INFLUENCE OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES ON DEMOCRATIC PROCEDURES

2021 ◽  
Vol 3 ◽  
pp. 16-21
Author(s):  
S. FURS ◽  
Keyword(s):  
Artificial Intelligence ◽  
Negative Impact ◽  
Social Medium ◽  
Potential Risks ◽  
The Given

The article considers the specifics of the artificial intelligence (AI) technologies implementation and adaptation into social medium; it shows the interaction between the given process and democratic procedures. The author of the article emphasizes the fact that, in addition to the powerful results, AI technologies bear the potential risks to democratic procedures that are not studied enough. These risks result from the openness of AI technology in terms of purposes of use and application areas. To neutralize its negative impact and manifestation in future, an active study of this problem is required within the framework of the regulatory sphere. The article is dedicated to the consideration of this issue.

Dyadic Obligations over Complex Actions as Deontic Constraints in the Situation Calculus

2020 ◽  
Author(s):  
Jens Claßen ◽  
James Delgrande
Keyword(s):  
Artificial Intelligence ◽  
Deontic Logic ◽  
Action Theory ◽  
Prima Facie ◽  
Situation Calculus ◽  
Artificial Agents ◽  
Planning Techniques ◽  
Course Of Action ◽  
Reasoning About Action ◽  
The Given

With the advent of artificial agents in everyday life, it is important that these agents are guided by social norms and moral guidelines. Notions of obligation, permission, and the like have traditionally been studied in the field of Deontic Logic, where deontic assertions generally refer to what an agent should or should not do; that is they refer to actions. In Artificial Intelligence, the Situation Calculus is (arguably) the best known and most studied formalism for reasoning about action and change. In this paper, we integrate these two areas by incorporating deontic notions into Situation Calculus theories. We do this by considering deontic assertions as constraints, expressed as a set of conditionals, which apply to complex actions expressed as GOLOG programs. These constraints induce a ranking of "ideality" over possible future situations. This ranking in turn is used to guide an agent in its planning deliberation, towards a course of action that adheres best to the deontic constraints. We present a formalization that includes a wide class of (dyadic) deontic assertions, lets us distinguish prima facie from all-things-considered obligations, and particularly addresses contrary-to-duty scenarios. We furthermore present results on compiling the deontic constraints directly into the Situation Calculus action theory, so as to obtain an agent that respects the given norms, but works solely based on the standard reasoning and planning techniques.

scholarly journals Technical and Humanities Students’ Perspectives on the Development and Sustainability of Artificial Intelligence (AI)

2018 ◽  
Vol 10 (9) ◽  
pp. 3066 ◽  
Author(s):  
Vasile Gherheș ◽  
Ciprian Obrad
Keyword(s):  
Artificial Intelligence ◽  
Social Life ◽  
Research Method ◽  
Quantitative Research ◽  
Positive Attitude ◽  
Negative Impact ◽  
Representation Error ◽  
The Social ◽  
The Future ◽  
Humanities Students

This study investigates how the development of artificial intelligence (AI) is perceived by the students enrolled in technical and humanistic specializations at two universities in Timisoara. It has an emphasis on identifying their attitudes towards the phenomenon, on the connotations associated with it, and on the possible impact of artificial intelligence on certain areas of the social life. Moreover, the present study reveals the students’ perceptions on the sustainability of these changes and developments, and therefore aims to reduce the possible negative impact on consumers, and at anticipate the changes that AI will produce in the future. In order to collect the data, the authors have used a quantitative research method. A questionnaire-based sociological survey was completed by 928 students, with a representation error of only ±3%. The analysis has shown that a great number of respondents have a positive attitude towards the emergence of AI, who believe it will influence society for the better. The results have also underscored underlying differences based on the respondents’ type of specialization (humanistic or technical), and their gender.

scholarly journals New risks related to emerging technologies and reputation for corporate governance

2020 ◽  
Vol 9 (2) ◽  
pp. 64-74
Author(s):  
Hugh Grove ◽  
Mac Clouse ◽  
Tracy Xu
Keyword(s):  
Artificial Intelligence ◽  
Corporate Governance ◽  
Boards Of Directors ◽  
Emerging Technologies ◽  
Research Question ◽  
World Intellectual Property Organization ◽  
Global Marketplace ◽  
Challenges And Opportunities ◽  
Potential Risks ◽  
Management Issues

Artificial intelligence (AI) has moved from theory into the global marketplace. The United Nations World Intellectual Property Organization released the first report of its Technology Trends series on January 31, 2019. It considered more than 340,000 AI-related patent applications over the last 70 years. 50 percent of all AI patents have been published in just the last five years. The challenges, potential risks, and opportunities for business and corporate governance from emerging technologies, especially artificial intelligence, have been summarized as whereby machines and software can analyze, optimize, prophesize, customize, digitize and automate just about any job in every industry. Boards of directors and executives need to recognize and understand the new risks associated with these emerging technologies and related reputational risks. The major research question of this paper is how boards of directors and executives can deal with both risk challenges and opportunities to strengthen corporate governance. Accordingly, the following sections of this paper discuss key risk management issues: deep shift risks, global risks, digital risks and opportunities, AI initiatives risks, business risks from millennials, business reputational risks, and conclusions.

scholarly journals Linear Regression Algorithm in Machine Learning through MATLAB

2021 ◽  
Vol 9 (12) ◽  
pp. 989-995
Author(s):  
Kalva Sindhu Priya
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Linear Regression ◽  
Mean Squared Error ◽  
Critical Part ◽  
Squared Error ◽  
Master Level ◽  
Predicted Model ◽  
The Given

Abstract: In the present scenario, it is quite aware that almost every field is moving into machine based automation right from fundamentals to master level systems. Among them, Machine Learning (ML) is one of the important tool which is most similar to Artificial Intelligence (AI) by allowing some well known data or past experience in order to improve automatically or estimate the behavior or status of the given data through various algorithms. Modeling a system or data through Machine Learning is important and advantageous as it helps in the development of later and newer versions. Today most of the information technology giants such as Facebook, Uber, Google maps made Machine learning as a critical part of their ongoing operations for the better view of users. In this paper, various available algorithms in ML is given briefly and out of all the existing different algorithms, Linear Regression algorithm is used to predict a new set of values by taking older data as reference. However, a detailed predicted model is discussed clearly by building a code with the help of Machine Learning and Deep Learning tool in MATLAB/ SIMULINK. Keywords: Machine Learning (ML), Linear Regression algorithm, Curve fitting, Root Mean Squared Error

scholarly journals Artificial intelligence in the service of man: medical, social and economic aspects

2021 ◽  
Vol 7 (3C) ◽  
pp. 619-626
Author(s):  
Svetlana Gennadevna Karamysheva ◽  
Alexander Vladimirovich Grigoriev ◽  
Elena Mikhailovna Kiseleva ◽  
Alexandra G. Polyakova ◽  
Sergey Barinov
Keyword(s):  
Artificial Intelligence ◽  
Human Activity ◽  
Negative Impact ◽  
Social Aspect ◽  
Economic Aspects ◽  
Human Capabilities ◽  
The Social ◽  
Labor Resources ◽  
A Company ◽  
Robotic Technologies

Artificial intelligence (AI) and robotic technologies have recently been increasingly used in various areas of human activity. Thus, the purpose of this paper is to consider the medical, social and economic aspects of the use of artificial intelligence in various spheres of human activity. The reason for people turning to the above-mentioned innovations is to expand a number of human capabilities, increase labor productivity, reduce the negative impact of the human factor, etc. The social aspect of the use of robotic technologies should also not be underestimated. The economic aspects of the use of artificial intelligence and robotic technologies are the possibility of optimizing the number of labor resources, replacing a whole staff of auxiliary workers, which can significantly reduce the salary fund in general and the costs of a company using such technologies, in particular.

scholarly journals Complex approach to organizations’ capital assets reproduction

2020 ◽  
Vol 157 ◽  
pp. 04026 ◽  
Author(s):  
Aleksandr Birjukov ◽  
Evgeniy Dobryshkin ◽  
Yurii Birjukov ◽  
Vladimir Tishchenko
Keyword(s):  
Working Conditions ◽  
Negative Impact ◽  
Technical Condition ◽  
Joint Estimation ◽  
Mathematical Apparatus ◽  
Production Processes ◽  
Capital Assets ◽  
Industrial Buildings ◽  
Complex Approach ◽  
The Given

Effective production activities of organizations is impossible without the concept implementation of the constant reproduction of capital assets, a significant part of which is represented by buildings and structures for various functional purposes. Increased deterioration of industrial buildings does not allow to solve such important tasks as improvement and automation of production processes in their entirety, and has a negative impact on the working conditions and safety of personnel. The analysis of scientific and normative literature is showed that the issue under consideration requires further research. Author’s approach to the reproduction of capital assets, the use of which allows to increase the management decisions efficiency on the basis of a complex of tasks for the joint estimation of damage and deterioration, planning of works under the given constraints with the use of mathematical apparatus and technological solutions for monitoring the technical condition of buildings is presented in the article.

Impact of the Slurry Pond of the Tyrnyauz Tungsten-Molybdenum Complex on the Mountain Territories Environment

2018 ◽  
Vol 931 ◽  
pp. 1070-1075 ◽  
Author(s):  
Buzgigit M. Huchunayev ◽  
Oksana O. Dakhova ◽  
Svetlana A. Bekkiyeva ◽  
Svetlana B. Hatefova
Keyword(s):  
Negative Impact ◽  
Scientific Work ◽  
Land Resources ◽  
Molybdenum Complex ◽  
Atmospheric Air ◽  
Impact Reduction ◽  
The Given ◽  
Made In

The results of the Tyrnyauz tungsten-molybdenum Plant (TTMP) slurry pond settler environment impacts assessment are given in this scientific work, and the recommendations about the negative impact reduction on the environment are made. In the given work the characteristics of the environment state are investigated: atmospheric air, water objects and land resources.

scholarly journals The Graph Reasoning Approach Based on the Dynamic Knowledge Auxiliary for Complex Fact Verification

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1472
Author(s):  
Yongyue Wang ◽  
Chunhe Xia ◽  
Chengxiang Si ◽  
Chongyu Zhang ◽  
Tianbo Wang
Keyword(s):  
Common Sense ◽  
Negative Impact ◽  
Background Knowledge ◽  
Small Sample ◽  
Training Data ◽  
Reasoning Ability ◽  
Auxiliary Graph ◽  
Graph Neural Networks ◽  
The Given ◽  
Conceptual Relationship

Complex fact verification (FV) requires fusing scattered sequences and performing multi-hop reasoning over these composed sequences. Recently, by employing some FV models, knowledge is obtained from context to support the reasoning process based on pretrained models (e.g., BERT, XLNET), and this model outperforms previous out-of-the-art FV models. In practice, however, the limited training data cannot provide enough background knowledge for FV tasks. Once the background knowledge changed, the pretrained models’ parameters cannot be updated. Additionally, noise against common sense cannot be accurately filtered out due to the lack of necessary knowledge, which may have a negative impact on the reasoning progress. Furthermore, existing models often wrongly label the given claims as ‘not enough information’ due to the lack of necessary conceptual relationship between pieces of evidence. In the present study, a Dynamic Knowledge Auxiliary Graph Reasoning (DKAR) approach is proposed for incorporating external background knowledge in the current FV model, which explicitly identifies and fills the knowledge gaps between provided sources and the given claims, to enhance the reasoning ability of graph neural networks. Experiments show that DKAR put forward in this study can be combined with specific and discriminative knowledge to guide the FV system to successfully overcome the knowledge-gap challenges and achieve improvement in FV tasks. Furthermore, DKAR is adopted to complete the FV task on the Fake NewsNet dataset, showing outstanding advantages in a small sample and heterogeneous web text source.

Australian female athlete perceptions of the challenges associated with training and competing when menstrual symptoms are present

2020 ◽  
Vol 15 (3) ◽  
pp. 316-323
Author(s):  
Mike Armour ◽  
Kelly A Parry ◽  
Kylie Steel ◽  
Caroline A Smith
Keyword(s):  
Menstrual Cycle ◽  
Contraceptive Use ◽  
Negative Impact ◽  
Management Strategies ◽  
Chi Square ◽  
Contraceptive Usage ◽  
Menstrual Symptoms ◽  
Potential Risks ◽  
Potential Impact ◽  
The Impact

Coaches consider various competencies (e.g. conditioning, nutrition, skills and tactics), when planning sessions, though rarely the impact of menstruation on the efficacy of training and competition performance for athletes. Given the impact menstrual symptoms can have on athletes, the management strategies that athletes may use to minimise any potential impact, and the mechanisms that provide barriers to greater coach athlete interaction require investigation and consideration. Therefore, this study aimed to investigate the strategies used by athletes to manage menstrual symptoms and the role coaches played in this process. An anonymous, 36-item questionnaire was developed and hosted on Qualtrics. Descriptive statistics and Chi-square statistics were used to analyse the data. One hundred and twenty-four valid responses from Australian athletes 16–45, with a mean age of 29 years, were received. Period pain (82%) and pre-menstrual symptoms (83%) were commonly reported and contributed to fatigue and to perceived reductions in performance during or just prior to the period (50.0% in training, 58.7% on ‘game day’). Contraceptive use was reported by 42% of athletes. Those reporting heavy menstrual bleeding (29.7%) were more likely to report increased fatigue (relative risk 1.6, 95% CI 1.07 to 2.32). Over three-quarters of athletes reported neither they nor their coaches altered training due to the menstrual cycle. Most athletes (76%) did not discuss menstruation with their coaches. Given the perceived negative impact on performance and potential risks with contraceptive usage during adolescence, coaches, trainers and athletes need to have a more open dialogue around the menstrual cycle.

scholarly journals Tingkat Kesulitan Dinamis Menggunakan Logika Fuzzy pada Game Musik Tradisional Jawa Tengah

2021 ◽  
Vol 5 (2) ◽  
pp. 56-64
Author(s):  
Kadhana Reya Wisinggya ◽  
Hanny Haryanto ◽  
T. Sutojo ◽  
Edy Mulyanto ◽  
Erlin Dolphina
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Digital Games ◽  
Way Of Thinking ◽  
Traditional Songs ◽  
The Given

The culture in Indonesia is very diverse, one of which is traditional songs. However, knowledge of traditional songs is still small. Digital Games can spread knowledge about traditional songs, one of which is Central Javanese traditional songs. However, the Game that is made still has static difficulties, so the Game cannot follow the player's ability, resulting in the player feeling bored and not wanting to continue the Game. To generate dynamic difficulties, methods in artificial intelligence can be applied to Games, one of which is Fuzzy. So in this study proposed the application of dynamic difficulties using Fuzzy Logic in music Games / Rhythm Games. Fuzzy Logic is built based on mathematical values and represents uncertainty, where this logic imitates the human way of thinking. Fuzzy Logic can convert crisp input values into fuzzy sets by performing fuzzification. After the input value is converted, the input will be entered into the set of rules provided. Each rule produces a different output. After the process is complete, the output value will be converted back to the crisp output value. Based on the research conducted, it is found that Fuzzy Logic can be applied to music Games where the Game can follow the player's ability based on the given rules.

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