scholarly journals Artificial Intelligence in Enforcement: Epistemological Analysis

2020 ◽  
Vol 13 (2) ◽  
pp. 75
Author(s):  
Alexey I. Ovchinnikov ◽  
Alexey Yu. Mamychev ◽  
Tatiana S. Yatsenko ◽  
Artur Kravchenko ◽  
Yuri A. Kolesnikov
Keyword(s):  
Artificial Intelligence ◽  
Law Enforcement ◽  
Public Administration ◽  
Hermeneutic Circle ◽  
Administrative Functions ◽  
Legal Problems ◽  
Key Factor ◽  
General Norm ◽  
Epistemological Analysis ◽  
Artificial Intelligence Systems

The presented study examines the epistemological and philosophical and legal problems of the introduction of artificial intelligence systems in law enforcement. The article discusses the problematic implementation and use of artificial intelligence to automate the enforcement process, the judiciary and public administration. It is shown that the latter is considered without taking into account a key factor - the specifics of the intellectual process of bringing the general norm to a particular case. The authors show that for artificial intelligence systems, the contextuality of the principles of law is not achievable, while it is extremely necessary in law enforcement. In AI, contextual intellectual procedures cannot be programmed, since the ratio between the norm and the context of its interpretation involves a break through the hermeneutic circle in which the norm is a part and the context of the norm (industry principles) is a whole. The limited possibilities of using artificial intelligence systems in justice are also discussed, it is proved that digitalization in this area will be only instrumental in nature, and the administrative functions of robotic technologies are quite problematic and generally ineffective in the spiritual, moral and ethical dimension.

scholarly journals Features of statistical modeling and forecasting of crime: theoretical aspect

2021 ◽  
pp. 123-130
Author(s):  
Andrey Terekhov ◽  
Sergey Kuvychkov ◽  
Sergey Smirnov
Keyword(s):  
Artificial Intelligence ◽  
Law Enforcement ◽  
Public Administration ◽  
Social Economic ◽  
Theoretical Aspect ◽  
The State ◽  
Optimal Method ◽  
Modeling And Forecasting ◽  
Spatiotemporal Models

The purpose of the work is to provide a theoretical analysis of modern methods of modeling and forecasting the state of crime, which can be used in the system of public administration of the law enforcement sphere. In the course of the research, the peculiarities of using various tools and models for predicting the state of crime are revealed. A significant part of the research of scientists is directed towards the use of spatial and spatiotemporal models, as well as methods of artificial intelligence. The high quality of monthly forecasts is noted. Various economic, social, geographical, temporal and other groups of factors that influence the state of crime are identified. It is established that the quality of the developed crime forecasts depends on the choice of the optimal method and period of forecasting, on the completeness of the information base, including social, economic, legal and other characteristics of the phenomena and processes of public life that affect the criminal situation. It is noted that the practical use of artificial intelligence and econometric analysis methods in predicting the state of crime is becoming particularly relevant at the present time.

scholarly journals The Use of Artificial Intelligence Systems in Law Enforcement

2020 ◽  
Vol 14 (2) ◽  
pp. 206-214
Author(s):  
Diana Stepanenko ◽  
Dmitry Bakhteev ◽  
Yuliana Evstratova
Keyword(s):  
Artificial Intelligence ◽  
Law Enforcement ◽  
Adaptive Learning ◽  
Learning Ability ◽  
Human Cognition ◽  
Technological Basis ◽  
Intelligence System ◽  
Investigation Methods ◽  
Artificial Neural ◽  
Artificial Intelligence Systems

The paper examines the technological basis and opportunities for the use of artificial intelligence systems in law enforcement. The authors describe the investigation methods and the essence of artificial intelligence, and conduct a detailed study of approaches to the taxonomy of its systems. Artificial intelligence today does not only make it possible to solve specific tasks, but also approaches human cognition in its functions. In the present legal environment, programming and automation of crime investigation and solving are used to create information and reference systems, as well as databases and criminalistic algorithms that optimize, for example, the process of developing and verifying criminalistic leads, planning an investigation, supporting the maintenance of order, searching for the culprit, etc. The authors define key features of artificial neural networks viewed as one of the main methods of using artificial intelligence systems in law enforcement, specifically, situational adaptive learning, ability to identify non-obvious links and regularities. The designing of an applied artificial neural network is examined stage-by-stage. At the first stage, a dataset is collected - it is a volume of data for training the network. At the second stage, an algorithm (a set of rules) for learning is selected or designed. After that comes the process of learning and validating its results. The authors analyze the criteria for evaluating the effectiveness of training an artificial intelligence system, including the criteria of precision and accuracy. They single out three key types of operations in the sphere of law enforcement that can be performed by artificial intelligence systems: identification (of visual images and links between the objects of criminalistic study), prediction and classification.

scholarly journals A Kratt as an Administrative Body: Algorithmic Decisions and Principles of Administrative Law

2020 ◽  
Vol 29 ◽  
pp. 47-61
Author(s):  
Ivo Pilving ◽  
Monika Mikiver
Keyword(s):  
Artificial Intelligence ◽  
Public Administration ◽  
Training Data ◽  
Judicial Control ◽  
Learning Capacity ◽  
Data Analyst ◽  
Negative Side Effects ◽  
Judicial Appraisal ◽  
Logic Operations ◽  
Artificial Intelligence Systems

Estonia, as the number-one-ranked country in Europe for the digital public services dimension of the Digital Economy and Society Index, aims at widespread adoption of artificial-intelligence systems to assist or even replace officials in public administration. It is expected that there will be 50 artificial-intelligence applications operating in Estonian public administration by the end of 2020. The machine learning capacity that is often intrinsic in artificial intelligence systems means, in practice, that even the data analyst or programmer who wrote the respective code is later no longer able to explain the parameters behind the decisions. If the state allows a so-called black box to make administrative decisions, further constitutional issues will arise in addition to that of judicial control of such a decision. An administrative decision presumes the implementation of legislation. Owing to the vagueness of the law, a judicial appraisal does not merely involve formal-logic operations, as laws and regulations require interpretation and the consideration of the facts. This is particularly important in making discretionary decisions. Interpretation and consideration must not be limited to the predictions made on the basis of earlier, similar cases by means of statistical methods. It is not rare that a decision on applying a standard needs to be made also in a situation that the legislator has been unable to foresee and for which there is no requisite pattern emerging in the training data fed to an algorithm. The article examines the related principles arising from the Constitution, and one of the conclusions drawn from these is that for factually or legally complex decisions, the weight of the decision must be borne by humans, at least until much more powerful artificial intelligence is developed. However, with the help of learning algorithms individual components and elements of such decisions can be taken. Full automation remains an option in cases of routine administrative decisions that are advantageous for the person(s) concerned and that lack negative side effects for them, as well in cases where all relevant factual circumstances are comprehensible to an algorithm as such and transparent.

Artificial intelligence as a moving force of improvement and innovative development in education and pedagogic

2019 ◽  
pp. 21-30
Author(s):  
M. G. Koliada ◽  
T. I. Bugayova
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Interaction Analysis ◽  
Educational Data Mining ◽  
Main Task ◽  
Intellectual System ◽  
Will Force ◽  
To Come ◽  
Artificial Intelligence Systems

The article discusses the history of the development of the problem of using artificial intelligence systems in education and pedagogic. Two directions of its development are shown: “Computational Pedagogic” and “Educational Data Mining”, in which poorly studied aspects of the internal mechanisms of functioning of artificial intelligence systems in this field of activity are revealed. The main task is a problem of interface of a kernel of the system with blocks of pedagogical and thematic databases, as well as with the blocks of pedagogical diagnostics of a student and a teacher. The role of the pedagogical diagnosis as evident reflection of the complex influence of factors and reasons is shown. It provides the intelligent system with operative and reliable information on how various reasons intertwine in the interaction, which of them are dangerous at present, where recession of characteristics of efficiency is planned. All components of the teaching and educational system are subject to diagnosis; without it, it is impossible to own any pedagogical situation optimum. The means in obtaining information about students, as well as the “mechanisms” of work of intelligent systems based on innovative ideas of advanced pedagogical experience in diagnostics of the professionalism of a teacher, are considered. Ways of realization of skill of the teacher on the basis of the ideas developed by the American scientists are shown. Among them, the approaches of researchers D. Rajonz and U. Bronfenbrenner who put at the forefront the teacher’s attitude towards students, their views, intellectual and emotional characteristics are allocated. An assessment of the teacher’s work according to N. Flanders’s system, in the form of the so-called “The Interaction Analysis”, through the mechanism of fixing such elements as: the verbal behavior of the teacher, events at the lesson and their sequence is also proposed. A system for assessing the professionalism of a teacher according to B. O. Smith and M. O. Meux is examined — through the study of the logic of teaching, using logical operations at the lesson. Samples of forms of external communication of the intellectual system with the learning environment are given. It is indicated that the conclusion of the found productive solutions can have the most acceptable and comfortable form both for students and for the teacher in the form of three approaches. The first shows that artificial intelligence in this area can be represented in the form of robotized being in the shape of a person; the second indicates that it is enough to confine oneself only to specially organized input-output systems for targeted transmission of effective methodological recommendations and instructions to both students and teachers; the third demonstrates that life will force one to come up with completely new hybrid forms of interaction between both sides in the form of interactive educational environments, to some extent resembling the educational spaces of virtual reality.

Public Administration in the Field of Subsoil Use and Protection in Ukraine

2019 ◽  
pp. 169
Author(s):  
Nadiia Maksimentseva
Keyword(s):  
Public Administration ◽  
Phenomenological Study ◽  
Inductive Reasoning ◽  
Mineral Resources ◽  
Selling Price ◽  
Administrative Functions ◽  
The People ◽  
European Court ◽  
And Performance ◽  
Incoming Energy

Laws and regulations backing and governing public administration in subsoil use and protection in Ukraine is gradually gaining priority and importance given incoming energy security and resource self-sufficiency risks alerts for the State as one of the warrants for political and economic independence and guarantees for the people of Ukraine to enjoy and plenipotentiary implement its propitiatory rights set forth in the Constitution of Ukraine with regard to natural resources and benefits that constitute the genuine wealth of the nation. The article is written with the application of inductive reasoning and performance of various research methods, such as case studies, phenomenological study with some focus on nature and source of laws and administrative functions, grounded theory study; also a deep comparative analysis of domestic and overseas legal patterns is carried out. The article is devoted to the research of problems with regard to public administration in the field of subsoil use and protection in Ukraine. The author emphasizes that determination of public administration in the field of subsoil use and protection is a form of public managerial activities of public administration authorities (state authorities, local self-government bodies, self-governing public organizations with the respective competence). It is suggested that these activities are aimed at implementation of the policies in the field of geological exploration of mineral resources, mineral extraction, construction of underground and terrestrial facilities not related to the extraction of minerals, subsoil and environmental protection and they are based on the principles of interaction between subject and object of public administration, discretion, mutual responsibility, self-governance and decentralization when public services are provided. Also, the article presents many judicial practice of the European Court of Human Rights and Citizen, the Supreme Court in the field of public administration in the field of subsoil use and protection. In concluding notes amendments to Subsoil Code of Ukraine, methodology for calculating the initial selling price for the sale of special permit, selection procedures for open special permit tender bid winners and responsibility for subsoil use abandonment costs are suggested by the author.

About digital transformation of the transport industry in Russia

2020 ◽  
Vol 19 (3) ◽  
pp. 95-105
Author(s):  
Natalia V. Vysotskaya ◽  
T. V. Kyrbatskaya
Keyword(s):  
Artificial Intelligence ◽  
Business Model ◽  
Data Science ◽  
Digital Transformation ◽  
Digital Culture ◽  
Blockchain Technology ◽  
Community Approach ◽  
Non Linear ◽  
Transport Industry ◽  
Artificial Intelligence Systems

The article is devoted to the consideration of the main directions of digital transformation of the transport industry in Russia. It is proposed in the process of digital transformation to integrate the community approach into the company's business model using blockchain technology and methods and results of data science; complement the new digital culture with a digital team and new communities that help management solve business problems; focus the attention of the company's management on its employees and develop those competencies in them that robots and artificial intelligence systems cannot implement: develop algorithmic, computable and non-linear thinking in all employees of the company.

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