Foundations of statistical natural language processing
Foundations of statistical natural language processing
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The Structure and Dynamics of Networks: (Princeton Studies in Complexity)
The Structure and Dynamics of Networks: (Princeton Studies in Complexity)
Meta Math!: The Quest for Omega
Meta Math!: The Quest for Omega
P2P systems in legal networks: another
Proceedings of the 11th international conference on Artificial intelligence and law
The Flood, the Channels and the Dykes: Managing Legal Information in a Globalized and Digital World
Proceedings of the 2009 conference on Law, Ontologies and the Semantic Web: Channelling the Legal Information Flood
Complexity: A Guided Tour
A decentralized recommendation system based on self-organizing partnerships
NETWORKING'06 Proceedings of the 5th international IFIP-TC6 conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications Systems
Cracking down on autonomy: three challenges to design in IT Law
Ethics and Information Technology
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The paper deals with Hayek's classical distinction between cosmos and taxis, i.e., evolution vs. constructivism, spontaneous orders vs. human (political). planning. Recent empirical evidence confirms that the informational complexity of the law is not reducible to taxis alone and, furthermore, orders spontaneously emerge from the complexity of the environment through specific laws of evolution. Whereas, most of the time, today's research on AI & Law focuses on the taxis-side of the law, my aim is to illustrate the informational nature of complex social systems via a theory of spontaneous orders and an evolutionary theory of complex social networks. By distinguishing three levels of analysis, namely information as reality, for reality, and on reality, a topological approach shows how information is produced and distributed in current legal systems, how it is possible to harness these properties and obtain useful applications in the legal domain, while shedding further light on some aspects of current AI research.