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Code and language: Difference between revisions
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Computer language (for ease of discussion let's call this “code”) differs from ordinary human languages (let’s can these “languages”) in that it has no concept of tense. It can still record and transmit past and future states, but it does so by rendering them in the present. | {{A|Technology|}} | ||
Computer language (for ease of discussion let's call this “code”) differs from ordinary human languages (let’s can these “languages”) in that it has no concept of ''tense''. It can still record and transmit past and future states, but it does so by rendering them in the present. | |||
The present tense is different from the past or the future because it addresses an infinitesimal instant having no duration in time. A given object in the present tense there cannot contradict itself. It can only have one state. | The present tense is different from the past or the future because it addresses an infinitesimal instant having no duration in time. A given object in the present tense there cannot contradict itself. It can only have one state. | ||
Say Switch A has two possible states: On and Off: to describe the state of that switch at any time T, a computer language would describe them thus: <br> | Say Switch A has two possible states: On and Off: to describe the state of that switch at any time T, a computer language would describe them thus: <br> | ||
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But Switch A is an “it”. A past, present and a future. It has a history. <br> | But Switch A is an “it”. A past, present and a future. It has a history. <br> | ||
In computer code, A is simply a common property of existing fields A(T1) to A(Tn). <br> | In computer code, A is simply a common property of existing fields A(T1) to A(Tn). <br> | ||
Both approaches capture the same “external data” - there is no degradation involved in either method - but a language applies a | Both approaches capture the same “external data” - there is no degradation involved in either method - but a language applies a {{t|metaphor}}ical overlay which designates given fields having a common feature as an integral object having a causal history. This history is a causal chain running through the “object”. Thus, unless something intervenes to change it, Switch A’s status at T+n will be the same as its state was at T. There is an equivalent causal chain operating on interactions between discrete integral objects. <br> | ||
By contrast machine code does sees only a correlation between states, and not a causal chain. <br> | By contrast machine code does sees only a correlation between states, and not a causal chain. <br> | ||
It was the great Scottish philosopher David Hume who first observed that the very idea of causality is an explaining fiction that we lay over the raw data of our observations to organise and make sense of them. <br> | It was the great Scottish philosopher David Hume who first observed that the very idea of causality is an explaining fiction that we lay over the raw data of our observations to organise and make sense of them. <br> | ||
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So far we've been talking about a single on/off switch - in any complex system (whether a computer, a machine, a cell, a molecule, or an atom), the simplest possible unit. 1 or 0; existence or non existence. One cannot further reduce. Even here we find, when we are using a natural language, ambiguity. <br> | So far we've been talking about a single on/off switch - in any complex system (whether a computer, a machine, a cell, a molecule, or an atom), the simplest possible unit. 1 or 0; existence or non existence. One cannot further reduce. Even here we find, when we are using a natural language, ambiguity. <br> | ||
The ambiguity, and the power of the history we create, is amplified if we group switches together. All complex systems (brains, organisms, societies, the Internet) are combinations of billions of switches. By selecting the switches that we wish to group together we can identify meta-objects to which we apply a history. Meta objects like “a bicycle” or “a program”, or “you” or “me”. <br> | The ambiguity, and the power of the history we create, is amplified if we group switches together. All complex systems (brains, organisms, societies, the Internet) are combinations of billions of switches. By selecting the switches that we wish to group together we can identify meta-objects to which we apply a history. Meta objects like “a bicycle” or “a program”, or “you” or “me”. <br> | ||
For exactly the same reason any such grouping is (or at one point in time was) an imaginative act: nothing in the underlying configuration of switches requires any grouping at all (we could operate like a code) let alone any particular grouping: the groupings we apply - many of which seem profound - evolved and layered on top of each other throughout the development of natural language. It is a way of organising sensory input to make sense of it. Call this “narratisation” (© {{author|Julian Jaynes}}) or coining a metaphor. <br> | For exactly the same reason any such grouping is (or at one point in time was) an imaginative act: nothing in the underlying configuration of switches requires any grouping at all (we could operate like a code) let alone any particular grouping: the groupings we apply - many of which seem profound - evolved and layered on top of each other throughout the development of natural language. It is a way of organising sensory input to make sense of it. Call this “narratisation” (© {{author|Julian Jaynes}}) or coining a {{t|metaphor}}. <br> | ||
The ability to narratise - the susceptibility of a language to metaphor implies ambiguity. <br> | The ability to narratise - the susceptibility of a language to metaphor implies ambiguity. <br> | ||
That history may be a kind of fiction: the ship of thebes will tend to be treated as a continuous object when, if you look at it as a collection of infinitesimal states, there is not one in common. <br> | That history may be a kind of fiction: the ship of thebes will tend to be treated as a continuous object when, if you look at it as a collection of infinitesimal states, there is not one in common. <br> | ||
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Secondly, arbitrariness. The continuity we assign to related switches and collections of switches is our own invention. Any given switch may have many particular features (“A”ness, “B”ness, “C”ness and so on); which one (or more) we choose to associate with it when we see it as a continuous object is up to us: in our discourse a red car from Italy can be a car (that happens to be red and Italian, a red thing (that happens to be an Italian car), an Italian thing (that happens to be a red car) a red car (that happens to be from Italy) and so on. Any of these groupings is legitimate, but the act of preferring one over another is an act of creative “narratising”: it does not exist in the data - it is a function of the sentence we put it in. (Richard Rorty put it this way: truth is a property of sentences, not objects”. <br> | Secondly, arbitrariness. The continuity we assign to related switches and collections of switches is our own invention. Any given switch may have many particular features (“A”ness, “B”ness, “C”ness and so on); which one (or more) we choose to associate with it when we see it as a continuous object is up to us: in our discourse a red car from Italy can be a car (that happens to be red and Italian, a red thing (that happens to be an Italian car), an Italian thing (that happens to be a red car) a red car (that happens to be from Italy) and so on. Any of these groupings is legitimate, but the act of preferring one over another is an act of creative “narratising”: it does not exist in the data - it is a function of the sentence we put it in. (Richard Rorty put it this way: truth is a property of sentences, not objects”. <br> | ||
This brings us back to an important point. Algorithms can be fiendishly complex but they must have one property: for any input, only one output. They cannot require the machine to see any nuance, or make any value judgment. There cannot be any ambiguity in the instructions. If an algorithm is presented with an input it does not expect (that the algorithm does not cater for) the program will stop. If the algorithm stipulates “you decide what to do next” the program will freeze. <br> | This brings us back to an important point. Algorithms can be fiendishly complex but they must have one property: for any input, only one output. They cannot require the machine to see any nuance, or make any value judgment. There cannot be any ambiguity in the instructions. If an algorithm is presented with an input it does not expect (that the algorithm does not cater for) the program will stop. If the algorithm stipulates “you decide what to do next” the program will freeze. <br> | ||
{{c|Technology}} | |||