{'fraction_non_alphanumeric': 0.019699326075686883, 'fraction_numerical': 0.0, 'mean_word_length': 5.5646258503401365, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Towards a Real Reconciliation of Centralised and Decentralised Approach in Legal Regulation: Application of an AI-Toolkit to a Problem of Jurisprudence

We present results from the implementation of an approach and a toolkit overcoming the limitations of the existing approaches by which law creates mechanisms for regulating socio-economic interests. In the centralized approach the rules come down from the rulers to the ruled ones. That limits the range of interested individuals to establish and implement regulatory mechanisms. In the decentralized approach, if necessary, rulers delegate certain individuals to create rules ad hoc, expanding the range of subjects of decision. This presupposes possibility of power abuse and take conflicting decisions in analogous cases.These disadvantages have been identified back in the ancient Rome. For their overcoming the systems of ius civile and ius honorarium were combined (II B.C.-I A.C.). Such attempts continue, for example within the EU law. A model that overcomes these disadvantages hasn`t been applied so far, because optimal and socially-efficient combination of centralized and decentralized approaches presupposes specific mechanisms. Their establishment and implementation should cover all interested individuals by coordinating and integrating the partial decisions, guaranteeing an optimal adaptability of the society towards the environment. Such mechanisms are achievable by the application of a cognitive approach, methodology and the G-space architecture for identifying inaccurately or mistakenly formulated motivational mechanisms in legislation. We describe how this set of cognitive instruments could be used to correct mistakes in existing legislation and design new, subject to ex-ante defined purposes. We show that the approach, methodology and G-space architecture extend the boundaries of the inter-disciplinary area of Artificial Intelligence in Law.