scholarly journals Lawyers and the Machine. Contemplating the Future of Litigation in the Age of AI

2020 ◽  
Vol 8 (2) ◽  
pp. 231-244
Author(s):  
János Székely
Keyword(s):  
Artificial Intelligence ◽  
Modern World ◽  
Legal Services ◽  
Complex Field ◽  
Optimal Outcome ◽  
Rating Systems ◽  
Factors Influencing ◽  
Main Factors ◽  
Judicial Procedure ◽  
Social Rating

The possible impacts of artificial intelligence (AI) on the modern world constitute a complex field of study. In our analysis, we attempt to explore some possible consequences of the utilization of AI in the judicial field both as regarding adjudication, formerly exclusively reserved for human judges, and in the rendering of legal services by attorneys-at-law. We list the main factors influencing technology adoption and analyse the possible paths the automated management and solution of disputes may take. We conclude that the optimal outcome would be a cooperation of human and artificially intelligent factors. We also outline the conditions in which, following the abandonment of the principle of procedural fairness, AI may be directly utilized in judicial procedure. We conclude that big data solutions, such as social rating systems, are particularly concerning as they constitute a conceivable modality of deploying AI to solve litigious disputes without regard to fundamental human rights as understood today.

scholarly journals DEVELOPING SOLUTION FOR USING ARTIFICIAL INTELLIGENCE TO OBTAIN MORE ACCURATE RESULTS OF THE BASIC PARAMETERS OF RADIO SIGNAL PROPAGATION

2021 ◽  
Vol 11 (1) ◽  
pp. 36-39
Author(s):  
Andrii Shchepak ◽  
Volodimir Parkhomenko ◽  
Vyacheslav Parkhomenko
Keyword(s):  
Artificial Intelligence ◽  
Radio Signal ◽  
Signal Propagation ◽  
Signal Power ◽  
Signal Source ◽  
Calculation Methods ◽  
Factors Influencing ◽  
Basic Parameters ◽  
Main Factors

The article considers the methods of calculating radio signal power. The main factors influencing the distribution and their connection with the error in the calculations of the indicators' peak values are analyzed. The regularities of signal propagation and the correlation between the distance from the radio signal source and the ratio of noise to useful information are determined. These patterns allow us to develop a model of artificial intelligence, which improves the prediction of results compared to existing calculation methods. The obtained results present the efficiency of the offered method.  

Key Factors Influencing the Performance of the Company’s Personnel

2015 ◽  
Vol 4 (4) ◽  
pp. 62-64
Author(s):  
Маслова ◽  
Valyentina Maslova
Keyword(s):  
Detailed Analysis ◽  
Personnel Management ◽  
Business Processes ◽  
Management Style ◽  
Modern World ◽  
Key Factors ◽  
Staff Performance ◽  
Factors Influencing ◽  
Effi Ciency ◽  
Main Factors

The modern world attaches great importance to not only to planning and organizing work in the company, but to the effi ciency of work of its staff . This article analyzes the main factors that aff ect the effi ciency of the personnel of modern Russian and foreign organizations. Among These factors are: professional competencies of employees, regulation of business processes, motivation of labor activity of personnel, management style of the CEO. The paper provides a detailed analysis of each of the identifi edfactors of staff performance. The article contains defi nitions of concepts: competence, regulation of business processes, motivation of labor activity, style of leadership. Particular attention is paid to the study of areas and levels of regulation of business processes, as well as the types of motivation.

Reproduction potential-based differentiation of Russian regions

2020 ◽  
Vol 18 (7) ◽  
pp. 1304-1319
Author(s):  
M.V. Moroshkina
Keyword(s):  
Spatial Development ◽  
Uneven Development ◽  
Regional Differentiation ◽  
Russian Regions ◽  
Policy Documents ◽  
Factors Influencing ◽  
Strategic Policy ◽  
Main Factors ◽  
Per Capita ◽  
Research Period

Subject. This article examines the issues related to changes in reproduction capacity and heterogeneity of the development of Russian regions. Objectives. The article aims to assess regional differentiation and investigate the main factors influencing the uneven development of the areas. Methods. For the study, we used the methods of comparative and correlation analyses. Results. The article identifies groups of leading and lagging Russian regions and assesses the possibility of convergence of Russian regions according to the analyzed indicators, such as GRP, GRP per capita, and the output of industry. Conclusions. The results obtained can be used when preparing strategic policy documents, spatial development programmes and concepts. The observed heterogeneity suggests that the regions maintain their positions throughout the research period.

PROSPECTS OF ARTIFICIAL INTELLIGENCE IN CARRYING OUT THE ONCOLOGICAL COMPONENT OF MEDICAL EXAMINATION OF THE POPULATION

2019 ◽  
Vol 65 (2) ◽  
pp. 234-237
Author(s):  
Vyacheslav Cherenkov ◽  
A. Petrov ◽  
I. Gulkov ◽  
A. Kostyukov
Keyword(s):  
Artificial Intelligence ◽  
Early Diagnosis ◽  
Mass Screening ◽  
Malignant Tumors ◽  
Risk Groups ◽  
Modern World ◽  
Pilot Program ◽  
Urgent Problem ◽  
Gender And Age ◽  
Group Version

Diagnosis of malignant tumors is an urgent problem of the modern world. Early diagnosis depends on General practitioners. The doctor should conduct a systematic examination of the patient regularly, taking into account the risk groups, gender and age. With mass screening, signs of dysplasia or an early focus, developing cancer can «slip away» [1]. Optimization of analysis and examination algorithms is required, which is not always possible for one person. Positive application of the digital program with elements of imaging in Oncology, we were able to create such a class of tasks for the preliminary subjective-objective survey of patients in three versions: with a widescreen screen and consoles for patients (group version up to 15 or more patients), interactive (touch) and tablet. The results of the survey are sent through the accepted channels to the doctor with recommendations for further examination, and the patient is given a coupon. The pilot program showed that the system of such robotic technologies in the future can replace the oncologist in its development to artificial intelligence at the stage of the primary link.

Polymer composites as sensing materials for liquid organic solvents – preliminary results

e-Polymers ◽  
2011 ◽  
Vol 11 (1) ◽  
Author(s):  
Stanislaw Frackowiak ◽  
Monika Maciejewska ◽  
Andrzej Szczurek ◽  
Marek Kozlowski
Keyword(s):  
Electrical Resistivity ◽  
Carbon Black ◽  
Polymer Composites ◽  
Percolation Theory ◽  
Liquid Mixtures ◽  
Organic Liquids ◽  
Volumetric Fraction ◽  
Factors Influencing ◽  
Benzene Toluene ◽  
Main Factors

AbstractCarbon black-filled polymer composites were investigated as sensing materials for organic liquids. Polypropylene and polystyrene which were selected as matrices and various amounts of carbon black were considered as the main factors influencing sensitivity of the composites in view of the percolation theory. Disposable filaments were produced of these materials. Change in their electrical resistivity was measured upon immersion in benzene, toluene, xylene, ethylbenzene and their mixtures. It has been found that studied materials were sensitive to the composition of liquid mixtures of organic solvent. Relationships between the filament response and volumetric fraction of the components were presented. The studied materials have shown promising sensing properties, which suggest their applicability for identification and quantification of multicomponent organic liquids.

Trust in Artificial Intelligence: Meta-Analytic Findings

2021 ◽  
pp. 001872082110139
Author(s):  
Alexandra D. Kaplan ◽  
Theresa T. Kessler ◽  
J. Christopher Brill ◽  
P. A. Hancock
Keyword(s):  
Artificial Intelligence ◽  
Empirical Research ◽  
Meta Analysis ◽  
Automated Vehicles ◽  
Factors Influencing ◽  
Moderating Factors ◽  
Shared Context ◽  
Build Systems ◽  
Significant Factors

Objective The present meta-analysis sought to determine significant factors that predict trust in artificial intelligence (AI). Such factors were divided into those relating to (a) the human trustor, (b) the AI trustee, and (c) the shared context of their interaction. Background There are many factors influencing trust in robots, automation, and technology in general, and there have been several meta-analytic attempts to understand the antecedents of trust in these areas. However, no targeted meta-analysis has been performed examining the antecedents of trust in AI. Method Data from 65 articles examined the three predicted categories, as well as the subcategories of human characteristics and abilities, AI performance and attributes, and contextual tasking. Lastly, four common uses for AI (i.e., chatbots, robots, automated vehicles, and nonembodied, plain algorithms) were examined as further potential moderating factors. Results Results showed that all of the examined categories were significant predictors of trust in AI as well as many individual antecedents such as AI reliability and anthropomorphism, among many others. Conclusion Overall, the results of this meta-analysis determined several factors that influence trust, including some that have no bearing on AI performance. Additionally, we highlight the areas where there is currently no empirical research. Application Findings from this analysis will allow designers to build systems that elicit higher or lower levels of trust, as they require.

Factors Influencing Saudi Parents’ Choice of International Schools in Saudi Arabia

2020 ◽  
Vol 19 (3) ◽  
pp. 220-232
Author(s):  
Hamdah Abdullah Alfaraidy
Keyword(s):  
Socioeconomic Status ◽  
International Education ◽  
School Quality ◽  
International Schools ◽  
Traditional Schools ◽  
Ministry Of Education ◽  
Public And Private ◽  
Mandated Curriculum ◽  
Factors Influencing ◽  
Main Factors

The Saudi Ministry of Education has recently begun to allow all Saudi families to enroll their children in international schools. The international curriculum offered by such schools represents a notably different choice compared with Saudi traditional public and private schools, both of which teach the same state-mandated curriculum. As a result of the change, there has been a surge in demand for international education; the number of schools has increased rapidly, and there has been a steady “student leak” towards them and away from traditional schools. Little is known about why Saudi parents choose to enroll their children in international schools. We explored this question by surveying 431 Saudi parents of children attending such schools to identify the main factors contributing to their choice. Although all factors examined were important to parents, curriculum and overall school quality emerged as the most important; socioeconomic status was not influential in their decisions.

scholarly journals Artificial Intelligence: The Attitude of the Public and Representatives of Various Industries

2021 ◽  
Vol 14 (8) ◽  
pp. 339
Author(s):  
Tatjana Vasiljeva ◽  
Ilmars Kreituss ◽  
Ilze Lulle
Keyword(s):  
Artificial Intelligence ◽  
Primary Data ◽  
Structured Interviews ◽  
The Public ◽  
Qualitative And Quantitative ◽  
Public Survey ◽  
Significant Difference ◽  
Main Factors ◽  
Negative Factors ◽  
Near Future

This paper looks at public and business attitudes towards artificial intelligence, examining the main factors that influence them. The conceptual model is based on the technology–organization–environment (TOE) framework and was tested through analysis of qualitative and quantitative data. Primary data were collected by a public survey with a questionnaire specially developed for the study and by semi-structured interviews with experts in the artificial intelligence field and management representatives from various companies. This study aims to evaluate the current attitudes of the public and employees of various industries towards AI and investigate the factors that affect them. It was discovered that attitude towards AI differs significantly among industries. There is a significant difference in attitude towards AI between employees at organizations with already implemented AI solutions and employees at organizations with no intention to implement them in the near future. The three main factors which have an impact on AI adoption in an organization are top management’s attitude, competition and regulations. After determining the main factors that influence the attitudes of society and companies towards artificial intelligence, recommendations are provided for reducing various negative factors. The authors develop a proposition that justifies the activities needed for successful adoption of innovative technologies.

scholarly journals Implementation Constraints on Israel–Palestine Water Cooperation: An Analysis Using the Water Governance Assessment Framework

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 620
Author(s):  
Liping Dai
Keyword(s):  
Water Governance ◽  
Political Environment ◽  
Assessment Framework ◽  
Foreseeable Future ◽  
Current Technology ◽  
Factors Influencing ◽  
Water Cooperation ◽  
Main Factors ◽  
Enforcement Mechanisms ◽  
Business As Usual

This study uses a diagnostic and multidisciplinary water governance assessment framework to examine the main factors influencing water cooperation on the shared Mountain Aquifer between Israel and Palestine. It finds that effective cooperation between Israel and Palestine is unlikely in the foreseeable future if both parties persist with the business-as-usual approach. What constrains the two parties from achieving consensual agreement are political tensions, the constraints of current technology, the different perceptions of the value of the shared water, the mistrust between the two parties, the lack of external enforcement mechanisms, and the impacts of the domestic political environment.

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