scholarly journals Dealing Crisis Management using AI

2021 ◽  
Vol 11 (05) ◽  
pp. 15-22
Author(s):  
Yew Kee Wong
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Crisis Management ◽  
Social Life ◽  
Decision Makers ◽  
Advanced Technology ◽  
Business Operations ◽  
The World ◽  
Tools And Techniques ◽  
Management Domains

Artificial intelligence has been a buzz word that is impacting every industry in the world. With the rise of such advanced technology, there will be always a question regarding its impact on our social life, environment and economy thus impacting all efforts exerted towards sustainable development. In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets for different industries and business operations. Numerous use cases have shown that AI can ensure an effective supply of information to citizens, users and customers in times of crisis. This paper aims to analyse some of the different methods and scenario which can be applied to AI and big data, as well as the opportunities provided by the application in various business operations and crisis management domains.

scholarly journals Dealing Crisis Management using AI

2021 ◽  
Author(s):  
Yew Kee Wong
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Crisis Management ◽  
Social Life ◽  
Decision Makers ◽  
Advanced Technology ◽  
Business Operations ◽  
The World ◽  
Tools And Techniques ◽  
Management Domains

Artificial intelligence has been a buzz word that is impacting every industry in the world. With the rise of such advanced technology, there will be always a question regarding its impact on our social life, environment and economy thus impacting all efforts exerted towards sustainable development. In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets for different industries and business operations. Numerous use cases have shown that AI can ensure an effective supply of information to citizens, users and customers in times of crisis. This paper aims to analyse some of the different methods and scenario which can be applied to AI and big data, as well as the opportunities provided by the application in various business operations and crisis management domains.

scholarly journals Using AI to Learn Industry Specific Big Data for Business Operation and Crisis Management

2021 ◽  
Author(s):  
Yew Kee Wong
Keyword(s):  
Big Data ◽  
Crisis Management ◽  
Social Life ◽  
Decision Makers ◽  
Advanced Technology ◽  
Business Operation ◽  
Business Operations ◽  
The World ◽  
Tools And Techniques ◽  
Management Domains

Artificial intelligence has been a buzz word that is impacting every industry in the world. With the rise of such advanced technology, there will be always a question regarding its impact on our social life, environment and economy thus impacting all efforts exerted towards sustainable development. In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets for different industries and business operations. Numerous use cases have shown that AI can ensure an effective supply of information to citizens, users and customers in times of crisis. This paper aims to analyse some of the different methods and scenario which can be applied to AI and big data, as well as the opportunities provided by the application in various business operations and crisis management domains.

scholarly journals Applying AI and Big Data for Sensitive Operations and Disaster Management

2021 ◽  
Author(s):  
Yew Kee Wong
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
Big Data ◽  
Disaster Management ◽  
Social Life ◽  
Decision Makers ◽  
Advanced Technology ◽  
Business Operations ◽  
The World ◽  
Tools And Techniques

Artificial intelligence has been a buzz word that is impacting every industry in the world. With the rise of such advanced technology, there will be always a question regarding its impact on our social life, environment and economy thus impacting all efforts exerted towards sustainable development. In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets for different industries and business operations. Numerous use cases have shown that AI can ensure an effective supply of information to citizens, users and customers in times of crisis. This paper aims to analyse some of the different methods and scenario which can be applied to AI and big data, as well as the opportunities provided by the application in various sensitive operations and disaster management.

Machine Learning and Deep Learning Technologies

2021 ◽  
Author(s):  
Yew Kee Wong
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Deep Learning ◽  
Model Building ◽  
Learning Technologies ◽  
Decision Makers ◽  
Human Intervention ◽  
Learning Techniques ◽  
Tools And Techniques

In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets. Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. Such minimal human intervention can be provided using machine learning, which is the application of advanced deep learning techniques on big data. This paper aims to analyse some of the different machine learning and deep learning algorithms and methods, aswell as the opportunities provided by the AI applications in various decision making domains.

scholarly journals Artificial Intelligence Usage in Zakat Optimization

2019 ◽  
pp. 14-24
Author(s):  
Fajar Nugraha ◽  
Sendi Permadia ◽  
Aditya Rahmat Gunawan ◽  
Erip Saeful
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Social Life ◽  
Industrial Revolution ◽  
Research Subject ◽  
Time Saving ◽  
The World

The development of big data and Artificial Intelligence is a challenge and also opportunity in managing zakat. Dramatically changes of technology could impact on social life and employment throughout the world, including zakat institutions. This study discusses changes in the management of zakat in 4.0 industrial revolution era, and how big data and Artificial Intelligence take over part of amil duties. The method used in this research is qualitative with a constructivistic paradigm. The research subject of this study is Rumah Zakat as the national zakat institution, with the object of research on the change in management of zakat from zakat 1.0 era to the era of zakat 4.0 and any AI technology that can take over part of amil duties. There is a change in the management of zakat from the zakat 1.0 era to the zakat 4.0 era which is certainly influenced by the development of industrial revolution. The presence of AI technology has taken over part of the amil duties at Rumah Zakat, which is in charge of serving both muzakki and mustahiq. With the presence of various artificial intelligence and big data devices, made the tasks of amil are simpler, more time-saving, and more efficient.

scholarly journals Leadership in Higher Education – coping with AI and the turbulence of our times

2018 ◽  
Vol 12 (1) ◽  
pp. 683-694
Author(s):  
Mariana Nicolae ◽  
Elena E. Nicolae
Keyword(s):  
Artificial Intelligence ◽  
Higher Education ◽  
Big Data ◽  
Decision Makers ◽  
Human Intelligence ◽  
Higher Education System ◽  
Leadership In Higher Education ◽  
National Media ◽  
The World ◽  
Human Decision

Abstract Today’s world is clearly fractured whether we are looking at it through economic, political, cultural or educational lenses. This is in no way something new. The world has always been in this state, but the speed with which it reacted to real or perceived threats and tried to change accordingly was barely perceivable and, therefore, easier to adopt and adapt to. Today those changes happen with incredible speed and our reactions to them may not be informed or educated and are usually taken by leaders who are, at best, controversial and at worst obviously partial to their own, petty interests against the greater public good they vowed to serve. What can higher education do in such a world? Artificial intelligence (AI) is making huge progress and, although education at all levels is lagging behind in meaningfully adopting AI and working with it, the educational system is expected to react to a world divided by the fear of AI using big data, claiming jobs, and ushering in the era of loss of human supremacy or by the glorification of AI which is only a tool, fast developing indeed, but permanently controlled by human intelligence. Even if that human intelligence is concentrated into fewer and fewer human decision makers thus contributing to the already huge gap of inequality existing in today’s world. The present paper will explore issues related to the way in which the leadership of higher education chooses to handle today’s challenges and will use the home university of the authors to illustrate what happens in Romanian universities. The discussion will be informed by the authors’ own experience in the higher education system as well as by an analysis of various discourses and narratives belonging to different stakeholders, discussing those issues in various inter/national media. The paper will offer some recommendations.

scholarly journals Putting the world back to work: An expert system using big data and artificial intelligence in combating the spread of COVID-19 and similar contagious diseases

Work ◽  
2020 ◽  
Vol 67 (3) ◽  
pp. 557-572
Author(s):  
Said Tkatek ◽  
Amine Belmzoukia ◽  
Said Nafai ◽  
Jaafar Abouchabaka ◽  
Youssef Ibnou-ratib
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Expert System ◽  
Population Monitoring ◽  
High Definition ◽  
Contagious Diseases ◽  
The World ◽  
General Guide ◽  
The Impact ◽  
Back To Work

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the world are turning to data collection and population monitoring for analysis and prediction. The massive data generated through the use of big data and artificial intelligence can play an important role in addressing this unprecedented global health and economic crisis. OBJECTIVES: The objective of this work is to develop an expert system that combines several solutions to combat COVID-19. The main solution is based on a new developed software called General Guide (GG) application. This expert system allows us to explore, monitor, forecast, and optimize the data collected in order to take an efficient decision to ensure the safety of citizens, forecast, and slow down the spread’s rate of COVID-19. It will also facilitate countries’ interventions and optimize resources. Moreover, other solutions can be integrated into this expert system, such as the automatic vehicle and passenger sanitizing system equipped with a thermal and smart High Definition (HD) cameras and multi-purpose drones which offer many services. All of these solutions will facilitate lifting COVID-19 restrictions and minimize the impact of this pandemic. METHODS: The methods used in this expert system will assist in designing and analyzing the model based on big data and artificial intelligence (machine learning). This can enhance countries’ abilities and tools in monitoring, combating, and predicting the spread of COVID-19. RESULTS: The results obtained by this prediction process and the use of the above mentioned solutions will help monitor, predict, generate indicators, and make operational decisions to stop the spread of COVID-19. CONCLUSIONS: This developed expert system can assist in stopping the spread of COVID-19 globally and putting the world back to work.

Who’s making the decisions? How managers can harness artificial intelligence and remain in charge

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pooya Tabesh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Digital Transformation ◽  
Decision Processes ◽  
Decision Makers ◽  
Content Type ◽  
Human Decision ◽  
Practical Implications

Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.

scholarly journals IR 4.0 TECHNOLOGY: JEWEL IN PANDEMIC ERA

2020 ◽  
Vol 5 (21) ◽  
pp. 240-247
Author(s):  
Ahmad Shamsul Abd Aziz ◽  
Nor Azlina Mohd Noor ◽  
Khadijah Mohamed
Keyword(s):  
Artificial Intelligence ◽  
Intellectual Property ◽  
Crisis Management ◽  
World Health ◽  
Human Communication ◽  
Secondary Sources ◽  
Realistic Approach ◽  
Library Research ◽  
The World ◽  
Health Organization

Coronavirus 2019 (COVID 19) was first reported in Wuhan, China in December 2019. The rapidly spreading coronavirus outbreak around the world had forced the World Health Organization (WHO) to declare COVID 19 as a pandemic on March 11, 2020. Crisis management for COVID 19 requires an integrated and realistic approach, and a focus on technology can assist matters to become more efficient. Although IR 4.0 technology is widely used in dealing with pandemic crises, the relevant laws relating to intellectual property laws, especially copyrights and patents with this technology must continue to be protected. This article discusses IR 4.0 technologies such as artificial intelligence (AI) and blockchain as applied in the era of pandemics and intellectual property protection associated with this technology. For this purpose, this article applies library research methodology by analyzing primary and secondary sources. This article concludes that IR 4.0 technology such as artificial intelligence and blockchain is seen as jewels in the era of pandemics because as with the use of this technology, human communication can be reduced. In addition, this technology can also reduce dependence on manpower. Improvements to intellectual property laws can be done in providing more protection against this IR 4.0 technology.

scholarly journals Preface

2021 ◽  
Vol 2050 (1) ◽  
pp. 011001
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Industrial Applications ◽  
Program Committee ◽  
Technical Session ◽  
Technical Program ◽  
Content Type ◽  
The World ◽  
Travel Restrictions ◽  
Virtual Conference

Considering the current situation of COVID-19 and travel restrictions, the 3rd International Conference on Industrial Applications of Big Data and Artificial Intelligence (BDAI 2021) which was planned to be held in Wuhan. China from Sept. 23 to 25, 2021 was changed into virtual conference on Sept. 24, 2021 via Tencent Meeting (Voov) software. BDAI 2021 was organized by China University of Geosciences (Wuhan), sponsored by Hong Kong Society of Mechanical Engineers (HKSME). The Technical Program committee received a total of 38 paper submissions from all over the world, among which 20 papers were accepted, and more than 30 participants attended the conference online, they were from China, Australia, Thailand, Malaysia, India, Japan, UK and more. Four renowned speakers given speeches about their latest research and reports. They are: Prof. Dan Zhang from York University, Canada; Prof. Lefei Zhang from Wuhan University. China: Prof. Deze Zeng from China University of Geosciences (Wuhan), China and Assoc. Prof. Simon James Fong from University of Macau. Macau S.A.R., China. The conference also had 1 technical session and 1 poster sessions. This conference aims to provide a platform for researchers and engineers to share their ideas, recent developments, and successful practices in energy engineering. The participants of the conference were from almost every part of the world, with various background such as academia, industry, and well-known entrepreneurs. Each keynote speech lasted 40 minutes, and authors presentation 15 minutes. Each presentation was included with questions and answers. BDAI 2021 became an effective communication platform for all the participants over the world and unlike some that claim international reach this conference was truly international. The conference proceeding is a compilation of the accepted papers and represent an interesting outcome of the conference. This book covers 3 chapters: 1. Artificial Intelligence: 2. Big Data Technology; 3. Robot System. We would like to acknowledge all of those who supported BDAI 2021. Each individual and institutional help were very important for the success of this conference. Especially we would like to thank the committee chairs, committee members and reviewers, for their tremendous contribution in conference organization and peer review of the papers. We sincerely hope that BDAI 2021 will be a fomrn for excellent discussions that will put forward new ideas and promote collaborative research and support researchers as they take their work forward. We are sure that the proceedings will serve as an important research source of references and the knowledge, which will lead to not only scientific and engineering progress but also other new products and processes. Dan Zhang, York University, Canada

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