scholarly journals Based on Artificial Intelligence in the Judicial Field Operation Status and Countermeasure Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Kongze Zhu ◽  
Lei Zheng
Keyword(s):  
Artificial Intelligence ◽  
Justice System ◽  
Social Resources ◽  
Advanced Technology ◽  
Massive Data ◽  
Personal Privacy ◽  
Judicial Efficiency ◽  
Civil Cases ◽  
Human Thinking ◽  
Operation Status

Artificial intelligence is a recently emerging system that uses computers and big data as the basis to simulate human-like behavior with machines. Artificial intelligence is a way to imitate human thinking by learning massive data knowledge and using algorithms to reason and analyze the data. In the current age of advanced technology, many jobs in the justice system can be replaced by artificial technology technologies. Many courts have now scrutinized the use of artificial intelligence in the judiciary. With artificial intelligence, timely warnings on all aspects of admissions can effectively protect random or outdated trials and allocate social resources appropriately. In addition, it may better redress cases of misconduct and irregular conduct in the judiciary, which is conducive to justice. Based on BP neural network, research on related content and other methods has drawn relevant arguments, which will provide a certain theoretical basis for artificial intelligence to assist the judicial field in the future. The research in this article shows that artificial intelligence is conducive to suppressing duty crimes in the judicial field, promoting the transformation of extensive processing to intensive processing, and is conducive to judicial efficiency. In 2017, there were more than 8 million first-instance civil cases, but only 100,000 cases were closed. But by 2020, with the construction of smart courts, millions of cases out of more than 10 million first-instance civil cases are expected to be closed. The situation has been greatly improved. But at the same time, we also need to prevent the leakage of artificial intelligence to personal privacy, establish and improve corresponding laws and regulations, and coordinate the judgment relationship between the human brain and the machine brain. Artificial intelligence may be more suitable for assisting judicial judgments.

scholarly journals Applications of Non-Standard analysis in Topoi to Mathematical Neurosciences and Artificial Intelligence: Infons, Energons, Receptons (I)

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2048
Author(s):  
Ileana Ruxandra Badea ◽  
Carmen Elena Mocanu ◽  
Florin F. Nichita ◽  
Ovidiu Păsărescu
Keyword(s):  
Mathematical Modeling ◽  
Artificial Intelligence ◽  
Mathematical Model ◽  
Set Theory ◽  
Standard Analysis ◽  
New Methods ◽  
Internal Set ◽  
Human Thinking ◽  
Global Brain ◽  
Non Standard Analysis

The purpose of this paper is to promote new methods in mathematical modeling inspired by neuroscience—that is consciousness and subconsciousness—with an eye toward artificial intelligence as parts of the global brain. As a mathematical model, we propose topoi and their non-standard enlargements as models, due to the fact that their logic corresponds well to human thinking. For this reason, we built non-standard analysis in a special class of topoi; before now, this existed only in the topos of sets (A. Robinson). Then, we arrive at the pseudo-particles from the title and to a new axiomatics denoted by Intuitionistic Internal Set Theory (IIST); a class of models for it is provided, namely, non-standard enlargements of the previous topoi. We also consider the genetic–epigenetic interplay with a mathematical introduction consisting of a study of the Yang–Baxter equations with new mathematical results.

scholarly journals Prospects for Development of Artificial Intelligence in the Scientific Learning of the World

2019 ◽  
Vol 10 (4) ◽  
Author(s):  
Aleksey Stepanenko ◽  
Diana Stepanenko
Keyword(s):  
Artificial Intelligence ◽  
System Approach ◽  
Systematic Approach ◽  
Scientific Information ◽  
Existing Problems ◽  
The World ◽  
Human Thinking ◽  
Intelligence Development ◽  
Artificial Intelligence Systems ◽  
Scientific Learning

In the process of comprehending the prospects for the artificial intelligence development, the authors come to a conclusion that in the scientific learning of the world the problematic issues of the artificial intelligence are connected with problematic issues of recognizing the artificial intelligence systems and ordinary human thinking The article performs an analysis of the concepts of «intelligence» and «artificial intelligence», in the process of which the intelligence is viewed through a systematic approach in its broad sense. The purpose of the article is to present a number of conclusions about the levels of development of scientific studies of the problems under investigation, is there any reason to argue that attempts to implement the epistemological characteristics of thinking in modern artificial intelligence systems have not only been undertaken but also successful, and whether is it possible to talk about full transfer of the intellectual functions to the technical systems, endowing them with epistemological tools (in the context of the discussion about strong and weak versions of the artificial intelligence). The authors study the concept of «phenomenology of intelligence», the perception of intelligence in various historical eras by famous philosophers and scientists of other branches of knowledge; they identify the artificial intelligence as a special branch of science, analyze the existing problems in this field. In writing the article, they use the system approach, the theoretical analysis of and generalization of the scientific information, the historical, predicted, critical and dialectical methods of investigation.

Development of algorithms that simulate the solution of a problem by a person

2022 ◽  
Vol 1 ◽  
pp. 01006
Author(s):  
Iurii V. Filatov
Keyword(s):  
Artificial Intelligence ◽  
High Speed ◽  
Separate Study ◽  
Human Actions ◽  
History Of ◽  
Human Thinking ◽  
Problem Comparison ◽  
The Way

Some algorithms, which are often based on the use of elements of higher mathematics, possessing high speed and compact coding in algorithmic languages, are poorly mastered by most students. It can be assumed that this is due to the difficulty of presenting the principles of their work in the form of human actions in ordinary situations. Thus, a certain contradiction arises between the way of solving the problem that a person resorts to without using a computer and the way we force our computer to solve this problem. Comparison of the process of explaining algorithms speaks in favor of algorithms imitating human thinking. The discussion of the advantages of the algorithms themselves is beyond the scope of this article and undoubtedly deserves a separate study. If artificial intelligence is created, then its creator or creators will certainly be ranked among the outstanding geniuses in the history of civilization, no matter what algorithms it uses. However, so far there is no one to solve problems for us and create algorithms, so we will use all available means and try to teach this to children.

The Effects of Industry 4.0 on Labor Force Attributes and New Challenges

2020 ◽  
pp. 431-454
Author(s):  
Mehmet Saim Aşçı
Keyword(s):  
Artificial Intelligence ◽  
Labor Force ◽  
Industry 4.0 ◽  
The Other ◽  
Advanced Technology ◽  
Significant Problem ◽  
Production Processes ◽  
Other Hand ◽  
New Challenges

Unmanned factories became a topic of discussion after the concept of Industry 4.0 was first introduced in the Hannover Fair in 2001, and increasing the computerization level in business life and supporting the production processes with advanced technology were determined as targets. In this regard, artificial intelligence and increased automation are expected to create new kinds of jobs in the coming years; however, a significant problem is predicted considering that these changes will invalidate a high number of job types exist today. Thus, the workforce will face a severe unemployment threat. As a result of all of this, radical changes in the work methods, along with means of seeking employment, are now considered. The qualities of the work and the workforce are being transformed along with the organization methods of the production. While on the other hand, it becomes evident that education also has to adapt to this transformation. In this study, the issues the labor might have to face during this period will be discussed, along with what could be done to solve these problems.

DNA profiling and databasing: An analysis of issues and challenges in the criminal justice system of Pakistan

2020 ◽  
pp. 002580242096431
Author(s):  
Rao Munir ◽  
Rana Zamin Abbas ◽  
Noman Arshed
Keyword(s):  
Criminal Justice ◽  
Criminal Justice System ◽  
Justice System ◽  
Dna Profiling ◽  
Personal Privacy ◽  
Forensic Evidence ◽  
Exclusion Criteria ◽  
Significant Evidence ◽  
Central Database ◽  
Profiling Analysis

The use of DNA as evidence in judicial trials in Pakistan is fraught with issues and challenges, including sampling, profiling, analysis, inclusion and exclusion criteria, insight and oversight mechanisms, invasion of personal privacy, constitutional safeguards and court admissibility issues. These problems have diminished the significance of this robust forensic evidence and hindered the creation of a central database in the country. This paper discusses these issues and introduces suggestions for the inclusion of DNA as significant evidence in the criminal justice system of Pakistan.

scholarly journals Gut microbiota and artificial intelligence approaches: A scoping review

2020 ◽  
Vol 10 (6) ◽  
pp. 1343-1358
Author(s):  
Ernesto Iadanza ◽  
Rachele Fabbri ◽  
Džana Bašić-ČiČak ◽  
Amedeo Amedei ◽  
Jasminka Hasic Telalovic
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Gut Microbiota ◽  
Scoping Review ◽  
Massive Data ◽  
Data Sets ◽  
Research Groups ◽  
Human Gut ◽  
Massive Data Sets

Abstract This article aims to provide a thorough overview of the use of Artificial Intelligence (AI) techniques in studying the gut microbiota and its role in the diagnosis and treatment of some important diseases. The association between microbiota and diseases, together with its clinical relevance, is still difficult to interpret. The advances in AI techniques, such as Machine Learning (ML) and Deep Learning (DL), can help clinicians in processing and interpreting these massive data sets. Two research groups have been involved in this Scoping Review, working in two different areas of Europe: Florence and Sarajevo. The papers included in the review describe the use of ML or DL methods applied to the study of human gut microbiota. In total, 1109 papers were considered in this study. After elimination, a final set of 16 articles was considered in the scoping review. Different AI techniques were applied in the reviewed papers. Some papers applied ML, while others applied DL techniques. 11 papers evaluated just different ML algorithms (ranging from one to eight algorithms applied to one dataset). The remaining five papers examined both ML and DL algorithms. The most applied ML algorithm was Random Forest and it also exhibited the best performances.

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