I find the resonances between his argument for intelligence-as-prediction and my extensive teaching, practicing, and performing experience as a professional cellist to be compelling.
From chapter 5 of "On Intelligence":
...[Y]our brain makes low-level sensory predictions about what it expects to see, hear, and feel at every given moment, and it does so in parallel. All regions of your neocortex are simultaneously trying to predict what their next experience will be. Visual areas make predictions about edges, shapes, objects, locations, and motions. Auditory areas make predictions about tones, direction to source, and patterns of sound. Somatosensory areas make predictions about touch, texture, contour, and temperature.
"Prediction" means that the neurons involved in sensing your door become active in advance of them actually receiving sensory input. When the sensory input does arrive, it is compared with what was expected. As you approach the door, your cortex is forming a slew of predictions based on past experience. As you reach out, it predicts what you will feel on your fingers, when you will feel the door, and at what angle your joints will be when you actually touch the door. As you start to push the door open, your cortex predicts how much resistance the door will offer and how it will sound. When your predictions are all met, you'll walk through the door without consciously knowing these predictions were verified. But if your expectations about the door are violated, the error will cause you to take notice. Correct predictions result in understanding. The door is normal. Incorrect predictions result in confusion and prompt you to pay attention...We are making continuous low-level predictions in parallel across all our senses.
The above excerpt emphasizes the way parallel predictions across sensory modalities can be combined into rich representations. Let me offer two loosely paraphrased examples to illustrate the way Hawkins believes serial combinations might work.
1) When you learned to read, you started (like all of us) by learning to recognize letters. Once your letter recognition models became sufficiently reliable, your brain was able to use their output as the basis for constructing new predictive models that could recognize entire words. This reliability is why it is no longer necessary for you to consciously process every single letter when you read, although you can, if you focus your attention appropriately. Extending the example, we can say that further modeling of phrase units, sentence structure, and the rules of grammar and composition are the subjects of yet higher layers. Your memory-predictive mastery of lower-level tasks such as letter and word recognition frees up enough processing power to employ higher-level representations, and your resulting knowledge of vocabulary and grammar actually allow you to predict what you will read before you finish each word or senten (see?)
2) The expression "muscle memory" is often used to describe deeply learned complex movements, especially those of musicians and other performing athletes. The speed and relaxed precision of their movements are due to the layers of highly accurate predictive neurological representations of body structure and function (I expect my elbow to be here when I do this), integrated with equally well developed predictive models of the execution of the task at hand, whether it's meeting a ball with a diving catch or playing a cello concerto from memory. The unconscious ease of a physical talent at work bespeaks entire subsets of accurate models pushed below the threshhold of consciousness, whether they were discovered quickly and "naturally" (a great definition of intuition!) or learned and refined more slowly and painfully through extended trial and error.
By now it should be clear that the notion of intelligence as prediction is powerfully illuminating. Before turning to the equally powerful role that analogy plays in dramatically extending the reach of the predictive representations of intelligence, I'd like to add more of my own thoughts about how it is that representations become reliable enough to build into layers in the first place. These "internalized concepts" will be the subject of the next post.
Friday, March 6, 2009
What's the point? Or, Logical and Philosophical Implications of the Thesis Proposal
The thesis proposal provides a definition of emotion, but that is only half the story. This post will explain its significance.
Comingsoon eventually.
Until then, I recommend moving on to the new Working outline post.
Coming
Until then, I recommend moving on to the new Working outline post.
Intelligence I: Representations (04/07/09)
The thesis proposal made mention of the central roles of prediction and analogy in intelligence but did not explain their significance, and it introduced "representations" and "internalized concepts" without defining the terms at all. This is the first post in a short series (designated Intelligence I, II, etc. in the sidebar's "Table of Contents") which will provide a conceptual overview of these basic elements of intelligence for the general audience, thus providing a fitting prelude to the full exposition of the emotional core of the thesis.
__________________________________________
The obvious place to start a discussion of intelligence is with a definition. Broadly speaking, by intelligence I mean the general capacity to recognize new patterns in the torrent of sensory input and then to further organize those informational patterns into useful mental representations, like "food" or "dangerous animal" or "chair" or "trigonometric function." I do not mean consciousness, attention, or even awareness, although these things are all closely related topics, and I certainly do not mean particular levels of education, capability, wisdom, or experience.
So far as I can tell, this definition puts me on well-traveled theoretical ground; although the exact procedural architecture of intelligence is not yet certain, the fundamental idea that intelligence must involve pattern-recognition seems to be generally agreed upon by most cognitive scientists.
These informational patterns that we perceive, such as "chair" or "Beethoven's 9th Symphony," are recognized using the various modalities of sensory input (sight, smell, hearing, etc.), but it's worth pointing out that by the time those inputs have reached the brain they have already been converted into neuroelectrical impulses, conveying pure information. In this sense, to the brain (or at least the portions of it associated with the operation of intelligence) all patterns are equally abstract. The principal difference between neurological representations of concrete objects like chairs and abstract concepts like trigonometry lies in the directness of the methods available for testing and refining their conceptual details, not in the manner of their construction. This is especially important to remember when comparing richly complex representations of highly abstract concepts such as "self-identity," which can be spread widely through space and time, to the actual limits of the physical body.
Another point about the "information" paradigm that is worth making is that because the essence of information can be codified and defined in the purely abstract world of mathematics, it's adoption (if correct) theoretically allows us to mimic the brain's neurologically-based computational prowess in another substrate, like a computer, if we can just figure out the right processing architecture. While the extraordinary complexity of the human brain makes this is a horrendously difficult and somewhat controversial proposition, the informational approach has yielded some computational insight into what might be going on and continues to be an exciting focus of research.
The final preliminary piece to consider is that the highly organized complexity of each of the representative examples given above stems from the brain's ability to layer concepts, assembling more sophisticated representations out of older, simpler ones. This is nicely illustrated by the way in which a small number of written letters (once learned) are assembled into syllables and then words, which can be further assembled into sentences and then compositions. The higher the number of levels, the richer the capacity for meaning. At the other end of the spectrum, well below the level of consciousness, are individual neuronal inputs whose firing might correspond to the presence or absence of a vertical edge in a certain part of the field of vision. Much more will be said about this hierarchical layering in due course.
So to sum up, the representations with which we understand the world around us are abstractly neurological in nature, although they are assembled from the input of our senses, and their layered structure is the source of their sophistication. This is just enough background to introduce one of the more surprising functions of successful representations--their capacity to predict future events--which is the subject of the next post.
Further Reading:
( listed in rough ascending order of technical detail)
Jeff Hawkins/Sandra Blakeslee "On Intelligence"
Patricia Smith Churchland "Brain-Wise: Studies in Neurophilosophy"
Christof Koch "The Quest for Consciousness: A Neurobiological Approach"
These and other works can be found on my References/Further Reading post.
__________________________________________
The obvious place to start a discussion of intelligence is with a definition. Broadly speaking, by intelligence I mean the general capacity to recognize new patterns in the torrent of sensory input and then to further organize those informational patterns into useful mental representations, like "food" or "dangerous animal" or "chair" or "trigonometric function." I do not mean consciousness, attention, or even awareness, although these things are all closely related topics, and I certainly do not mean particular levels of education, capability, wisdom, or experience.
So far as I can tell, this definition puts me on well-traveled theoretical ground; although the exact procedural architecture of intelligence is not yet certain, the fundamental idea that intelligence must involve pattern-recognition seems to be generally agreed upon by most cognitive scientists.
These informational patterns that we perceive, such as "chair" or "Beethoven's 9th Symphony," are recognized using the various modalities of sensory input (sight, smell, hearing, etc.), but it's worth pointing out that by the time those inputs have reached the brain they have already been converted into neuroelectrical impulses, conveying pure information. In this sense, to the brain (or at least the portions of it associated with the operation of intelligence) all patterns are equally abstract. The principal difference between neurological representations of concrete objects like chairs and abstract concepts like trigonometry lies in the directness of the methods available for testing and refining their conceptual details, not in the manner of their construction. This is especially important to remember when comparing richly complex representations of highly abstract concepts such as "self-identity," which can be spread widely through space and time, to the actual limits of the physical body.
Another point about the "information" paradigm that is worth making is that because the essence of information can be codified and defined in the purely abstract world of mathematics, it's adoption (if correct) theoretically allows us to mimic the brain's neurologically-based computational prowess in another substrate, like a computer, if we can just figure out the right processing architecture. While the extraordinary complexity of the human brain makes this is a horrendously difficult and somewhat controversial proposition, the informational approach has yielded some computational insight into what might be going on and continues to be an exciting focus of research.
The final preliminary piece to consider is that the highly organized complexity of each of the representative examples given above stems from the brain's ability to layer concepts, assembling more sophisticated representations out of older, simpler ones. This is nicely illustrated by the way in which a small number of written letters (once learned) are assembled into syllables and then words, which can be further assembled into sentences and then compositions. The higher the number of levels, the richer the capacity for meaning. At the other end of the spectrum, well below the level of consciousness, are individual neuronal inputs whose firing might correspond to the presence or absence of a vertical edge in a certain part of the field of vision. Much more will be said about this hierarchical layering in due course.
So to sum up, the representations with which we understand the world around us are abstractly neurological in nature, although they are assembled from the input of our senses, and their layered structure is the source of their sophistication. This is just enough background to introduce one of the more surprising functions of successful representations--their capacity to predict future events--which is the subject of the next post.
Further Reading:
( listed in rough ascending order of technical detail)
Jeff Hawkins/Sandra Blakeslee "On Intelligence"
Patricia Smith Churchland "Brain-Wise: Studies in Neurophilosophy"
Christof Koch "The Quest for Consciousness: A Neurobiological Approach"
These and other works can be found on my References/Further Reading post.
Thursday, March 5, 2009
What is this Blog? (03/18/09)
Greetings, and Welcome! This blog exists to share an elegant new definition of emotion, to extend that definition into a powerful explanatory theory of human nature, and to explore the resulting structural implications for human affairs great and small. The process will benefit from the give and take of conversation, so I hope you'll comment or ask questions.
My goal is to write clearly and informally enough for the interested bystander, but also with sufficient breadth and detail to give this argument the beginnings of academic legs. Hopefully I can do both at the same time.
New posts will appear on top as they are written, but their sequence is not firmly tied to their place in the overall argument. For structural reasons a clear introduction of many of my argument's conceptual components creates chicken-and-egg type problems of presentation, so for now I am simply letting the posts write themselves in whatever order they prefer; I'll be filling the gaps as needed.
For those who prefer a more organized reading experience, I am listing the posts in what I believe to be a more helpful reading order under the "Table of Contents" heading at the top of the sidebar. As the blog expands I will also be directly connecting related posts to each other by adding appropriately placed links (for example, next up in the sequence is the thesis proposal), and I'll eventually add tag functionality for a way of searching posts by topic once things really get rolling.
One final caution! The clarity of my writing improves dramatically when I reword and revise over an extended period of time, so rather than waiting to post until everything is perfect (my purpose is conversation, after all) I intend to continue editing until I am satisfied, indicating the most recent revision of each post with a date at the end of its title. Major revisions to content will probably generate new posts, but wording changes in the service of clarity will not.
If you'd like to see a particular topic addressed sooner rather than later, drop a request into the comments and I'll see what I can do!
And now, onward to the thesis proposal!
My goal is to write clearly and informally enough for the interested bystander, but also with sufficient breadth and detail to give this argument the beginnings of academic legs. Hopefully I can do both at the same time.
New posts will appear on top as they are written, but their sequence is not firmly tied to their place in the overall argument. For structural reasons a clear introduction of many of my argument's conceptual components creates chicken-and-egg type problems of presentation, so for now I am simply letting the posts write themselves in whatever order they prefer; I'll be filling the gaps as needed.
For those who prefer a more organized reading experience, I am listing the posts in what I believe to be a more helpful reading order under the "Table of Contents" heading at the top of the sidebar. As the blog expands I will also be directly connecting related posts to each other by adding appropriately placed links (for example, next up in the sequence is the thesis proposal), and I'll eventually add tag functionality for a way of searching posts by topic once things really get rolling.
One final caution! The clarity of my writing improves dramatically when I reword and revise over an extended period of time, so rather than waiting to post until everything is perfect (my purpose is conversation, after all) I intend to continue editing until I am satisfied, indicating the most recent revision of each post with a date at the end of its title. Major revisions to content will probably generate new posts, but wording changes in the service of clarity will not.
If you'd like to see a particular topic addressed sooner rather than later, drop a request into the comments and I'll see what I can do!
And now, onward to the thesis proposal!
Wednesday, February 25, 2009
References/Further Reading (02/07/10)
This post contains the growing portion of my expanding library that I consider to be strongly related to the thesis of this blog. It is opportunistically updated, loosely organized by category, and will eventually include links. Some books are listed in more than one category, and many have not yet been fully read. I hope you enjoy browsing through it! I welcome suggestions for further reading, as my main sources for new material are footnotes, the serendipity of used bookstores, and the internet.
COGNITION AND ARTIFICIAL INTELLIGENCE: (Exploring various computational approaches to cognitive architecture for their logical compatibility with the thesis)
Grim, Patrick, Gary Mar, and Paul St. Denis, "The Philosophical Computer: Exploratory Essays in Philosophical Computer Modeling," 1998
√ Hall, J. Storrs, “Beyond AI: Creating the Conscience of the Machine,” 2007
√ Hawkins, Jeff, "On Intelligence," 2004
√ Hofstadter, Douglas, “Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought,” 1995
√ Hofstadter, Douglas, “Gödel, Escher, Bach: An Eternal Golden Braid,” 1979
√ Holland, Holyoke, Nisbett, and Thagard, “Induction: Processes of Inference, Learning, and Discovery,” 1986
√ Kurzweil, Ray, "The Singularity is Near: When Humans Transcend Biology," 2005
Levitin, Daniel, ed. "Foundations of Cognitive Psychology: Core Readings," 2002
√ Minsky, Marvin, "The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind," 2006
Penrose, Roger, "The Emperor's New Mind: Concerning Computers, Minds, and the Laws of Physics," 1989
√ Pinker, Steven, "How the Mind Works," 1997
√ Thagard, Paul R., “Coherence in Thought and Action,” 2000
√ Thagard, Paul R., “Hot Thought: Mechanisms and Applications of Emotional Cognition,” 2006
MATHEMATICS, PHYSICS, AND PROGRAMMING: (Ongoing refurbishment and expansion of the quantitative toolbox)
Cormen, Leiserson, and Rivest, “Introduction to Algorithms, first edition,” 1990
Feynman, Leighton, and Sands, "The Feynman Lectures on Physics (three volumes)," 1965
√ Hacking, Ian, "An Introduction to Probability and Inductive Logic", 2001
Holland, John H., “Hidden Order: How Adaptation Builds Complexity,” 1995
Mandelbrot, Benoit B., "The Fractal Geometry of Nature," 1977
Mitchell, Melanie, “An Introduction to Genetic Algorithms,” 1996
Penrose, Roger, "The Road to Reality: A Complete Guide to the Laws of the Universe," 2004
√ Pierce, John R., “An Introduction to Information Theory” (2nd edition), 1980
Swokowski, Earl W., “Calculus with Analytic Geometry” (2nd edition), 1979
Wiitala, Stephen A., “Discrete Mathematics: A Unified Approach,” 1987
Williams, Garnett P., "Chaos Theory Tamed," 1997
QUALITATIVE NONLINEARITY: (Mostly non-quantitative works about chaos and complexity)
√ Gleick, James, “Chaos: Making a New Science,” 1987
√ Kelly, Kevin, “Out of Control: The New Biology of Machines, Social Systems, and the Economic World,” 1994
Mandelbrot, Benoit B., "The Fractal Geometry of Nature," 1977
Mitchell, Melanie, "Complexity: A Guided Tour," 2009
Mullin, Tom (ed), “The Nature of Chaos,” 1993
√ Waldrop, M. Mitchell, “Complexity: The Emerging Science at the Edge of Order and Chaos,” 1992
MUSIC: (Original direction of personal research--resolving tensions in cello technique habits by tracing them to mapping errors in mental representations involving bodily movement--which ultimately led to the more general thesis)
√ Alexander, R. McNeill, "Human Bones: A Scientific and Pictorial Investigation," 2005
√ Conable, Barbara, “How to Learn the Alexander Technique: A Manual for Students” (3rd edition), 1995
√ Gray, Henry, “Gray’s Anatomy” (15th edition), 1995
√ Greene, Don, “Audition Success: An Olympic Sports Psychologist Teaches Performing Artists How to Win,” 2001
√ Levitin, Daniel J., "This Is Your Brain on Music: The Science of a Human Obsession," 2006
√ Levitin, Daniel J., "The World in Six Songs: How the Musical Brain Created Human Nature," 2008
√ Mantel, Gerhard, “Cello Technique: Principles and Forms of Movement,” 1995
BIOLOGY/NEUROBIOLOGY: (Brain structure, neuroplasticity, and the biology of instincts)
√ Churchland, Patricia Smith, "Brain-Wise: Studies in Neurophilosophy," 2002
√ Damasio, Antonio, “Descartes’ Error: Reason, Emotion, and the Human Brain,” 1995
Damasio, Antonio, "The Feeling of What Happens: Body and Emotion in the Making of Consciousness," 1999
√ Doidge, Norman, “The Brain that Changes Itself: Stories of Personal Triumph from the Frontiers of Brain Science,” 2007
Geary, David C., "The Origin of Mind: Evolution of Brain, Cognition, and General Intelligence," 2005
√ Hawkins, Jeff, "On Intelligence," 2004
√ Hrdy, Sarah Blaffer, “Mother Nature: Maternal Instincts and How They Shape the Human Species,” 1999
√ Kandel, Eric R., "In Search of Memory: The Emergence of a New Science of Mind," 2006
√ Koch, Christof, "The Quest for Consciousness: A Neurobiological Approach," 2004
√ LeDoux, Joseph, "The Emotional Brain: The Mysterious Underpinnings of Emotional Life," 1996
√ Panksepp, Jaak, "Affective Neuroscience: The Foundations of Human and Animal Emotions," 1998
PHILOSOPHY OF EMOTION: (Current theoretical approaches to emotion from a variety of angles)
√ Damasio, Antonio, “Descartes’ Error: Reason, Emotion, and the Human Brain,” 1995
Damasio, Antonio, "The Feeling of What Happens: Body and Emotion in the Making of Consciousness," 1999
√ LeDoux, Joseph, "The Emotional Brain: The Mysterious Underpinnings of Emotional Life," 1996
√ Minsky, Marvin, "The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind," 2006
PHILOSOPHY OF MIND: (A growing selection of approaches with a less exclusively computational focus)
PHILOSOPHY/HISTORY OF SCIENCE, AND LAYMAN'S BEARINGS: (Self-explanatory!)
√ Aczel, Amir D., "Fermat's Last Theorem: Unlocking the Secret of an Ancient Mathematical Problem," 1996
Bronowski, J., "Science and Human Values," 1956
Feynman, Leighton, and Sands, "The Feynman Lectures on Physics (three volumes)," 1965
√ Goldstein, Rebecca, “Incompleteness: The Proof and Paradox of Kurt Gödel,” 2005
√ Kaku, Michio, "Hyperspace: A Scientific Odyssey Through Parallel Universes, Time Warps, and the 10th Dimension," 1994
√ Kuhn, Thomas S., "The Structure of Scientific Revolutions (2nd Edition, Enlarged)," 1970
Mandelbrot, Benoit B., "The Fractal Geometry of Nature," 1977
√ Petroski, Henry, “To Engineer is Human: The Role of Failure in Successful Design,” 1992
√ Polya, G., "How to Solve It: A New Aspect of Mathematical Method," 1957
√ Sagan, Carl, “The Demon-Haunted World: Science as a Candle in the Dark,” 1996
√ Stewart, Ian, "Why Beauty is Truth: A History of Symmetry," 2007
√ Taleb, Nassim Nicholas, “The Black Swan: The Impact of the Highly Improbable,” 2007
√ Thagard, Paul R., “Coherence in Thought and Action,” 2000
GENERAL PHILOSOPHY: (Initial explorations of general philosophical approaches and their resonances with the meta-philosophical position taken by the thesis, or things that fail to fit earlier categories)
OTHER BOOKS: (Anything else that resonates well enough to stand out, or does well at providing deep systemic background of a useful nature)
√ Ariely, Dan, "Predictably Irrational: The Hidden Forces That Shape Our Decisions," 2008
√ Brin, David, “The Transparent Society: Will Technology Force Us to Choose Between Privacy and Freedom?” 1998
√ Coram, Robert, "Boyd: The Fighter Pilot Who Changed the Art of War," 2002
√ Diamond, Jared, “Collapse: How Societies Choose to Fail or Succeed,” 2005
√ Gladwell, Malcom, "The Tipping Point: How Little Things Can Make a Big Difference," 2002
√ Gleick, James, "Genius: The Life and Science of Richard Feynman," 1992
√ Massie, Robert K., “Dreadnought: Britain, Germany, and the Coming of the Great War,” 1991
√ Pelligrino, Charles, "Ghosts of Vesuvius: A New Look at the Last Days of Pompeii, How Towers Fall, and Other Strange Connections," 2004
√ Surowiecki, James, “The Wisdom of Crowds,” 2004
√ Tuchman, Barbara W., “The First Salute: A View of the American Revolution,” 1988
A green check mark (√ ) indicates material I am currently reading, and a red one (√ ) indicates books I have already read, or at least finished with for now. Anything unchecked is still sadly relegated to anti-library status, for the moment.
As is somewhat indicated by the placement and color of the checkmarks, I started my reading with basic groundwork in emotion theory and neuroscience; now that I have some sense of the landmarks in that particular territory, my current efforts are toward finding my bearings in philosophy and cognition and toward strategically lining up material for a big push of quantitative catchup over the summer.
COGNITION AND ARTIFICIAL INTELLIGENCE: (Exploring various computational approaches to cognitive architecture for their logical compatibility with the thesis)
Grim, Patrick, Gary Mar, and Paul St. Denis, "The Philosophical Computer: Exploratory Essays in Philosophical Computer Modeling," 1998
√ Hall, J. Storrs, “Beyond AI: Creating the Conscience of the Machine,” 2007
√ Hawkins, Jeff, "On Intelligence," 2004
√ Hofstadter, Douglas, “Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought,” 1995
√ Hofstadter, Douglas, “Gödel, Escher, Bach: An Eternal Golden Braid,” 1979
√ Holland, Holyoke, Nisbett, and Thagard, “Induction: Processes of Inference, Learning, and Discovery,” 1986
√ Kurzweil, Ray, "The Singularity is Near: When Humans Transcend Biology," 2005
Levitin, Daniel, ed. "Foundations of Cognitive Psychology: Core Readings," 2002
√ Minsky, Marvin, "The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind," 2006
Penrose, Roger, "The Emperor's New Mind: Concerning Computers, Minds, and the Laws of Physics," 1989
√ Pinker, Steven, "How the Mind Works," 1997
√ Thagard, Paul R., “Coherence in Thought and Action,” 2000
√ Thagard, Paul R., “Hot Thought: Mechanisms and Applications of Emotional Cognition,” 2006
MATHEMATICS, PHYSICS, AND PROGRAMMING: (Ongoing refurbishment and expansion of the quantitative toolbox)
Cormen, Leiserson, and Rivest, “Introduction to Algorithms, first edition,” 1990
Feynman, Leighton, and Sands, "The Feynman Lectures on Physics (three volumes)," 1965
√ Hacking, Ian, "An Introduction to Probability and Inductive Logic", 2001
Holland, John H., “Hidden Order: How Adaptation Builds Complexity,” 1995
Mandelbrot, Benoit B., "The Fractal Geometry of Nature," 1977
Mitchell, Melanie, “An Introduction to Genetic Algorithms,” 1996
Penrose, Roger, "The Road to Reality: A Complete Guide to the Laws of the Universe," 2004
√ Pierce, John R., “An Introduction to Information Theory” (2nd edition), 1980
Swokowski, Earl W., “Calculus with Analytic Geometry” (2nd edition), 1979
Wiitala, Stephen A., “Discrete Mathematics: A Unified Approach,” 1987
Williams, Garnett P., "Chaos Theory Tamed," 1997
QUALITATIVE NONLINEARITY: (Mostly non-quantitative works about chaos and complexity)
√ Gleick, James, “Chaos: Making a New Science,” 1987
√ Kelly, Kevin, “Out of Control: The New Biology of Machines, Social Systems, and the Economic World,” 1994
Mandelbrot, Benoit B., "The Fractal Geometry of Nature," 1977
Mitchell, Melanie, "Complexity: A Guided Tour," 2009
Mullin, Tom (ed), “The Nature of Chaos,” 1993
√ Waldrop, M. Mitchell, “Complexity: The Emerging Science at the Edge of Order and Chaos,” 1992
MUSIC: (Original direction of personal research--resolving tensions in cello technique habits by tracing them to mapping errors in mental representations involving bodily movement--which ultimately led to the more general thesis)
√ Alexander, R. McNeill, "Human Bones: A Scientific and Pictorial Investigation," 2005
√ Conable, Barbara, “How to Learn the Alexander Technique: A Manual for Students” (3rd edition), 1995
√ Gray, Henry, “Gray’s Anatomy” (15th edition), 1995
√ Greene, Don, “Audition Success: An Olympic Sports Psychologist Teaches Performing Artists How to Win,” 2001
√ Levitin, Daniel J., "This Is Your Brain on Music: The Science of a Human Obsession," 2006
√ Levitin, Daniel J., "The World in Six Songs: How the Musical Brain Created Human Nature," 2008
√ Mantel, Gerhard, “Cello Technique: Principles and Forms of Movement,” 1995
BIOLOGY/NEUROBIOLOGY: (Brain structure, neuroplasticity, and the biology of instincts)
√ Churchland, Patricia Smith, "Brain-Wise: Studies in Neurophilosophy," 2002
√ Damasio, Antonio, “Descartes’ Error: Reason, Emotion, and the Human Brain,” 1995
Damasio, Antonio, "The Feeling of What Happens: Body and Emotion in the Making of Consciousness," 1999
√ Doidge, Norman, “The Brain that Changes Itself: Stories of Personal Triumph from the Frontiers of Brain Science,” 2007
Geary, David C., "The Origin of Mind: Evolution of Brain, Cognition, and General Intelligence," 2005
√ Hawkins, Jeff, "On Intelligence," 2004
√ Hrdy, Sarah Blaffer, “Mother Nature: Maternal Instincts and How They Shape the Human Species,” 1999
√ Kandel, Eric R., "In Search of Memory: The Emergence of a New Science of Mind," 2006
√ Koch, Christof, "The Quest for Consciousness: A Neurobiological Approach," 2004
√ LeDoux, Joseph, "The Emotional Brain: The Mysterious Underpinnings of Emotional Life," 1996
√ Panksepp, Jaak, "Affective Neuroscience: The Foundations of Human and Animal Emotions," 1998
PHILOSOPHY OF EMOTION: (Current theoretical approaches to emotion from a variety of angles)
√ Damasio, Antonio, “Descartes’ Error: Reason, Emotion, and the Human Brain,” 1995
Damasio, Antonio, "The Feeling of What Happens: Body and Emotion in the Making of Consciousness," 1999
√ LeDoux, Joseph, "The Emotional Brain: The Mysterious Underpinnings of Emotional Life," 1996
√ Minsky, Marvin, "The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind," 2006
√ Panksepp, Jaak, "Affective Neuroscience: The Foundations of Human and Animal Emotions," 1998
√ Prinz, Jesse J., "Gut Reactions: A Perceptual Theory of Emotion," 2004
√ Robinson, Jenefer, "Deeper than Reason: Emotion and its role in Literature, Music, and Art," 2005
√ Solomon, Robert C. (ed), “Thinking about Feeling: Contemporary Philosophy on Emotions,” 2004
√ Thagard, Paul R., “Hot Thought: Mechanisms and Applications of Emotional Cognition,” 2006
√ Robinson, Jenefer, "Deeper than Reason: Emotion and its role in Literature, Music, and Art," 2005
√ Solomon, Robert C. (ed), “Thinking about Feeling: Contemporary Philosophy on Emotions,” 2004
√ Thagard, Paul R., “Hot Thought: Mechanisms and Applications of Emotional Cognition,” 2006
PHILOSOPHY OF MIND: (A growing selection of approaches with a less exclusively computational focus)
Arendt, Hannah, "The Life of the Mind: The Groundbreaking Investigation on How We Think," 1971
√ Churchland, Patricia Smith, "Brain-Wise: Studies in Neurophilosophy," 2002
Descartes, René, "Philosophical Writings: A Selection Translated and Edited by Elizabeth Anscombe and Peter Thomas Geach," 1971
Geary, David C., "The Origin of Mind: Evolution of Brain, Cognition, and General Intelligence," 2005
Grim, Patrick, Gary Mar, and Paul St. Denis, "The Philosophical Computer: Exploratory Essays in Philosophical Computer Modeling," 1998
√ Hawkins, Jeff, "On Intelligence," 2004
√ Hofstadter, Douglas, “Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought,” 1995
√ Hofstadter, Douglas, “Gödel, Escher, Bach: An Eternal Golden Braid,” 1979
Hofstadter, Douglas and Dennett, Daniel C. (ed), “The Mind’s I: Fantasies and Reflections on Self and Soul,” 1981
James, William, "Psychology," 1892
James, William, "Pragmatism," 1907
Jaynes, Julian, "The Origin of Consciousness in the Breakdown of the Bicameral Mind," 1976
Levitin, Daniel, ed. "Foundations of Cognitive Psychology: Core Readings," 2002
√ Churchland, Patricia Smith, "Brain-Wise: Studies in Neurophilosophy," 2002
Descartes, René, "Philosophical Writings: A Selection Translated and Edited by Elizabeth Anscombe and Peter Thomas Geach," 1971
Geary, David C., "The Origin of Mind: Evolution of Brain, Cognition, and General Intelligence," 2005
Grim, Patrick, Gary Mar, and Paul St. Denis, "The Philosophical Computer: Exploratory Essays in Philosophical Computer Modeling," 1998
√ Hawkins, Jeff, "On Intelligence," 2004
√ Hofstadter, Douglas, “Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought,” 1995
√ Hofstadter, Douglas, “Gödel, Escher, Bach: An Eternal Golden Braid,” 1979
Hofstadter, Douglas and Dennett, Daniel C. (ed), “The Mind’s I: Fantasies and Reflections on Self and Soul,” 1981
James, William, "Psychology," 1892
James, William, "Pragmatism," 1907
Jaynes, Julian, "The Origin of Consciousness in the Breakdown of the Bicameral Mind," 1976
Levitin, Daniel, ed. "Foundations of Cognitive Psychology: Core Readings," 2002
√ Minsky, Marvin, "The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind," 2006
Penrose, Roger, "The Emperor's New Mind: Concerning Computers, Minds, and the Laws of Physics," 1989
Penrose, Roger, "The Emperor's New Mind: Concerning Computers, Minds, and the Laws of Physics," 1989
PHILOSOPHY/HISTORY OF SCIENCE, AND LAYMAN'S BEARINGS: (Self-explanatory!)
√ Aczel, Amir D., "Fermat's Last Theorem: Unlocking the Secret of an Ancient Mathematical Problem," 1996
Bronowski, J., "Science and Human Values," 1956
Feynman, Leighton, and Sands, "The Feynman Lectures on Physics (three volumes)," 1965
√ Goldstein, Rebecca, “Incompleteness: The Proof and Paradox of Kurt Gödel,” 2005
√ Kaku, Michio, "Hyperspace: A Scientific Odyssey Through Parallel Universes, Time Warps, and the 10th Dimension," 1994
√ Kuhn, Thomas S., "The Structure of Scientific Revolutions (2nd Edition, Enlarged)," 1970
Mandelbrot, Benoit B., "The Fractal Geometry of Nature," 1977
√ Petroski, Henry, “To Engineer is Human: The Role of Failure in Successful Design,” 1992
√ Polya, G., "How to Solve It: A New Aspect of Mathematical Method," 1957
√ Sagan, Carl, “The Demon-Haunted World: Science as a Candle in the Dark,” 1996
√ Stewart, Ian, "Why Beauty is Truth: A History of Symmetry," 2007
√ Taleb, Nassim Nicholas, “The Black Swan: The Impact of the Highly Improbable,” 2007
√ Thagard, Paul R., “Coherence in Thought and Action,” 2000
GENERAL PHILOSOPHY: (Initial explorations of general philosophical approaches and their resonances with the meta-philosophical position taken by the thesis, or things that fail to fit earlier categories)
Aristotle, “The Nicomachean Ethics” (trans. David Ross)
Burke, Edmond, "A Philosophical Enquiry into the Origin of our Ideas of the Sublime and Beautiful," ed. James Boulton, 1968
Hazlitt, Henry, "The Foundations of Morality," 1964
Hobbes, Thomas, "Leviathan," ed. C. B. MacPherson, 1968 (1651)
√ Hicks, Stephen R. C., “Explaining Postmodernism: Skepticism and Socialism from Rousseau to Foucault,” 2004
Plato, "The Republic" (trans. Desmond Lee)
Popper, Karl R., “The Poverty of Historicism,” 1964
√ Sharansky, Natan, “The Case for Democracy,” 2004
Burke, Edmond, "A Philosophical Enquiry into the Origin of our Ideas of the Sublime and Beautiful," ed. James Boulton, 1968
Hazlitt, Henry, "The Foundations of Morality," 1964
Hobbes, Thomas, "Leviathan," ed. C. B. MacPherson, 1968 (1651)
√ Hicks, Stephen R. C., “Explaining Postmodernism: Skepticism and Socialism from Rousseau to Foucault,” 2004
Plato, "The Republic" (trans. Desmond Lee)
Popper, Karl R., “The Poverty of Historicism,” 1964
√ Sharansky, Natan, “The Case for Democracy,” 2004
OTHER BOOKS: (Anything else that resonates well enough to stand out, or does well at providing deep systemic background of a useful nature)
√ Ariely, Dan, "Predictably Irrational: The Hidden Forces That Shape Our Decisions," 2008
√ Brin, David, “The Transparent Society: Will Technology Force Us to Choose Between Privacy and Freedom?” 1998
√ Coram, Robert, "Boyd: The Fighter Pilot Who Changed the Art of War," 2002
√ Diamond, Jared, “Collapse: How Societies Choose to Fail or Succeed,” 2005
√ Gladwell, Malcom, "The Tipping Point: How Little Things Can Make a Big Difference," 2002
√ Gleick, James, "Genius: The Life and Science of Richard Feynman," 1992
√ Massie, Robert K., “Dreadnought: Britain, Germany, and the Coming of the Great War,” 1991
√ Pelligrino, Charles, "Ghosts of Vesuvius: A New Look at the Last Days of Pompeii, How Towers Fall, and Other Strange Connections," 2004
√ Surowiecki, James, “The Wisdom of Crowds,” 2004
√ Tuchman, Barbara W., “The First Salute: A View of the American Revolution,” 1988
Thesis Proposal: Can Emotion Be Defined In Terms Of Instinct and Intelligence? (03/06/10)
Disclaimer - Because this post is basically a thesis proposal, it is often both dense and terse, which is not terribly helpful for someone unacquainted with some of the concepts it brings up. I'll be unpacking terminology, concepts, arguments, and implications much more thoroughly and accessibly in the near future as this blog unfolds, so until then please bear with me. Many of these topics have already been addressed in considerable detail in the books listed in my References/Reading List post, which can therefore be mined for hints.
Finally, if you haven't just arrived from my introductory post What is this Blog?, you might consider starting there, as it will provide a minimal amount of conceptual and organizational framing for what I am attempting to do here.
-P.
___________________________________________
(and now, the Real Post)
Although emotion is often considered to be a biological drive in its own right, significant and perhaps transformative insights into the fundamental nature of emotion appear when it is reconceptualized as an emergent effect of elegant interactions between the protective functions of instinct and the structural logic of cognition. Accumulated cognitive research suggests that 1) intelligence works in part by using patterns detected in incoming sensory data to make predictions about future inputs and that 2) hierarchical layering and analogy-making combine to stretch those simple predictions into a sophisticated but flexible representational awareness of the world. Given this description, the structural logic of intelligence can be combined at a high level with the presence of instincts to produce the following thesis statement:
The idea can be more compactly expressed in a short qualitative equation:
This general formulation achieves a rare but elegant professional compromise between the physiological and cognitive aspects of emotion, the respective centers of the two uneasily co-dominant camps of emotion research, essentially by positioning these two well-established theoretical planes so that their explanatory strengths interlock rather than oppose. Thanks to the analogical fluidity built into the human concept of self-identity, the visceral, physical nature of emotions can be fully reconciled with the human ability to be emotional at or about things, yielding a remarkably coherent explanation for the richly multi-dimensional variation observed in individual emotional intensity, target, cause, and speed of onset. This newfound theoretical continuity is partially illustrated by the following four examples:
1) Emotional responses that involve already thought out and established aspects of identity strike with instinctive speed, hitting too fast for cognitive warning, but emotional reactions to events that require the cognitive evaluation of identity-related events, such as implications based on the construction of analogies or chains of reasoning, must unfold no faster than the relatively slow speed at which active cognition takes place;
2) Complex emotions can be considered as system-wide instinctive responses to parallel internalized identity roles that are temporarily in conflict, such as "friend" and "competitor" or "career scientist" and "parent," rather than as serially layered emotional responses to a single, monolithic identity. This is possible because the many overlapping models of self-identity are initially constructed by intelligence from the bottom up rather than the top down, following an organizational structure based on local success rather than global coherence, and they are only later integrated as needed;
3) A single stimulus is capable of provoking wildly different emotional reactions from individual to another, even though all humans share the same general instinctive hardwiring and cognitive architecture, because the intensity of an instinctive response is always directly proportional to the relative status of its target identity component within each personal identity constellation, and because identity constructs are subject to endless individual variation in culture, education, environment, and experience;
4) The individuality of emotional reactions is further amplified by the interplay of emotions with moods, which this theory describes as instinctive reactions to energy-budgeting assessments based on the differences between subjective estimates of the energy available and equally subjective estimates of the energy required to reach a desired goal.
Further investigation suggests that the vast internal complexity of human emotional life can be comprehensively mapped as a combined function of just three global factors: 1) a powerful instinctive pressure, probably supplied by several interacting sets of hardwired instinctive drives operating on different time scales; 2) the higher-level coherence problems faced by identity because of its representational origin in the massively parallel, bottom-up, loosely hierarchical organization of intelligence; and 3) the unique analogical ease with which humans extend their emotional domains, effortlessly investing identity in other people, possessions, past and future events, nations, personal roles, and ideological positions. Both logic and experience suggest that it is not necessary for these investments to be internally coherent in order for them to be instinctively defended.
On a more abstract systemic level, the richness of the emotional experience by anything possessing both self-representational cognitive capacity and an accompanying set of hardwired instincts is likely to correlate strongly with the degree of meta-representational prowess provided by the resident intelligence, but the overall character of that emergent emotional experience should be directly traceable to the specific structure of its supporting cognitive and instinctive architecture. This suggests a plausible emotional and evolutionary continuity between humanity and the rest of the animal kingdom, but it may also raise some interesting implications for Artificial Intelligence researchers.
From a computational perspective, this framework appears likely to allow the mathematical expression of emotion as an emergent consequence of the dynamical interplay between instinct and the structural logic of cognition. If this proposition can be formalized, then the incorporation of appropriate “constants of instinctive force” into various cognitive models might result in the successful modeling of individual emotional effects. In turn, an integrated approach to cognition and emotion may facilitate more effective agent-based modeling of the incompletely rational behavior exhibited by large populations. A rigorous pursuit of the computational underpinnings of cognitive modeling and the mathematics needed to model complex adaptive systems in detail would allow the investigation of the efficacy of this proposal at a much higher level of quantitative resolution.
___________________________________________
In addition to its computational possibilities, an integrated view of emotion and cognition creates valuable logical linkages which allow profound philosophical insight into human affairs on many levels, generating what appear to be far-reaching practical applications. You will eventually be able to read more on this aspect of the theory here, once I have collected enough time and information to write the post.
Finally, if you haven't just arrived from my introductory post What is this Blog?, you might consider starting there, as it will provide a minimal amount of conceptual and organizational framing for what I am attempting to do here.
-P.
___________________________________________
(and now, the Real Post)
Although emotion is often considered to be a biological drive in its own right, significant and perhaps transformative insights into the fundamental nature of emotion appear when it is reconceptualized as an emergent effect of elegant interactions between the protective functions of instinct and the structural logic of cognition. Accumulated cognitive research suggests that 1) intelligence works in part by using patterns detected in incoming sensory data to make predictions about future inputs and that 2) hierarchical layering and analogy-making combine to stretch those simple predictions into a sophisticated but flexible representational awareness of the world. Given this description, the structural logic of intelligence can be combined at a high level with the presence of instincts to produce the following thesis statement:
"The instincts which evolved to protect the physical body must also act in defense of the sense of identity, an abstract cognitive representation of self assembled by intelligence and extended by analogy, and their autonomous actions to that effect are directly perceived as moods and emotions."
The idea can be more compactly expressed in a short qualitative equation:
Instincts --> (Sense of Identity <-- Intelligence) = Emotions
This general formulation achieves a rare but elegant professional compromise between the physiological and cognitive aspects of emotion, the respective centers of the two uneasily co-dominant camps of emotion research, essentially by positioning these two well-established theoretical planes so that their explanatory strengths interlock rather than oppose. Thanks to the analogical fluidity built into the human concept of self-identity, the visceral, physical nature of emotions can be fully reconciled with the human ability to be emotional at or about things, yielding a remarkably coherent explanation for the richly multi-dimensional variation observed in individual emotional intensity, target, cause, and speed of onset. This newfound theoretical continuity is partially illustrated by the following four examples:
1) Emotional responses that involve already thought out and established aspects of identity strike with instinctive speed, hitting too fast for cognitive warning, but emotional reactions to events that require the cognitive evaluation of identity-related events, such as implications based on the construction of analogies or chains of reasoning, must unfold no faster than the relatively slow speed at which active cognition takes place;
2) Complex emotions can be considered as system-wide instinctive responses to parallel internalized identity roles that are temporarily in conflict, such as "friend" and "competitor" or "career scientist" and "parent," rather than as serially layered emotional responses to a single, monolithic identity. This is possible because the many overlapping models of self-identity are initially constructed by intelligence from the bottom up rather than the top down, following an organizational structure based on local success rather than global coherence, and they are only later integrated as needed;
3) A single stimulus is capable of provoking wildly different emotional reactions from individual to another, even though all humans share the same general instinctive hardwiring and cognitive architecture, because the intensity of an instinctive response is always directly proportional to the relative status of its target identity component within each personal identity constellation, and because identity constructs are subject to endless individual variation in culture, education, environment, and experience;
4) The individuality of emotional reactions is further amplified by the interplay of emotions with moods, which this theory describes as instinctive reactions to energy-budgeting assessments based on the differences between subjective estimates of the energy available and equally subjective estimates of the energy required to reach a desired goal.
Further investigation suggests that the vast internal complexity of human emotional life can be comprehensively mapped as a combined function of just three global factors: 1) a powerful instinctive pressure, probably supplied by several interacting sets of hardwired instinctive drives operating on different time scales; 2) the higher-level coherence problems faced by identity because of its representational origin in the massively parallel, bottom-up, loosely hierarchical organization of intelligence; and 3) the unique analogical ease with which humans extend their emotional domains, effortlessly investing identity in other people, possessions, past and future events, nations, personal roles, and ideological positions. Both logic and experience suggest that it is not necessary for these investments to be internally coherent in order for them to be instinctively defended.
On a more abstract systemic level, the richness of the emotional experience by anything possessing both self-representational cognitive capacity and an accompanying set of hardwired instincts is likely to correlate strongly with the degree of meta-representational prowess provided by the resident intelligence, but the overall character of that emergent emotional experience should be directly traceable to the specific structure of its supporting cognitive and instinctive architecture. This suggests a plausible emotional and evolutionary continuity between humanity and the rest of the animal kingdom, but it may also raise some interesting implications for Artificial Intelligence researchers.
From a computational perspective, this framework appears likely to allow the mathematical expression of emotion as an emergent consequence of the dynamical interplay between instinct and the structural logic of cognition. If this proposition can be formalized, then the incorporation of appropriate “constants of instinctive force” into various cognitive models might result in the successful modeling of individual emotional effects. In turn, an integrated approach to cognition and emotion may facilitate more effective agent-based modeling of the incompletely rational behavior exhibited by large populations. A rigorous pursuit of the computational underpinnings of cognitive modeling and the mathematics needed to model complex adaptive systems in detail would allow the investigation of the efficacy of this proposal at a much higher level of quantitative resolution.
___________________________________________
In addition to its computational possibilities, an integrated view of emotion and cognition creates valuable logical linkages which allow profound philosophical insight into human affairs on many levels, generating what appear to be far-reaching practical applications. You will eventually be able to read more on this aspect of the theory here, once I have collected enough time and information to write the post.
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