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Artificial intelligence: Difference between revisions
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:''The computer’s configuration on May 1, 2012 '''''was''''' XYZ''<br> | :''The computer’s configuration on May 1, 2012 '''''was''''' XYZ''<br> | ||
Machine language will typically say: | Machine language will typically say: | ||
:''Where <DATE<sub>x</sub>> equals “May 1 2012”, let CONFIGURATION<sub>x</sub> equal “XYZ”''<br> | :''Where <DATE<sub>x</sub>> equals “May 1 2012”, let <CONFIGURATION<sub>x</sub>> equal “XYZ”''<br> | ||
This way a computer does not need to conceptualise ''itself yesterday'' as something different to ''itself today'', which means it doesn’t need to conceptualise “itself” ''at all''. Therefore, computers don’t need to be self-aware. Unless computer syntax undergoes some dramatic revolution (it could happen: we have to assume human language went through that revolution at some stage) computers will never be self-aware. | This way a computer does not need to conceptualise ''itself yesterday'' as something different to ''itself today'', which means it doesn’t need to conceptualise “itself” ''at all''. Therefore, computers don’t need to be self-aware. Unless computer syntax undergoes some dramatic revolution (it could happen: we have to assume human language went through that revolution at some stage) computers will never be self-aware. | ||
====It can’t handle ambiguity==== | ====It can’t handle ambiguity==== | ||
Computer language is designed to allow machines to follow algorithms flawlessly. It needs to be deterministic — a given proposition must generate a unique binary operation — and it can’t allow any ''variability'' in interpretation. This makes it different from a natural language, which is shot through with both. | Computer language is designed to allow machines to follow algorithms flawlessly. It needs to be deterministic — a given proposition must generate a unique binary operation with no ambiguity — and it can’t allow any ''variability'' in interpretation. This makes it different from a natural language, which is shot through with both ambiguity and variability. Synonyms. [[Metaphor|Metaphors]]. Figurative language. All of these are incompatible with code, but utterly fundamental to natural language. | ||
*It is very hard for a machine language to handle things like “reasonably necessary” or | *It is very hard for a machine language to handle things like “reasonably necessary” or “[[best endeavours]]”. | ||
*Coding for | *Coding for the sort of redundancy which is rife in English (especially in legal English, which rejoices in [[triplet|triplets]] like “give, devise and bequeath”) dramatically increases the complexity of any [[algorithm|algorithms]]. | ||
*Aside from | *Aside from redundancy there are many meanings which are almost, but not entirely, the same, which must be coded for separately. This increases the load on the dictionary and the cost of maintenance. | ||
====The ground rules cannot change==== | ====The ground rules cannot change==== | ||
The logic and grammar of machine language and the assigned meaning of expressions is profoundly static. The corollary of the narrow and technical purpose for which machine language is used is its inflexibility: Machines fail to deal with unanticipated change. | The logic and grammar of machine language and the assigned meaning of expressions is profoundly static. The corollary of the narrow and technical purpose for which machine language is used is its inflexibility: ''Machines fail to deal with unanticipated change''. | ||
====Infinite fidelity is impossible==== | ====Infinite fidelity is impossible==== | ||
There is a popular | There is a popular “[[reductionism|reductionist]]” movement at the moment which seeks to atomise concepts with a view to untangling bundled concepts. The belief is that by separating bundles into their elemental parts you can ultimately dispel all ambiguity. A similar attitude influences contemporary markets regulation. This programme aspires to ultimate certainty; a single set of axioms from which all propositions can be derived. From this perspective shortcomings in machine understanding of legal information are purely a function of a lack of sufficient detail the surmounting of which is a matter of time, given the collaborative power of the worldwide internet. The singularity is near: look at the incredible strides made in natural language processing (Google translate), self-driving cars, computers beating grand masters at Chess and Go. | ||
But you can split these into two categories: those which are the product of obvious (however impressive) computational feats - like Chess, Go, Self-driving cars, and those that are the product of statistical analysis, so are rendered as matters of probability (like Google translate). | But you can split these into two categories: those which are the product of obvious (however impressive) computational feats - like Chess, Go, Self-driving cars, and those that are the product of statistical analysis, so are rendered as matters of probability (like Google translate). | ||