scholarly journals The Analysis of Opportunities of the Application of Big Data and Artificial Intelligence Technologies in Public Governance and Social Policy

2021 ◽  
Vol 22 ◽  
pp. 88-100
Author(s):  
Adomas Vincas Rakšnys ◽  
Dangis Gudelis ◽  
Arvydas Guogis
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Social Policy ◽  
Ethical Issues ◽  
Policy Formation ◽  
Modern World ◽  
Business Systems ◽  
Public Governance ◽  
Advantages And Disadvantages ◽  
Data Fragmentation

This interdisciplinary article presents a concept of the 21st century and phenomena that are products of the 4th industrial revolution – big data and Artificial Intelligence technologies – as well as the opportunities of their application in public governance and social policy. This paper examines the advantages and disadvantages of big data, problems of data collection, its reliability and use. Big data can be used for the analysis and modeling of phenomena relevant to public governance and social policy. Big data consist of three main types: a) historical data, b) present data with little delay, c) prognostic data for future forecasting. The following categories of big data can be defined as: a) data from social networks, b) traditional data from business systems, c) machine-generated data, such as water extraction, pollution, satellite information. The article analyzes the advantages and disadvantages of big data. There are big data challenges such as data security, lack of cooperation in civil service and social work, in rare situations – data fragmentation, incompleteness and erroneous issues, as well as ethical issues regarding the analysis of data and its use in social policy and social administration. Big data, covered by Artificial Intelligence, can be used in public governance and social policy by identifying “the hot spots” of various phenomena, by prognosing the meanings of variables in the future on the basis of past time rows, and by calculating the optimal motion of actions in the situations where there are possible various alternatives. The technologies of Artificial Intelligence are used more profoundly in many spheres of public policy, and in the governance of COVID-19 pandemics too. The substantial advantages of the provided big data and Artificial Intelligence are a holistic improvement of public services, possibilities of personalization, the enhancement of citizen satisfaction, the diminishing of the costs of processing expenditure, the targeting of adopted and implemented decisions, more active involvement of citizens, the feedback of the preferences of policy formation and implementation, the observation of social phenomenas in real time, and possibilities for more detailed prognosing. Challenges to security of data, necessary resources and competences, the lack of cooperation in public service, especially rare instances of data fragmentation, roughness, falseness, and ethical questions regarding data analysis and application can be evaluated as the most significant problems of using big data and Artificial Intelligence technologies. Big data and their analytics conducted using Artificial Intelligence technologies can contribute to the adequacy and objectivity of decisions in public governance and social policy, effectively curbing corruption and nepotism by raising the authority and confidence of public sector organizations in governance, which is so lacking in the modern world.

scholarly journals Modern technologies of marketing research and market analysis

2021 ◽  
Vol 2021 (2) ◽  
pp. 29-39
Author(s):  
Oleh Duma ◽  
◽  
M. Melnyk ◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Human Life ◽  
Marketing Research ◽  
Research Process ◽  
Target Market ◽  
Advantages And Disadvantages ◽  
Marketing Activities ◽  
Modern Technologies

Nowadays, marketing research is increasingly important for the success of enterprises. Conducting marketing research reduces the risk of making wrong decisions in the analysis and development of marketing strategies, planning and control of marketing activities. The article provides an overview of the emergence of marketing research, explores the latest methods of marketing research, their advantages and disadvantages, the possibility of its application at different stages of marketing activities. Scientific approaches to the interpretation of the concepts "marketing research", "methods of marketing research" are systematized. The latest methods of marketing research that widely use AI, Big Data, ML, TRI * M, have been studied. The technologies of mobile advertising, areas of use of artificial intelligence, the essence and features of the formation of Big Data and machine learning were researched in the article. The benefits of using artificial intelligence, big data and machine learning to conduct marketing research were researched in the article. Analytical materials are confirmed by cases from the practice of marketing research. All research outcomes were proved by cases of Independent Media, TNS Ukraine, British Council, Chat fuel and Coca - Cola. The scheme of the marketing research process is supplemented by the possibilities of applying the latest technologies, which are grouped by stages. Any marketing research is a sequence of steps. Each of them uses a set of tools that provide collection, processing and analysis of data about the target market, customers, or economic processes. Each of these stages can be implemented using the modern technologies that are widely used in various spheres of human life. The directions of application the artificial intelligence, Big data, machine learning for carrying out office researches, field researches, pilot researches and a method of focus groups are offered. The analysis of realization of methods of marketing researches on the basis of Big Data, AI, ML is carried out.

scholarly journals Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review

10.2196/20921 ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. e20921
Author(s):  
Qiang Pan ◽  
Damien Brulin ◽  
Eric Campo
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Mining ◽  
Big Data ◽  
Monitoring System ◽  
The Body ◽  
Monitoring Systems ◽  
Sleep Monitoring ◽  
Advantages And Disadvantages ◽  
System Solution

Background Sleep is essential for human health. Considerable effort has been put into academic and industrial research and in the development of wireless body area networks for sleep monitoring in terms of nonintrusiveness, portability, and autonomy. With the help of rapid advances in smart sensing and communication technologies, various sleep monitoring systems (hereafter, sleep monitoring systems) have been developed with advantages such as being low cost, accessible, discreet, contactless, unmanned, and suitable for long-term monitoring. Objective This paper aims to review current research in sleep monitoring to serve as a reference for researchers and to provide insights for future work. Specific selection criteria were chosen to include articles in which sleep monitoring systems or devices are covered. Methods This review investigates the use of various common sensors in the hardware implementation of current sleep monitoring systems as well as the types of parameters collected, their position in the body, the possible description of sleep phases, and the advantages and drawbacks. In addition, the data processing algorithms and software used in different studies on sleep monitoring systems and their results are presented. This review was not only limited to the study of laboratory research but also investigated the various popular commercial products available for sleep monitoring, presenting their characteristics, advantages, and disadvantages. In particular, we categorized existing research on sleep monitoring systems based on how the sensor is used, including the number and type of sensors, and the preferred position in the body. In addition to focusing on a specific system, issues concerning sleep monitoring systems such as privacy, economic, and social impact are also included. Finally, we presented an original sleep monitoring system solution developed in our laboratory. Results By retrieving a large number of articles and abstracts, we found that hotspot techniques such as big data, machine learning, artificial intelligence, and data mining have not been widely applied to the sleep monitoring research area. Accelerometers are the most commonly used sensor in sleep monitoring systems. Most commercial sleep monitoring products cannot provide performance evaluation based on gold standard polysomnography. Conclusions Combining hotspot techniques such as big data, machine learning, artificial intelligence, and data mining with sleep monitoring may be a promising research approach and will attract more researchers in the future. Balancing user acceptance and monitoring performance is the biggest challenge in sleep monitoring system research.

scholarly journals Organizational knowledge management with Big Data. The foundation of using artificial intelligence

2017 ◽  
Vol 2 (1) ◽  
pp. 301-308 ◽  
Author(s):  
Daniel Paschek ◽  
Anca Mocan ◽  
Corina-Monica Dufour ◽  
Anca Draghici
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Knowledge Management ◽  
Organizational Knowledge ◽  
Knowledge Model ◽  
Core Component ◽  
Advantages And Disadvantages ◽  
The Core ◽  
Core Components ◽  
Framework Conditions

Abstract In the following paper the relevance of Knowledge Management (KM) as a foundation of Artificial Intelligence (AI) systems will be analyzed. The purpose of the work is the presentation of mandatory framework conditions for using AI with a special view on knowledge management for Big Data. Therefore the mandatory definitions of the core components will be described theoretically supported by practical examples. Based on literature, there will be done research and presentation of existing applications the relation between the knowledge management in the organization and big data as core component. To identify the relevant topics of using Big Data for knowledge management an analysis will be held up with digital companies. In addition, the main advantages and disadvantages will be depicted. The finding of the paper will be a recommendation of the developed Artificial Intelligence Knowledge Model for using Knowledge Management and Big Data for Artificial Intelligence decisions within the company.

Philosophy of Information Technology

2015 ◽  
Vol 6 (4) ◽  
pp. 67-76 ◽  
Author(s):  
Budi Yulianto ◽  
Shidarta
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Sexual Partner ◽  
Ethical Issues ◽  
Future Trend ◽  
Philosophy Of Information ◽  
Advantages And Disadvantages ◽  
The Future

Technology moves from the sex toy to the sex robot, a sex doll with artificial intelligence (AI) implemented. It is not a surprise idea to move robot as a servant to a sexual partner. As AI becomes more advanced and interaction between human and robot becomes more personal, sex and marriage with robot could result in the future. The authors conducted survey to discuss current and future trend of sex robot, its advantages and disadvantages. This paper also presents falsification theorems and implications to business, human social, moral, and psychological life caused by sex robot. This paper closes the discussion with further works of important ethical issues to be considered with deontology or consequentialism, and suggests to concern of sex robot regulations rather than banning it.

Philosophy of Information Technology

2019 ◽  
pp. 1458-1467
Author(s):  
Budi Yulianto ◽  
Shidarta
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Sexual Partner ◽  
Ethical Issues ◽  
Future Trend ◽  
Philosophy Of Information ◽  
Advantages And Disadvantages ◽  
The Future

Technology moves from the sex toy to the sex robot, a sex doll with artificial intelligence (AI) implemented. It is not a surprise idea to move robot as a servant to a sexual partner. As AI becomes more advanced and interaction between human and robot becomes more personal, sex and marriage with robot could result in the future. The authors conducted survey to discuss current and future trend of sex robot, its advantages and disadvantages. This paper also presents falsification theorems and implications to business, human social, moral, and psychological life caused by sex robot. This paper closes the discussion with further works of important ethical issues to be considered with deontology or consequentialism, and suggests to concern of sex robot regulations rather than banning it.

Digital Ethics

2022 ◽  
pp. 526-551
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Ethical Issues ◽  
Personal Data ◽  
Digital Technologies ◽  
Codes Of Ethics ◽  
Digital Ethics ◽  
Management Association ◽  
Legal Challenges ◽  
Right Of Access

The purpose of this chapter is to discuss strategies that can be applied in the domain of cyberlaw. The chapter begins by distinguishing between ethics, morality, and law. It then focuses on the relation between ethics and digital technologies. The chapter then examines proposals for what should be included in codes of ethics as well as examples of codes of ethics for IT companies. The examples include the British Computer Society, the Association for Computer Machinery, and the Data Processing Management Association. Next, ethical codes for regulating automation, computerization, and artificial intelligence are summarized. The chapter then discusses ethical issues surrounding privacy, anonymity, and personal data, including the EU's right of access by data subjects as well as issues connected with big data. The chapter then focuses on crimes caused by digitization and the protection of intellectual property. The chapter concludes by considering recent laws of ecommerce as well as social and international legal challenges of regulating cyberspace.

Large Technical Systems

2021 ◽  
pp. 91-106
Author(s):  
Muhammed Can ◽  
Halid Kaplan
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Smart Cities ◽  
Technical System ◽  
Modern World ◽  
Power Networks ◽  
Technical Aspects ◽  
Theoretical Approaches ◽  
Big Data Applications ◽  
Technical Systems

In recent years, artificial intelligence has become a new normal in the modern world. Even though there are still limitations and it remains to be premature both in terms of applications and theoretical approaches, AI has a huge potential to shift various systems from healthcare to transportation. Needless to say, smart cities are also significant for AI's development. IoT, big data applications, and power networks bring a new understanding of how we live and what the future will be like when AI is adapted to smart cities. However, it is highly misleading to focus on AI itself in this manner. Rather, it should be considered as a part of the ‘Large Technical System'. In this vein, the chapter will ask the following questions: To what extent might AI contribute the power networks of smart cities? How can LTS theory explain this evolution both in terms of technical aspects and technopolitics?

scholarly journals Artificial intelligence, physiological genomics, and precision medicine

2018 ◽  
Vol 50 (4) ◽  
pp. 237-243 ◽  
Author(s):  
Anna Marie Williams ◽  
Yong Liu ◽  
Kevin R. Regner ◽  
Fabrice Jotterand ◽  
Pengyuan Liu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Precision Medicine ◽  
Ethical Issues ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Common Diseases ◽  
Powerful Approach ◽  
Genetic And Environmental Factors ◽  
Analytical Approaches

Big data are a major driver in the development of precision medicine. Efficient analysis methods are needed to transform big data into clinically-actionable knowledge. To accomplish this, many researchers are turning toward machine learning (ML), an approach of artificial intelligence (AI) that utilizes modern algorithms to give computers the ability to learn. Much of the effort to advance ML for precision medicine has been focused on the development and implementation of algorithms and the generation of ever larger quantities of genomic sequence data and electronic health records. However, relevance and accuracy of the data are as important as quantity of data in the advancement of ML for precision medicine. For common diseases, physiological genomic readouts in disease-applicable tissues may be an effective surrogate to measure the effect of genetic and environmental factors and their interactions that underlie disease development and progression. Disease-applicable tissue may be difficult to obtain, but there are important exceptions such as kidney needle biopsy specimens. As AI continues to advance, new analytical approaches, including those that go beyond data correlation, need to be developed and ethical issues of AI need to be addressed. Physiological genomic readouts in disease-relevant tissues, combined with advanced AI, can be a powerful approach for precision medicine for common diseases.

scholarly journals Artificial Intelligence and Big Data in Public Health

2018 ◽  
Vol 15 (12) ◽  
pp. 2796 ◽  
Author(s):  
Kurt Benke ◽  
Geza Benke
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Big Data ◽  
Economic Performance ◽  
Data Analytics ◽  
Ethical Issues ◽  
Medical Professionals ◽  
Societal Change ◽  
The Future ◽  
Research Problems

Artificial intelligence and automation are topics dominating global discussions on the future of professional employment, societal change, and economic performance. In this paper, we describe fundamental concepts underlying AI and Big Data and their significance to public health. We highlight issues involved and describe the potential impacts and challenges to medical professionals and diagnosticians. The possible benefits of advanced data analytics and machine learning are described in the context of recently reported research. Problems are identified and discussed with respect to ethical issues and the future roles of professionals and specialists in the age of artificial intelligence.

scholarly journals Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review (Preprint)

2020 ◽  
Author(s):  
Qiang Pan ◽  
Damien Brulin ◽  
Eric Campo
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Mining ◽  
Big Data ◽  
Monitoring System ◽  
The Body ◽  
Monitoring Systems ◽  
Sleep Monitoring ◽  
Advantages And Disadvantages ◽  
System Solution

BACKGROUND Sleep is essential for human health. Considerable effort has been put into academic and industrial research and in the development of wireless body area networks for sleep monitoring in terms of nonintrusiveness, portability, and autonomy. With the help of rapid advances in smart sensing and communication technologies, various sleep monitoring systems (hereafter, sleep monitoring systems) have been developed with advantages such as being low cost, accessible, discreet, contactless, unmanned, and suitable for long-term monitoring. OBJECTIVE This paper aims to review current research in sleep monitoring to serve as a reference for researchers and to provide insights for future work. Specific selection criteria were chosen to include articles in which sleep monitoring systems or devices are covered. METHODS This review investigates the use of various common sensors in the hardware implementation of current sleep monitoring systems as well as the types of parameters collected, their position in the body, the possible description of sleep phases, and the advantages and drawbacks. In addition, the data processing algorithms and software used in different studies on sleep monitoring systems and their results are presented. This review was not only limited to the study of laboratory research but also investigated the various popular commercial products available for sleep monitoring, presenting their characteristics, advantages, and disadvantages. In particular, we categorized existing research on sleep monitoring systems based on how the sensor is used, including the number and type of sensors, and the preferred position in the body. In addition to focusing on a specific system, issues concerning sleep monitoring systems such as privacy, economic, and social impact are also included. Finally, we presented an original sleep monitoring system solution developed in our laboratory. RESULTS By retrieving a large number of articles and abstracts, we found that hotspot techniques such as big data, machine learning, artificial intelligence, and data mining have not been widely applied to the sleep monitoring research area. Accelerometers are the most commonly used sensor in sleep monitoring systems. Most commercial sleep monitoring products cannot provide performance evaluation based on gold standard polysomnography. CONCLUSIONS Combining hotspot techniques such as big data, machine learning, artificial intelligence, and data mining with sleep monitoring may be a promising research approach and will attract more researchers in the future. Balancing user acceptance and monitoring performance is the biggest challenge in sleep monitoring system research.

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