ASPECTS REGARDING THE USE OF ARTIFICIAL INTELLIGENCE IN IMPROVING DEFENSE RESOURCE MANAGEMENT

2021 ◽  
Vol 17 (1) ◽  
pp. 323-330
Author(s):  
Gabriela-Florina NICOARĂ ◽  
Gergonia-Cristiana BOGĂȚEANU
Keyword(s):  
Artificial Intelligence ◽  
Resource Management ◽  
Technological Progress ◽  
Digital Systems ◽  
Constructive Approach ◽  
The Past ◽  
A Priority ◽  
High Level

Abstract: Regarding the society evolution dominated by a high-level technology, we consider this article a constructive approach. The aim of the paper is to highlight a few activities/places/spots in which competences of humans/soldiers interfere with different elements of the artificial intelligence. We deem that the technological progress in the past few years has been impressive. Nowadays, thousands of activities that were mostly or exclusively executed by people can be done faster and often with greater precision using digital systems. In this instance and considering the achievement of functional compatibility between Romanian Army and forces from NATO as being a priority, the development of the technology based on artificial intelligence is vital within the defense resource management.

scholarly journals Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021

AI and Ethics ◽  
2021 ◽  
Author(s):  
Muhammad Ali Chaudhry ◽  
Emre Kazim
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Tutoring Systems ◽  
Policy Makers ◽  
Tutoring Systems ◽  
Research And Practice ◽  
The Past ◽  
Artificial Intelligence In Education ◽  
Potential Impact ◽  
High Level ◽  
Contextualized Learning

AbstractIn the past few decades, technology has completely transformed the world around us. Indeed, experts believe that the next big digital transformation in how we live, communicate, work, trade and learn will be driven by Artificial Intelligence (AI) [83]. This paper presents a high-level industrial and academic overview of AI in Education (AIEd). It presents the focus of latest research in AIEd on reducing teachers’ workload, contextualized learning for students, revolutionizing assessments and developments in intelligent tutoring systems. It also discusses the ethical dimension of AIEd and the potential impact of the Covid-19 pandemic on the future of AIEd’s research and practice. The intended readership of this article is policy makers and institutional leaders who are looking for an introductory state of play in AIEd.

The Future of Work and the Changing Workplace

2018 ◽  
Author(s):  
Mahesh K. Joshi ◽  
J.R. Klein
Keyword(s):  
Artificial Intelligence ◽  
Machine Intelligence ◽  
Political Issue ◽  
Digital Innovation ◽  
Future Of Work ◽  
The Past ◽  
The World ◽  
Public Debates ◽  
The Future ◽  
Market Opportunities

The world of work has been impacted by technology. Work is different than it was in the past due to digital innovation. Labor market opportunities are becoming polarized between high-end and low-end skilled jobs. Migration and its effects on employment have become a sensitive political issue. From Buffalo to Beijing public debates are raging about the future of work. Developments like artificial intelligence and machine intelligence are contributing to productivity, efficiency, safety, and convenience but are also having an impact on jobs, skills, wages, and the nature of work. The “undiscovered country” of the workplace today is the combination of the changing landscape of work itself and the availability of ill-fitting tools, platforms, and knowledge to train for the requirements, skills, and structure of this new age.

Europe

2020 ◽  
pp. 649-666
Author(s):  
Andrea Renda
Keyword(s):  
Artificial Intelligence ◽  
Digital Technology ◽  
Policy Framework ◽  
Expert Group ◽  
Ethical Guidelines ◽  
Ethical Implications ◽  
Strong Focus ◽  
Ethics Guidelines ◽  
Definition Of ◽  
High Level

This chapter assesses Europe’s efforts in developing a full-fledged strategy on the human and ethical implications of artificial intelligence (AI). The strong focus on ethics in the European Union’s AI strategy should be seen in the context of an overall strategy that aims at protecting citizens and civil society from abuses of digital technology but also as part of a competitiveness-oriented strategy aimed at raising the standards for access to Europe’s wealthy Single Market. In this context, one of the most peculiar steps in the European Union’s strategy was the creation of an independent High-Level Expert Group on AI (AI HLEG), accompanied by the launch of an AI Alliance, which quickly attracted several hundred participants. The AI HLEG, a multistakeholder group including fifty-two experts, was tasked with the definition of Ethics Guidelines as well as with the formulation of “Policy and Investment Recommendations.” With the advice of the AI HLEG, the European Commission put forward ethical guidelines for Trustworthy AI—which are now paving the way for a comprehensive, risk-based policy framework.

scholarly journals Customized Slicing for 6G: Enforcing Artificial Intelligence on Resource Management

IEEE Network ◽  
2021 ◽  
pp. 1-8
Author(s):  
Wanqing Guan ◽  
Haijun Zhang ◽  
Victor C. M. Leung
Keyword(s):  
Artificial Intelligence ◽  
Resource Management

Machine learning for rediscovering revolutionary ideas of the past

2021 ◽  
pp. 105971232098304
Author(s):  
R Alexander Bentley ◽  
Joshua Borycz ◽  
Simon Carrignon ◽  
Damian J Ruck ◽  
Michael J O’Brien
Keyword(s):  
Language Processing ◽  
Scientific Progress ◽  
Phylogenetic Inference ◽  
The Past ◽  
New Methods ◽  
Inherent Nature ◽  
Social Learning Processes ◽  
High Level ◽  
Scientific Ideas ◽  
Revolutionary Science

The explosion of online knowledge has made knowledge, paradoxically, difficult to find. A web or journal search might retrieve thousands of articles, ranked in a manner that is biased by, for example, popularity or eigenvalue centrality rather than by informed relevance to the complex query. With hundreds of thousands of articles published each year, the dense, tangled thicket of knowledge grows even more entwined. Although natural language processing and new methods of generating knowledge graphs can extract increasingly high-level interpretations from research articles, the results are inevitably biased toward recent, popular, and/or prestigious sources. This is a result of the inherent nature of human social-learning processes. To preserve and even rediscover lost scientific ideas, we employ the theory that scientific progress is punctuated by means of inspired, revolutionary ideas at the origin of new paradigms. Using a brief case example, we suggest how phylogenetic inference might be used to rediscover potentially useful lost discoveries, as a way in which machines could help drive revolutionary science.

Artificial Intelligence and Human Rights: Four Realms of Discussion: Summary of Remarks

2020 ◽  
Vol 114 ◽  
pp. 242-245
Author(s):  
Jootaek Lee
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Deep Learning ◽  
Language Processing ◽  
Human Reasoning ◽  
The Past ◽  
Making Choices ◽  
Data Capturing ◽  
Intensive Procedures

The term, Artificial Intelligence (AI), has changed since it was first coined by John MacCarthy in 1956. AI, believed to have been created with Kurt Gödel's unprovable computational statements in 1931, is now called deep learning or machine learning. AI is defined as a computer machine with the ability to make predictions about the future and solve complex tasks, using algorithms. The AI algorithms are enhanced and become effective with big data capturing the present and the past while still necessarily reflecting human biases into models and equations. AI is also capable of making choices like humans, mirroring human reasoning. AI can help robots to efficiently repeat the same labor intensive procedures in factories and can analyze historic and present data efficiently through deep learning, natural language processing, and anomaly detection. Thus, AI covers a spectrum of augmented intelligence relating to prediction, autonomous intelligence relating to decision making, automated intelligence for labor robots, and assisted intelligence for data analysis.

scholarly journals Boundaries Between Research Ethics and Ethical Research Use in Artificial Intelligence Health Research

2021 ◽  
pp. 155626462110027
Author(s):  
Gabrielle Samuel ◽  
Jenn Chubb ◽  
Gemma Derrick
Keyword(s):  
Artificial Intelligence ◽  
Health Research ◽  
Decision Makers ◽  
Societal Impact ◽  
The Past ◽  
Research And Innovation ◽  
The United Kingdom ◽  
Responsible Research ◽  
Past Half

The governance of ethically acceptable research in higher education institutions has been under scrutiny over the past half a century. Concomitantly, recently, decision makers have required researchers to acknowledge the societal impact of their research, as well as anticipate and respond to ethical dimensions of this societal impact through responsible research and innovation principles. Using artificial intelligence population health research in the United Kingdom and Canada as a case study, we combine a mapping study of journal publications with 18 interviews with researchers to explore how the ethical dimensions associated with this societal impact are incorporated into research agendas. Researchers separated the ethical responsibility of their research with its societal impact. We discuss the implications for both researchers and actors across the Ethics Ecosystem.

The Future of the Planetary Trust in a Kaleidoscopic World

2021 ◽  
pp. 1-8
Author(s):  
Edith Brown Weiss
Keyword(s):  
Artificial Intelligence ◽  
Natural Resource ◽  
Human Activities ◽  
New Technologies ◽  
Future Generations ◽  
Nuclear War ◽  
Human Environment ◽  
The Past ◽  
Resource Degradation ◽  
Shared Goal

Today, it is evident that we are part of a planetary trust. Conserving our planet represents a public good, global as well as local. The threats to future generations resulting from human activities make applying the normative framework of a planetary trust even more urgent than in the past decades. Initially, the planetary trust focused primarily on threats to the natural system of our human environment such as pollution and natural resource degradation, and on threats to cultural heritage. Now, we face a higher threat of nuclear war, cyber wars, and threats from gene drivers that can cause inheritable changes to genes, potential threats from other new technologies such as artificial intelligence, and possible pandemics. In this context, it is proposed that in the kaleidoscopic world, we must engage all the actors to cooperate with the shared goal of caring for and maintaining planet Earth in trust for present and future generations.

scholarly journals Application of Artificial Intelligence in Food Industry—a Guideline

2021 ◽  
Author(s):  
Nidhi Rajesh Mavani ◽  
Jarinah Mohd Ali ◽  
Suhaili Othman ◽  
M. A. Hussain ◽  
Haslaniza Hashim ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Food Industry ◽  
Near Infrared ◽  
Vision System ◽  
Electronic Tongue ◽  
World Population ◽  
Computer Vision System ◽  
The Past

AbstractArtificial intelligence (AI) has embodied the recent technology in the food industry over the past few decades due to the rising of food demands in line with the increasing of the world population. The capability of the said intelligent systems in various tasks such as food quality determination, control tools, classification of food, and prediction purposes has intensified their demand in the food industry. Therefore, this paper reviews those diverse applications in comparing their advantages, limitations, and formulations as a guideline for selecting the most appropriate methods in enhancing future AI- and food industry–related developments. Furthermore, the integration of this system with other devices such as electronic nose, electronic tongue, computer vision system, and near infrared spectroscopy (NIR) is also emphasized, all of which will benefit both the industry players and consumers.

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