scholarly journals The Development of Artificial Intelligence and Risks for the Implementation of Genocide and Mass Killings

2020 ◽  
pp. 119-134
Author(s):  
Narek Poghosyan
Keyword(s):  
Artificial Intelligence ◽  
Code Of Ethics ◽  
Technological Development ◽  
Mass Murder ◽  
Racial Groups ◽  
Negative Consequences ◽  
Autonomous Weapons ◽  
Artificial Intelligence Technology ◽  
Protection Of Human Rights ◽  
Mass Killings

This article illustrates the fact that the accelerating pace of technological development in recent years, in particular the use of artificial intelligence (AI) has raised serious concerns among experts that it, along with its advantages, can pose many dangers to mankind when machines think and make decisions for them. Particularly risky is that the development of AI and autonomous weapons can be used to target certain national, religious and racial groups, thereby increasing the risk of genocide and mass killings. In the present day, when the global arms race using AI is a reality, many technologists are turning their attention to banning lethal autonomous weapons. In addition, in order to prevent the potential negative consequences of AI development, industry professionals have suggested the need to develop an AI code of ethics. The creation of appropriate legislative mechanisms based on ethics and the protection of human rights has already become an urgent matter for mankind to prevent the possible risks posed by the development of robotics and artificial intelligence technology. Since artificial intelligence is used to detect and prevent various types of crime, it is therefore necessary to use the opportunities provided by it to prevent genocide and mass murder.

scholarly journals Risks and Ethical-Legal Models of Using Artificial Intelligence Systems

2019 ◽  
pp. 1-11
Author(s):  
Dmitrii V. Bakhteev
Keyword(s):  
Artificial Intelligence ◽  
Autonomous Vehicles ◽  
Code Of Ethics ◽  
Personal Data ◽  
Point Of View ◽  
Negative Consequences ◽  
Weapon Systems ◽  
Intelligence Studies ◽  
Artificial Intelligence Technology ◽  
Artificial Intelligence Systems

The matter under research of the legal patterns of interaction between the society and individuals and artificial intelligence technologies. Elements of the matter under research is the technological grounds for functioning of artificial intelligence systems, potential risks and negative consequences of using this technology based on the example of intellectual processing personal data and autonomous vehicles and weapon systems, ethical and legal approaches to its regulation. Bakhteev analyzes approaches to describing positions of artificial intelligence systems and whether these systems have personalities and thus certain rights. The research is based on the method of modelling that is used to describe stages of ethical-legal research of artificial intelligence technology. The author also describes different kinds of responses of the society to the development of the aforesaid technology. The main conclusions of the research is the description of stages of artificial intelligence studies, in particular, analysis of the technology itself, associated risks and responses of the society and creation of ethical and then legal grounds for regulation of this technology. The author gives the results of the analysis of possible ethical-legal models of subjectivity of artificial intelligence systems from the point of view of the need and possibility to grant them certain rights. These models include instrumental, tolerant, xenophobic and empathetic. The author also states the main provisions of the code of ethics for developer and user of artificial intelligence systems. 

scholarly journals 0792 Mandibular Movement Monitoring with Artificial Intelligence Analysis for the Diagnosis of Sleep Bruxism

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A301-A302
Author(s):  
J Martinot ◽  
N Le-Dong ◽  
V Cuthbert ◽  
S Denison ◽  
D Gozal ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Cluster Analysis ◽  
Sleep Bruxism ◽  
Specific Pattern ◽  
Measurement Unit ◽  
Type I ◽  
Negative Consequences ◽  
Mandibular Movement ◽  
Artificial Intelligence Technology ◽  
Mandibular Movements

Abstract Introduction Sleep bruxism (BXM) is the result of rhythmic muscular masticatory activity (RMMA) and can be captured by masseters surface electromyography (sEMG). Despite the multiple adverse negative consequences of BXM, a simple reliable home diagnostic device is currently unavailable, with in laboratory audio-video polysomnography (type I PSG) remaining the gold standard diagnostic tool. Mandibular movements (MM) recordings during sleep can readily identify RMMA, are simple to set up and can be easily repeated from night to night. Here, we aimed to identify stereotypical MM in patients with BXM, and to develop RMMA automatic detection and BXM diagnosis using an artificial intelligence-based approach. Methods MM were recorded by a dedicated sensor (Sunrise, Namur, Belgium) in 12 patients with BXM during type I PSG. The Sunrise system consists of a coin-sized hardware that is comfortably placed on the subject’s chin. Its embedded inertial measurement unit communicates via Bluetooth with a smartphone and automatically transfers MM signals to a cloud-based infrastructure at the end of the night. Data processing and analysis are then performed in Python programming language. A time series cluster analysis was applied to sequences of masseters sEMG and MM signals during BXM episodes (n=300) and during spontaneous micro-arousals (n=300). Then, a convolutional neuronal network (CNN) was developed to identify BXM and distinguish it from spontaneous micro-arousals while exclusively relying on MM signal. Results Based on the cluster analysis, BXM periods were characterized by a specific pattern of MM signals (higher frequency and amplitude), which was closely associated with the sEMG signals but clearly differed from the MM signal patterns during micro-arousals. CNN-based classifier distinguished the BXM events from other RMMAs during micro-arousals and respiratory efforts with an overall accuracy of 91%. Conclusion Sleep bruxism can be automatically identified, quantified, and characterized with mandibular movements analysis supported by artificial intelligence technology. Support This work was supported by the French National Research Agency (ANR-12-TECS-0010), in the framework of the “Investissements d’avenir” program (ANR-15-IDEX-02). https://life.univ-grenoble-alpes.fr.

scholarly journals Theoretical approaches to the definition and legal regulation of artificial intelligence

2021 ◽  
Vol 66 ◽  
pp. 50-55
Author(s):  
S.R. Kornieieva
Keyword(s):  
Artificial Intelligence ◽  
Soviet Union ◽  
Public Relations ◽  
Former Soviet Union ◽  
Rapid Development ◽  
Legal Regulation ◽  
Negative Consequences ◽  
Theoretical Approaches ◽  
Protection Of Human Rights ◽  
Definition Of

This article is devoted to the analysis of approaches to the legal regulation of artificial intelligence. At present time, issues of regulation of artificial intelligence and its impact on the exercise and protection of human rights are being at the stage of active development in the studies of scholars, mainly from European countries, and are less covered in scientific studies of scholars in Ukraine and other countries of the former Soviet Union. Given the trends of rapid development of artificial intelligence technologies, it can be presumed, that in the nearest future this topic will become the focus of many scholars in jurisprudence. In order to determine the place of artificial intelligence technologies in the legal system, it was conducted a general analysis of approaches to the legal regulation of this technology.      The analysis provides the review of the structure of legal regulation on the example of scientific developments and conclusions of the Council of Europe, as well as provides alternative approaches to definition of the subject-object nature of the concept of "artificial intelligence". Some scholars suggest legal regulation of "artificial intelligence" as an object of legal relations which is fully made and controlled by human. Other scholars suggest that "artificial intelligence" should be given subjective legal capacity, considering it as an autonomous and capable of taking responsibility for its own actions. The article provides the analysis the basis and possible consequences of the implementation of these two approaches in legal systems. The article also covers the rights and responsibilities of developers, owners and people who use artificial intelligence. The article partially covers the hybrid model of legal relations, in which part of public relations is exercised without human being.      It also defines the positive and negative consequences of the application of the approaches proposed by scholars.      The author emphasizes the low amount of studies concerning legal approaches and the lack of unified approach that could be applied in practice.

scholarly journals A Study of Automatic Judgment of Food Color and Cooking Conditions with Artificial Intelligence Technology

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1128
Author(s):  
Chern-Sheng Lin ◽  
Yu-Ching Pan ◽  
Yu-Xin Kuo ◽  
Ching-Kun Chen ◽  
Chuen-Lin Tien
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Color Space ◽  
Color Difference ◽  
Color Space Conversion ◽  
Before And After ◽  
Artificial Intelligence Technology ◽  
Artificial Intelligence Algorithm ◽  
Time Image ◽  
Cooking Conditions

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.

Research on the framework of university ideological and political education management system based on artificial intelligence

2021 ◽  
pp. 1-10
Author(s):  
Xuying Sun ◽  
Yu Zhang
Keyword(s):  
Artificial Intelligence ◽  
Political Theory ◽  
Outlier Detection ◽  
Management System ◽  
Detection Algorithm ◽  
Colleges And Universities ◽  
Ideological And Political Education ◽  
Political Education ◽  
Data Simulation ◽  
Artificial Intelligence Technology

The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.

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