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The article in the issue 0:0:

The date of the publication:
2020-09-21
The number of pages:
0
The issue:
0:0
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The Authors
Jan Woleński, Urszula Wybraniec-Skardowska, Andrzej Pietruszczak, Yaroslav Shramko, Andrew Schumann, Piotr Łukowski, Matheus Gabriel Barbosa, Fabien Schang, Vadim Verenich, Jaap Hage, Roman Murawski, Arkady Zakrevsky, Andrea Reichenberger, Marina F. Bykova, Robert W. McGee,

Vadim Verenich, Estonian legal semiotician, email: vadimverenich@gmail.com.

ARTICLE:

Neural Networks in Legal Theory

This article explores the domain of legal analysis and its methodologies, emphasizing the significance of generalization in legal systems. It discusses the process of generalization in relation to legal concepts and the development of ideal concepts that form the foundation of law. The article examines the role of logical induction and its similarities with semantic generalization, highlighting their importance in legal decision-making. It also critiques the formal-deductive approach in legal practice and advocates for more adaptable models, incorporating fuzzy logic, non-monotonic defeasible reasoning, and artificial intelligence. The potential application of neural networks, specifically deep learning algorithms, in legal theory is also discussed. The article discusses how neural networks encode legal knowledge in their synaptic connections, while the syllogistic model condenses legal information into axioms. The article also highlights how neural networks assimilate novel experiences and exhibit evolutionary progression, unlike the deductive model of law. Additionally, the article examines the historical and theoretical foundations of jurisprudence that align with the basic principles of neural networks. It delves into the statistical analysis of legal phenomena and theories that view legal development as an evolutionary process. The article then explores Friedrich Hayek’s theory of law as an autonomous self-organizing system and its compatibility with neural network models. It concludes by discussing the implications of Hayek’s theory on the role of a lawyer and the precision of neural networks.

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