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Prolegomena to a postmodern theory of law

University of British Columbia

Research in artificial intelligence and law has stalled because it presumes the model of legal reasoning asserted by legal positivism. An adequate model of legal reasoning must relate legal rules to social goals and must respond to critical perspectives. No existing legal theory accomplishes these tasks. This thesis asserts that postmodernism overcomes current difficulties in constructing an adequate model of legal reasoning. My methodology is to apply results from the sciences of chaos and complex adaptive systems to derive the elements of postmodernism from a mathematical perspective. This shows how systems can spontaneously construct knowledge and improve without assuming the possibility of perfect knowledge about social systems. I show how law behaves as a complex adaptive system and argue that legal reasoning shows the type of knowledge-building accomplished by complex adaptive systems. This implies limitations on what legal reasoning can attempt to accomplish and provides criteria to criticize existing legal theories. Social orders emerge from the concurrent behaviour of many individuals. The utility of social orders for society implies that there is value in individuals behaving according to rules. An important implication of chaos theory is that our knowledge about social orders must in principle remain imprecise. We can model social orders but the models must employ fuzzy concepts that are correlated or causally related probabilistically. The fundamental task of legal reasoning is to mediate the requirements of conflicting social orders. Some social orders are undesirable, so legal reasoning must include a strategy to expose ideology and decadence. When law-makers choose between alternative rules, they must consider the possible impact of each proposed rule upon desirable social orders. In a hard case, a law-maker must choose to impair either of two social orders. Since knowledge about the functioning of the social orders is fuzzy and probabilistic, the law-maker must model the social orders in terms of fuzzy instrumental goals and estimate the probable degree of impairment to the goals by each of the alternative rule possibilities. This thesis confirms and advances the "deep-structure" theory of jurisprudence and its application to legal expert systems.

Thesis/Dissertation

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2008-10-14

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http://hdl.handle.net/2429/2636

Law

University of British Columbia

UBCV

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