Computational legal analytics: concept, ontology, and significance for legal activity

Abstract

This article explores computational legal analytics - its concepts, features, and ontology. The author presents the terms ‘analytics’and ‘legal analytics’. The article focuses on explaining the importance of computational legal analytics (as a segment of digital technologies brought into the professional legal activity) for professional legal activity and the legal field as a whole. The author clarifies the determinants of the need for the emergence and development of computational legal analytics and its value for the legal activities of actors (subjects). The paper presents the author’s definitions for «legal analytics» and «cognitive computing» concepts. Computational legal analytics is based on well-known, well-established, and actively used (at least already being tested) technologies. Such technologies include intellectualized legal search technologies, cognitive computing technologies, natural language computer processing technologies, machine learning technologies (including deep learning), big data processing, and machine-readable law technologies. The author specifies and explains the technologies and possibilities of machine legal analytics, realized by cognitive and other operational capabilities of computer-software complexes, including using artificial intelligence. While preparing the article, the author used research methods of analysis and synthesis, induction, deduction and abduction, classification and modeling, approximation, and formalization. Using these research methods, the author uncovered the essential descriptive characteristics of the phenomenon and concept of machine legal analytics and assessed its prospects.