Special Workshop on Artificial Intelligence and Law

Ανακοινώθηκε το Special Workshop on Artificial Intelligence and Law, το οποίο οργανώνεται στα πλαίσια του 24ου Παγκομσίου Συνεδρίου Φιλοσοφίας του Δικαίου και Κοινωνικής Φιλοσοφίας, στο Πεκίνο στις 15-20 Σεπτεμβρίου 2009.

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AI approaches to the complexity of legal systems: Multilingual ontologies, Multiagent systems, Distributed networks

Work on Artificial Intelligence and Law has been particularly fruitful in the last decade. Besides providing advanced computer applications for the legal domain such as knowledge based systems and intelligent information retrieval, research on AI and law has developed innovative interdisciplinary models for understanding legal systems and legal reasoning, which are highly significant for philosophy of law and legal theory. Among such models, we can mention, for instance, logical frameworks for feasible legal reasoning and dialectical argumentation, logics of normative positions, theories of case-based reasoning, and computable models of legal concepts.
Recently, research on models of legal systems and legal reasoning has merged with research on multiagent systems, which enable the animation of such models: normative structures may provide guidance to, and result from, the interaction of digital agents, that is autonomous entities able to act and communicate, in the pursuit of their purposes, possibly accepting the constraints of violable rules. By developing computable models including not only legal norms and concepts but also legal agents (with the associated roles and procedures) we can go beyond the statics of a legal system, i.e., its representation as a set of norms and concepts, and capture the social, interactive and dialectical dynamics of the law (using also ideas from game theory). An even more recent line of research in AI and law uses social network analysis to model the evolution of the law: This means identifying the patterns of emergent behavior of complex social networks and the ways to anticipate and control such dynamics.
Today there is a strong need not only to integrate research in AI and law within legal theory, but also to encompass the different branches of research in AI and law: When different branches are developing quickly, the risk is in fact missing the opportunities to exchange knowledge and methodologies. This is particularly so in the case of ‘multiagent systems’-approach and social network analysis, that share concepts and objects of study, but often present merely superficial convergences in practice as well as in theory.
Multilingual ontologies provide an important opportunity for integrating different trends of research in AI and law as those mentioned above: Logical models of norms and concepts, multiagent systems, and distributed networks.
The inspiring idea of the 24th IVR World Congress – “Global Harmony and the Rule of Law” – can indeed be approached by developing models of legal knowledge concerning both its structure and content, in order to promote mutual understanding and communication between different legal systems and cultures. By achieving all the more precise models of legal concepts – from multilingual dictionaries to taxonomies and legal ontologies, namely formal models of legal conceptualization – we enhance our comprehension of legal cultures, of their commonalities and differences. Moreover, in this way we profit increasingly from computer support in managing legal knowledge, drawing on commonalities and bridging differences for deeper understanding.
Legal ontologies, in particular, support the creation of multiagent systems for the law – where the different agents can understand one-another by sharing the same ontologies, or through the awareness of their different conceptual structures – which can be useful, for instance, in electronic commerce. Legal ontologies can profit from social network analysis, which could indicate what terms are fundamental for comparison. The study of how legal information is produced and distributed in complex social systems makes it possible to follow the semantic evolution of the network through its own topology, since the set of nodes with highest degree represents the main core of the taxonomy with the shortest average distance-concepts. The domain of multi-system and
multi-lingual ontologies not only offers the opportunity to integrate artificial intelligence with legal theory, but also with comparative legal studies.
The relation of legal ontologies, multiagent systems, and distributed networks, is only one, albeit important, among many other examples of AI and law. The aim of the workshop is thus to offer effective support for the exchange of knowledge and methodological approaches between scholars from different scientific fields, by highlighting their similarities and differences. The comparison of multiple formal approaches to the law – such as logical models, cognitive theories, argumentation frameworks, graph theory, game theory, as well as opposite perspectives like the internal and the external viewpoints – should stress possible convergences in the realm, say, of conceptual structures, argumentation schemes, emergent behaviors, learning evolution, adaptation, simulation, etc. The overall aim is to promote a fruitful interaction between some of the most striking contributions to AI research on contemporary legal systems.

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