scholarly journals Involvement of Artificial Intelligence in Modern Society

2021 ◽  
Vol 10 ◽  
pp. 267-273
Author(s):  
Gregor Jagodič ◽  
Miloš Šinkovec
Keyword(s):  
Artificial Intelligence ◽  
Modern Society

scholarly journals Ordering Artificial Intelligence Based Recommendations to Tackle the SDGs with a Decision-Making Model Based on Surveys

2021 ◽  
Vol 13 (11) ◽  
pp. 6038
Author(s):  
Sergio Alonso ◽  
Rosana Montes ◽  
Daniel Molina ◽  
Iván Palomares ◽  
Eugenio Martínez-Cámara ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Sustainable Development Goals ◽  
Modern Society ◽  
Agenda 2030 ◽  
Model Based ◽  
Development Goals ◽  
Sustainability Challenges ◽  
New Research ◽  
Decision Making Model

The United Nations Agenda 2030 established 17 Sustainable Development Goals (SDGs) as a guideline to guarantee a sustainable worldwide development. Recent advances in artificial intelligence and other digital technologies have already changed several areas of modern society, and they could be very useful to reach these sustainable goals. In this paper we propose a novel decision making model based on surveys that ranks recommendations on the use of different artificial intelligence and related technologies to achieve the SDGs. According to the surveys, our decision making method is able to determine which of these technologies are worth investing in to lead new research to successfully tackle with sustainability challenges.

scholarly journals ARTIFICIAL INTELLIGENCE: NEW CHALLENGES AND PROSPECTS

2020 ◽  
Vol 8 (5) ◽  
pp. 42-48
Author(s):  
Yulia Matyuk
Keyword(s):  
Artificial Intelligence ◽  
Industrial Revolution ◽  
New Technologies ◽  
Rapid Development ◽  
Modern Society ◽  
Fourth Industrial Revolution ◽  
New Challenges ◽  
And Robotics

The article analyzes the risks and new opportunities that arise before man and modern society in the light of the development of artificial intelligence and robotics in the conditions of the fourth industrial revolution. The rapid development of AI indicates the absence of uniform approaches to assessing the risks and prospects associated with the use of AI. Using PESTEL analysis, the article examines the key areas of interaction between AI and humans, new challenges and prospects that open to humanity in the era of new technologies.

scholarly journals Design and Implementation of Cloud Analytics-Assisted Smart Power Meters Considering Advanced Artificial Intelligence as Edge Analytics in Demand-Side Management for Smart Homes

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2047 ◽  
Author(s):  
Yung-Yao Chen ◽  
Yu-Hsiu Lin ◽  
Chia-Ching Kung ◽  
Ming-Han Chung ◽  
I-Hsuan Yen
Keyword(s):  
Artificial Intelligence ◽  
Data Science ◽  
Modern Society ◽  
Smart Homes ◽  
Demand Side Management ◽  
Demand Side ◽  
Smart Meters ◽  
Smart Power ◽  
Iot Applications ◽  
User Centric

In a smart home linked to a smart grid (SG), demand-side management (DSM) has the potential to reduce electricity costs and carbon/chlorofluorocarbon emissions, which are associated with electricity used in today’s modern society. To meet continuously increasing electrical energy demands requested from downstream sectors in an SG, energy management systems (EMS), developed with paradigms of artificial intelligence (AI) across Internet of things (IoT) and conducted in fields of interest, monitor, manage, and analyze industrial, commercial, and residential electrical appliances efficiently in response to demand response (DR) signals as DSM. Usually, a DSM service provided by utilities for consumers in an SG is based on cloud-centered data science analytics. However, such cloud-centered data science analytics service involved for DSM is mostly far away from on-site IoT end devices, such as DR switches/power meters/smart meters, which is usually unacceptable for latency-sensitive user-centric IoT applications in DSM. This implies that, for instance, IoT end devices deployed on-site for latency-sensitive user-centric IoT applications in DSM should be aware of immediately analytical, interpretable, and real-time actionable data insights processed on and identified by IoT end devices at IoT sources. Therefore, this work designs and implements a smart edge analytics-empowered power meter prototype considering advanced AI in DSM for smart homes. The prototype in this work works in a cloud analytics-assisted electrical EMS architecture, which is designed and implemented as edge analytics in the architecture described and developed toward a next-generation smart sensing infrastructure for smart homes. Two different types of AI deployed on-site on the prototype are conducted for DSM and compared in this work. The experimentation reported in this work shows the architecture described with the prototype in this work is feasible and workable.

scholarly journals Application and Development of Computer Artificial Intelligence Technology

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Yu Zhang
Keyword(s):  
Artificial Intelligence ◽  
Science Fiction ◽  
Daily Life ◽  
Science And Technology ◽  
Modern Society ◽  
Internet Technology ◽  
Tertiary Industry ◽  
The People ◽  
Artificial Intelligence Technology ◽  
Applied Artificial Intelligence

In the development of modern society, Internet technology has been popularized and applied. Artificial intelligence technology is not only found in science fiction movies, but has been widely used in industry, tertiary industry and people’s livelihood. Under the background of rapid advancement of science and technology, computer artificial intelligence technology will play an important role in the future. Due to a series of problems in the development of computer artificial intelligence technology, it is necessary for relevant personnel to strengthen research on the application and development of computer artificial intelligence technology. The paper mainly studies the application and development of computer artificial intelligence technology, and hopes to bring more convenience to the daily life of the people.

scholarly journals Theoretical aspects of digitalization in social management

Communicology ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 53-64
Author(s):  
S. A. Ryumshin
Keyword(s):  
Artificial Intelligence ◽  
Goal Setting ◽  
System Analysis ◽  
Digital Technologies ◽  
Modern Society ◽  
Historical Background ◽  
Management Tools ◽  
Social Communications ◽  
The Subject ◽  
Social Management

The paper discusses the issues of digitalization of modern society. Within the framework of the system analysis of the subject of research, the author highlights the theoretical aspects of digitalization in social management, examines the historical background for digitalization; social management is represented through the categories of selfgovernment, organizational order, goal-setting, subject-subject interactions, management tools. In the system of social communications, digital technologies and artificial intelligence are presented by the author as a new socio-digital reality that transforms the environment of interaction. The author’s review of the main stages and markers of the development of digitalization made it possible to update the list of positive aspects in social management, as well as problems caused by the digitalization process.

scholarly journals ІДЕНТИФІКАЦІЙНІ ДАНІ: ПРАВОВІ МЕХАНІЗМИ РОЗРОБКИ КЛАСИФІКАТОРІВ

2021 ◽  
Author(s):  
О. В. Костенко ◽  
Keyword(s):  
Artificial Intelligence ◽  
Information And Communication Technologies ◽  
Driving Forces ◽  
Modern Society ◽  
Communication Technologies ◽  
Legal Rights ◽  
Technological Revolution ◽  
Modern Development ◽  
Information And Communication ◽  
Iot Devices

Modern society has entered into a full-scale implementation of the scientific and technological revolution 4.0 and economic globalization. One of the driving forces of the new scientific and technological revolution is the development of information and communication technologies and the introduction of technologies for the transmission and use of information. Today, the problem of legal support for the management of the confidentiality of data used to identify subjects and objects by their unique attributes is relevant. The degree of solving the problem of managing the processes of digital identification data is one of the main factors in the modern development of crossborder e-economy and trade. There is a situation when in Ukraine in all spheres of public life modern information and communication technologies are rapidly introduced in the actual absence of legal institutions for the management of identification and personal data, biometrics, IoT devices and artificial intelligence. A significant complication for the development and operation of identification data management systems is the lack of a single strategy in this area, socio-legal model of public relations, a single classifier of identification data and a single scheme of identification of subjects by identification data, mechanisms for legal rights and responsibilities. projects, legal procedures for biometric identification, methods of identification of IoT devices and artificial intelligence.

scholarly journals Artificial intelligence: legal and ethical aspects

2021 ◽  
pp. 63-71
Author(s):  
Al'bina Slavovna Lolaeva ◽  
Kristina Ushangievna Sakaeva
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Autonomous Systems ◽  
Modern Society ◽  
Ethical Aspects ◽  
Legal Decisions ◽  
Human Ability ◽  
Ethical Norms ◽  
Legal Difficulties ◽  
And Control

Ethical norms and the law are indispensably linked in the modern society. The adoption of major legal decisions is affected by various ethical rules. Artificial intelligence transforms the indicated problems into a new dimension. The systems that use artificial intelligence are becoming more autonomous by complexity of the tasks they accomplish, and their potential implications on the external environment. This diminishes the human ability to comprehend, predict, and control their activity. People usually underestimate the actual level of the autonomy of such systems. It is underlined that the machines based on artificial intelligence can learn from the own experience, and perform actions that are not meant by the developers. This leads to certain ethical and legal difficulties that are discussed in this article. In view of the specificity of artificial intelligence, the author makes suggestions on the direct responsibility of particular systems. Based on this logic, there are no fundamental reasons that prevent the autonomous should be held legally accountable for their actions. However, the question on the need or advisability to impose such type of responsibility (at the present stage specifically) remains open. This is partially due to the ethical issues listed above. It might be more effective to hold programmers or users of the autonomous systems accountable for the actions of these systems. However, it may decelerate innovations. This is namely why there is a need to find a perfect balance.

scholarly journals Monitoring of Coral Reefs Using Artificial Intelligence: A Feasible and Cost-Effective Approach

2020 ◽  
Vol 12 (3) ◽  
pp. 489 ◽  
Author(s):  
Manuel González-Rivero ◽  
Oscar Beijbom ◽  
Alberto Rodriguez-Ramirez ◽  
Dominic E. P. Bryant ◽  
Anjani Ganase ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Image Analysis ◽  
Coral Reef ◽  
Coral Reefs ◽  
Image Annotation ◽  
Rapid Evolution ◽  
Modern Society ◽  
Automated Image Analysis ◽  
Ecosystem Monitoring ◽  
Reef Monitoring

Ecosystem monitoring is central to effective management, where rapid reporting is essential to provide timely advice. While digital imagery has greatly improved the speed of underwater data collection for monitoring benthic communities, image analysis remains a bottleneck in reporting observations. In recent years, a rapid evolution of artificial intelligence in image recognition has been evident in its broad applications in modern society, offering new opportunities for increasing the capabilities of coral reef monitoring. Here, we evaluated the performance of Deep Learning Convolutional Neural Networks for automated image analysis, using a global coral reef monitoring dataset. The study demonstrates the advantages of automated image analysis for coral reef monitoring in terms of error and repeatability of benthic abundance estimations, as well as cost and benefit. We found unbiased and high agreement between expert and automated observations (97%). Repeated surveys and comparisons against existing monitoring programs also show that automated estimation of benthic composition is equally robust in detecting change and ensuring the continuity of existing monitoring data. Using this automated approach, data analysis and reporting can be accelerated by at least 200x and at a fraction of the cost (1%). Combining commonly used underwater imagery in monitoring with automated image annotation can dramatically improve how we measure and monitor coral reefs worldwide, particularly in terms of allocating limited resources, rapid reporting and data integration within and across management areas.

scholarly journals Use of artificial intelligence in computed tomography dose optimisation

2020 ◽  
Vol 49 (1_suppl) ◽  
pp. 113-125
Author(s):  
C.H. McCollough ◽  
S. Leng
Keyword(s):  
Artificial Intelligence ◽  
Computed Tomography ◽  
Radiation Dose ◽  
Data Acquisition ◽  
Patient Positioning ◽  
Modern Society ◽  
Reconstruction Algorithms ◽  
Technical Advances ◽  
Increased Sensitivity ◽  
Acquisition Processes

The field of artificial intelligence (AI) is transforming almost every aspect of modern society, including medical imaging. In computed tomography (CT), AI holds the promise of enabling further reductions in patient radiation dose through automation and optimisation of data acquisition processes, including patient positioning and acquisition parameter settings. Subsequent to data collection, optimisation of image reconstruction parameters, advanced reconstruction algorithms, and image denoising methods improve several aspects of image quality, especially in reducing image noise and enabling the use of lower radiation doses for data acquisition. Finally, AI-based methods to automatically segment organs or detect and characterise pathology have been translated out of the research environment and into clinical practice to bring automation, increased sensitivity, and new clinical applications to patient care, ultimately increasing the benefit to the patient from medically justified CT examinations. In summary, since the introduction of CT, a large number of technical advances have enabled increased clinical benefit and decreased patient risk, not only by reducing radiation dose, but also by reducing the likelihood of errors in the performance and interpretation of medically justified CT examinations.

A Multi-Disciplinary Perspective for Conducting Artificial Intelligence-enabled Privacy Analytics

2021 ◽  
Vol 12 (1) ◽  
pp. 1-18
Author(s):  
Sagar Samtani ◽  
Murat Kantarcioglu ◽  
Hsinchun Chen
Keyword(s):  
Artificial Intelligence ◽  
Web Sites ◽  
Data Aggregation ◽  
National Science Foundation ◽  
Modern Society ◽  
Data Sources ◽  
Risk Modeling ◽  
Legal Documents ◽  
Funding Sources ◽  
Assistance Systems

Events such as Facebook-Cambridge Analytica scandal and data aggregation efforts by technology providers have illustrated how fragile modern society is to privacy violations. Internationally recognized entities such as the National Science Foundation (NSF) have indicated that Artificial Intelligence (AI)-enabled models, artifacts, and systems can efficiently and effectively sift through large quantities of data from legal documents, social media, Dark Web sites, and other sources to curb privacy violations. Yet considerable efforts are still required for understanding prevailing data sources, systematically developing AI-enabled privacy analytics to tackle emerging challenges, and deploying systems to address critical privacy needs. To this end, we provide an overview of prevailing data sources that can support AI-enabled privacy analytics; a multi-disciplinary research framework that connects data, algorithms, and systems to tackle emerging AI-enabled privacy analytics challenges such as entity resolution, privacy assistance systems, privacy risk modeling, and more; a summary of selected funding sources to support high-impact privacy analytics research; and an overview of prevailing conference and journal venues that can be leveraged to share and archive privacy analytics research. We conclude this paper with an introduction of the papers included in this special issue.

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