Metaphors of the Mind
Metaphors of the Mind
Throughout history, people have drawn parallels between the brain and, by extension, the mind, and the most recent technical breakthrough. These days, everyone is using computer metaphors. Recently, metaphors involving software and (neuronal) networks have supplanted those involving computer hardware. Every area of human knowledge has its fair share of comparison-based attempts at understanding. The structural notion of "tensegrity" has recently been proposed by mathematicians and architects as an explanation for the phenomena of life. It is well-documented that humans have a survival benefit from their propensity to perceive patterns and structures everywhere, even when none exist.
Some people also think these metaphors are false, pointless, or intentionally misleading, therefore they disregard them. But it is the same Mind that generates these metaphors that will ultimately define it. Similar to how "brain-children" are the products of "brain-storming" and "minds" alike, the things or processes that the brain is compared to are likewise conceptual conceptions. If not a physical embodiment of mental processes, then what are computers, software programs, and communications networks?
That is to say, the minds of humans are an essential and sufficient condition for ANYTHING that humans produce. Some devices, like petrol pumps, require a "mind-correlate" factor. Our thoughts may also contain a-priori (not based on experience) or a-posteriori (depending on experience) representations of the "non-human" aspects of the cosmos. The relationship between the human mind and its "excretions," "output," "spin-offs," and "products"—a "correlation," "emulation," "simulation," "representation"—is crucial to comprehending the mind.
The claim that we may learn about an artist via their work, a creator through their creation, and, more broadly, about an origin through any of its derivatives, inheritors, successors, products, or similes is part of a larger category of statements.
When the product's nature is identical to that of its origin, this general contention becomes more stronger. If the father is human and the child is human as well, then there is a wealth of information that can be securely gleaned from the product that can be used to identify the father. We can learn more about the origin if the product is made close to its place of origin. A "thinking machine"—whatever that may mean—that is mechanical, recursive, limiting, and simulated. The brain is also a "thinking machine"—albeit one that is considerably more nimble, adaptable, non-linear, and potentially even qualitatively distinct. There must be some kind of relationship between the two, despite the obvious difference between them. There are two main reasons for their intimate relationship: first, both are "thinking machines" and, secondly, and most importantly, the second one is an offspring of the first. Since this is the case, the computer metaphor is robust. If an organic computer ever materialises, the analogy will take on more significance. If a quantum computer ever comes to fruition, it will surely improve upon certain parts of the metaphor.
By the way, it's not always the case that knowing where something comes from allows us to predict what it will be used for. The number of free variables is excessive. To use a metaphor from Bohr, the presence of a product "collapses" our probability set and expands our knowledge.
A "wave function" describes the starting point; this is, a set of possibilities with associated probabilities, where the possibilities are the products that are theoretically and logically feasible.
However, a superficial comparison to the end result reveals very nothing about its source. Characteristics and characteristics pertaining mostly to form and purpose. You can see these easily. Would this be enough? What does the "true nature" of the beginning tell us if anything? No, it is not correct. All things considered, it is pessimistic: we have no right to seek or assume knowledge of the "true nature" of anything. Metaphysics, not physics, governs this domain. Without stating anything substantial about either micro-processes or the Universe, Quantum Mechanics gives an incredibly accurate explanation of both. Instead of elaborating on one viewpoint or another, modern physics aims to make accurate predictions. It explains nothing; all it does is describe. Whenever an interpretation is put out, such as the Copenhagen interpretation of QM, it encounters philosophical roadblocks and impassable problems. So, many metaphors abound in contemporary science, including "particles" and "waves," to name just two. Scientifically speaking, metaphors are a valuable tool for the "thinking scientist's" toolbox.
Also, a metaphor can evolve across time, mirroring the stages of its inception. Consider the software metaphor in the context of computers:
Data (referred to as "structures") and instruction code (referred to as "functions" or "procedures") were strictly separated in the early days of computers when software applications were written serially in machine language. This was actually a "biological" stage, similar to when the brain (mind) of an embryo was developing. The machine code was a near-perfect match for the hardware's actual wiring. In biology, the instructions are contained within DNA, which is also separated from the data, which consists of amino acids and other things essential to life. An alphabetic order is an extrinsic order that exists only in the mind of the "imposer"; databases were serial, handled on a "listing" basis (called a "flat file"), and had no inherent relationship to each other. They had reached the substrate state and were prepared to be worked with. Functions could only operate on structures when they were "mixed" in the computer (during program execution).
The "relational" organisation of data, of which spreadsheets are a basic example, followed suit, as one might assume. Mathematical formulas were used to establish relationships between data components. As the pregnancy develops, this takes the place of the brain's circuitry.
"Object Orientated Programming Systems" (OOPS) represent the most recent systemic shift. Modules that hold data and instructions in separate parts are called objects. Objects are like "black boxes" (an engineering term): the user knows what they can do with them, but they have no idea how they are put together or what messages are going through inside. The developer has no idea how the object does its tasks or how its secret internal functions become its visible, helpful ones. Things are fleeting, new, and epiphenomenal. To sum up, it's a lot more in line with reality as we know it from contemporary physics.
The system's total efficiency is not determined by the communication (its speed or efficacy), but rather by the fact that it can be established among these black boxes. The key is in the objects' hierarchical and simultaneously fuzzy organisation. Classes are used to organise objects and specify their properties, both actualised and potential. The object's behaviour is determined by its class membership, including its actions and reactions. Additionally, the "inheritance" principle is in play: objects can be organised into new (sub)classes, which allow them to retain the original class's definitions and traits while also acquiring additional features that differentiate them from their parent. Essentially, the classes from which these new ones emerged are the source, and the classes from which they emerged are the products. The procedure is so realistic in its depiction of real-world events that it strengthens the metaphor.
Classes are thus useful as foundational elements. The set of all solvable issues is defined by their permutations. Returning to the Principia Mathematica, it is possible to demonstrate that Turing Machines are an instance of a more general and robust class theory. "Framework applications" modify the structural and functional aspects of both the hardware (computer) and software (computer programs, mind) components in order to integrate them. Brain structures (a priori categories, the collective unconscious, etc.) must contain an analogue.
The reason why one phase replaces another is why we call it evolution. For example, object-oriented databases cannot be merged with relational databases. A "virtual machine" must be built inside the OS in order for Java applets to execute. These stages are very similar to the maturation of the mind-brain pair.
At what points does a metaphor work well? When its inclusion sheds light on the genesis that would have been impossible to discover otherwise. We have already demonstrated that it must have a structural and functional similarity. However, this falls short. This is just the metaphor's "quantitative, observational" part. Another is of a qualitative kind; it has to lay the groundwork for a theory and its associated hypotheses while simultaneously being illuminating, beautiful, concise, and educational. Metaphors are theories that emerge from predetermined standards of logic and aesthetics. To be considered trustworthy, it needs to undergo the kind of extensive testing that is required by scientific inquiry.
In order for the software metaphor to work, the brain needs to have certain characteristics:
In order to set up a feedback parity loop, the electrochemical signal in a neurone must travel both forward and back (to its origin) at the same time. This allows for parity checks to be performed.
A neurone cannot function as a binary (two-state) machine; for example, quantum computers will have many states. In terms of information representation, it needs to be exciting on multiple levels. We must be mistaken if we believe the threshold hypothesis ("all or nothing" firing).
All parts and functions of the brain and its operations must be redundant. This includes the hardware (several centres will carry out the same functions), communications (information transfer channels will be duplicated and sent over multiple channels at once for comparison), retrieval (data excitation can occur in multiple locations at once), and the use of acquired data (through working memory, or "upper")."Representation elements" and "models of the world" must be compared as the fundamental idea of how the brain functions. The end result is a unified view that facilitates forecasting and efficient, fruitful environmental modification.The brain must solve many recursive functions. We could reasonably anticipate discovering that all brain processes can be reduced to computational, mechanically solvable recursive ones. The most fantastical visions of AI will materialise if this occurs, elevating the brain to the status of a Turing Machine. Until then, though, this incredible machine in our brains should be behaving in a strongly recursive fashion.The brain ought to be an entity that can learn and organise itself.
The software metaphor can only be considered strong if all six of these conditions are satisfied. Otherwise, we'll have little choice but to ignore it in preference of a more formidable opponent.
Paranoid machines controlled by Murphy's Laws make up the brain. It doesn't take any chances, instead preparing for the worst case scenario. It can and does not take any chances while precariously balanced and materially fragile, as it is in control of life itself.
Oh my goodness!
Metaphors of the Mind, Volume I
Written by Sam Vaknin, Ph.D.
Source: http://www.articlecity.com/articles/health/article 29.shtml.
creation time: 2007-07-25 12:30:10
subject: medical
article:
Throughout history, people have drawn parallels between the brain and, by extension, the mind, and the most recent technical breakthrough. These days, everyone is using computer metaphors. Recently, metaphors involving software and (neuronal) networks have supplanted those involving computer hardware. Every area of human knowledge has its fair share of comparison-based attempts at understanding. The structural notion of "tensegrity" has recently been proposed by mathematicians and architects as an explanation for the phenomena of life. It is well-documented that humans have a survival benefit from their propensity to perceive patterns and structures everywhere, even when none exist.
Some people also think these metaphors are false, pointless, or intentionally misleading, therefore they disregard them. But it is the same Mind that generates these metaphors that will ultimately define it. Similar to how "brain-children" are the products of "brain-storming" and "minds" alike, the things or processes that the brain is compared to are likewise conceptual conceptions. If not a physical embodiment of mental processes, then what are computers, software programs, and communications networks?
That is to say, the minds of humans are an essential and sufficient condition for ANYTHING that humans produce. Some devices, like petrol pumps, require a "mind-correlate" factor. Our thoughts may also contain a-priori (not based on experience) or a-posteriori (depending on experience) representations of the "non-human" aspects of the cosmos. The relationship between the human mind and its "excretions," "output," "spin-offs," and "products"—a "correlation," "emulation," "simulation," "representation"—is crucial to comprehending the mind.
The claim that we may learn about an artist via their work, a creator through their creation, and, more broadly, about an origin through any of its derivatives, inheritors, successors, products, or similes is part of a larger category of statements.
When the product's nature is identical to that of its origin, this general contention becomes more stronger. If the father is human and the child is human as well, then there is a wealth of information that can be securely gleaned from the product that can be used to identify the father. We can learn more about the origin if the product is made close to its place of origin. A "thinking machine"—whatever that may mean—that is mechanical, recursive, limiting, and simulated. The brain is also a "thinking machine"—albeit one that is considerably more nimble, adaptable, non-linear, and potentially even qualitatively distinct. There must be some kind of relationship between the two, despite the obvious difference between them. There are two main reasons for their intimate relationship: first, both are "thinking machines" and, secondly, and most importantly, the second one is an offspring of the first. Since this is the case, the computer metaphor is robust. If an organic computer ever materialises, the analogy will take on more significance. If a quantum computer ever comes to fruition, it will surely improve upon certain parts of the metaphor.
By the way, it's not always the case that knowing where something comes from allows us to predict what it will be used for. The number of free variables is excessive. To use a metaphor from Bohr, the presence of a product "collapses" our probability set and expands our knowledge.
A "wave function" describes the starting point; this is, a set of possibilities with associated probabilities, where the possibilities are the products that are theoretically and logically feasible.
However, a superficial comparison to the end result reveals very nothing about its source. Characteristics and characteristics pertaining mostly to form and purpose. You can see these easily. Would this be enough? What does the "true nature" of the beginning tell us if anything? No, it is not correct. All things considered, it is pessimistic: we have no right to seek or assume knowledge of the "true nature" of anything. Metaphysics, not physics, governs this domain. Without stating anything substantial about either micro-processes or the Universe, Quantum Mechanics gives an incredibly accurate explanation of both. Instead of elaborating on one viewpoint or another, modern physics aims to make accurate predictions. It explains nothing; all it does is describe. Whenever an interpretation is put out, such as the Copenhagen interpretation of QM, it encounters philosophical roadblocks and impassable problems. So, many metaphors abound in contemporary science, including "particles" and "waves," to name just two. Scientifically speaking, metaphors are a valuable tool for the "thinking scientist's" toolbox.
Also, a metaphor can evolve across time, mirroring the stages of its inception. Consider the software metaphor in the context of computers:
Data (referred to as "structures") and instruction code (referred to as "functions" or "procedures") were strictly separated in the early days of computers when software applications were written serially in machine language. This was actually a "biological" stage, similar to when the brain (mind) of an embryo was developing. The machine code was a near-perfect match for the hardware's actual wiring. In biology, the instructions are contained within DNA, which is also separated from the data, which consists of amino acids and other things essential to life. An alphabetic order is an extrinsic order that exists only in the mind of the "imposer"; databases were serial, handled on a "listing" basis (called a "flat file"), and had no inherent relationship to each other. They had reached the substrate state and were prepared to be worked with. Functions could only operate on structures when they were "mixed" in the computer (during program execution).
The "relational" organisation of data, of which spreadsheets are a basic example, followed suit, as one might assume. Mathematical formulas were used to establish relationships between data components. As the pregnancy develops, this takes the place of the brain's circuitry.
"Object Orientated Programming Systems" (OOPS) represent the most recent systemic shift. Modules that hold data and instructions in separate parts are called objects. Objects are like "black boxes" (an engineering term): the user knows what they can do with them, but they have no idea how they are put together or what messages are going through inside. The developer has no idea how the object does its tasks or how its secret internal functions become its visible, helpful ones. Things are fleeting, new, and epiphenomenal. To sum up, it's a lot more in line with reality as we know it from contemporary physics.
The system's total efficiency is not determined by the communication (its speed or efficacy), but rather by the fact that it can be established among these black boxes. The key is in the objects' hierarchical and simultaneously fuzzy organisation. Classes are used to organise objects and specify their properties, both actualised and potential. The object's behaviour is determined by its class membership, including its actions and reactions. Additionally, the "inheritance" principle is in play: objects can be organised into new (sub)classes, which allow them to retain the original class's definitions and traits while also acquiring additional features that differentiate them from their parent. Essentially, the classes from which these new ones emerged are the source, and the classes from which they emerged are the products. The procedure is so realistic in its depiction of real-world events that it strengthens the metaphor.
Classes are thus useful as foundational elements. The set of all solvable issues is defined by their permutations. Returning to the Principia Mathematica, it is possible to demonstrate that Turing Machines are an instance of a more general and robust class theory. "Framework applications" modify the structural and functional aspects of both the hardware (computer) and software (computer programs, mind) components in order to integrate them. Brain structures (a priori categories, the collective unconscious, etc.) must contain an analogue.
The reason why one phase replaces another is why we call it evolution. For example, object-oriented databases cannot be merged with relational databases. A "virtual machine" must be built inside the OS in order for Java applets to execute. These stages are very similar to the maturation of the mind-brain pair.
At what points does a metaphor work well? When its inclusion sheds light on the genesis that would have been impossible to discover otherwise. We have already demonstrated that it must have a structural and functional similarity. However, this falls short. This is just the metaphor's "quantitative, observational" part. Another is of a qualitative kind; it has to lay the groundwork for a theory and its associated hypotheses while simultaneously being illuminating, beautiful, concise, and educational. Metaphors are theories that emerge from predetermined standards of logic and aesthetics. To be considered trustworthy, it needs to undergo the kind of extensive testing that is required by scientific inquiry.
In order for the software metaphor to work, the brain needs to have certain characteristics:
In order to set up a feedback parity loop, the electrochemical signal in a neurone must travel both forward and back (to its origin) at the same time. This allows for parity checks to be performed.
A neurone cannot function as a binary (two-state) machine; for example, quantum computers will have many states. In terms of information representation, it needs to be exciting on multiple levels. We must be mistaken if we believe the threshold hypothesis ("all or nothing" firing).
All parts and functions of the brain and its operations must be redundant. This includes the hardware (several centres will carry out the same functions), communications (information transfer channels will be duplicated and sent over multiple channels at once for comparison), retrieval (data excitation can occur in multiple locations at once), and the use of acquired data (through working memory, or "upper")."Representation elements" and "models of the world" must be compared as the fundamental idea of how the brain functions. The end result is a unified view that facilitates forecasting and efficient, fruitful environmental modification.The brain must solve many recursive functions. We could reasonably anticipate discovering that all brain processes can be reduced to computational, mechanically solvable recursive ones. The most fantastical visions of AI will materialise if this occurs, elevating the brain to the status of a Turing Machine. Until then, though, this incredible machine in our brains should be behaving in a strongly recursive fashion.The brain ought to be an entity that can learn and organise itself.
The software metaphor can only be considered strong if all six of these conditions are satisfied. Otherwise, we'll have little choice but to ignore it in preference of a more formidable opponent.
Paranoid machines controlled by Murphy's Laws make up the brain. It doesn't take any chances, instead preparing for the worst case scenario. It can and does not take any chances while precariously balanced and materially fragile, as it is in control of life itself.
Oh my goodness!
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