scholarly journals ARTIFICIAL INTELLIGENCE AS A SOCIAL REGULATOR: PROS AND CONS

2018 ◽  
pp. 55-68 ◽  
Author(s):  
Roman I. Dremliuga ◽  
Alexey S. Koshel
Keyword(s):  
Artificial Intelligence ◽  
Pros And Cons

scholarly journals The Pros & Cons of Business Innovation at IT Organizations

2019 ◽  
Vol 7 (1) ◽  
pp. 82-85
Author(s):  
Geetha Swaminathan
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Information Technology ◽  
Cloud Computing ◽  
New Technologies ◽  
Global Market ◽  
Innovative Product ◽  
Business Innovation ◽  
It Organization ◽  
Pros And Cons

In the 21st Century, the buzzword is often used in all fields is “Innovation". It is no wonder using Innovation in day to the conversation as well as striving for innovation execution at organisations in Information Technology (IT) sectors. When we need to talk about innovation in IT sectors in the fast-moving technology IT organisations, they are in a position in increasing its capability in its innovative product and services. There is a lot of benefits out of business innovations that are being reaped in IT companies; there are apparent disadvantages are also the outcome of them. It is quite common, despite all benefits and drawbacks, they are in apposition to survive in the global market. That becomes a great challenge to all IT organisations. In IT organisations which consist of departments such as Development, Testing, Consulting, Networking, Infrastructure, Process and having common platforms and legacy languages, Apart from that they are in the way of invading new technologies such as Digital, Mobile, IoT, Artificial Intelligence, Machine learning Cloud computing. In all the fields, as mentioned above and area, they need to do innovation to sustain their business. This paper will provide elaborate results on Pros and Cons of Business Innovation in IT Organization.

Design Optimization of a Wind Turbine Using Artificial Intelligence

2017 ◽  
pp. 38-66
Author(s):  
Jagan Jayabalan ◽  
Dalkilic Yildirim ◽  
Dookie Kim ◽  
Pijush Samui
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Wind Turbine ◽  
Power Factor ◽  
Relevance Vector Machine ◽  
Support Vector ◽  
Speed Ratio ◽  
Tip Speed Ratio ◽  
Learning Framework ◽  
Pros And Cons

This chapter examines the capability of Support Vector Machine (SVM), Relevance Vector Machine (RVM) and Genetic Programming (GP) for the optimal design of wind turbine. The excellent design has been influenced by various factors, such as profile of the blade, number of blades, power factor and tip speed ratio. The key to design a wind turbine is to Assessing the optimal tip speed ratio (TSR) is the key for designing the wind turbine. This chapter handles the Artificial Intelligence techniques in predicting the optimal TSR and the power factor based on the parameters engaged for NACA 4415 and LS-1 profile types with 3 and 4 blades. The organized machine learning framework is anticipated to be lucrative than the traditional way in foretelling the TSR and power factor. The machine learning models are then compared with the existing Neural Network model and the pros and cons of the various models are inferred from the results.

scholarly journals Artificial Intelligence in Criminal Law: Pros and Cons

2019 ◽  
Vol 10 (4) ◽  
Author(s):  
Vasily Nekrasov
Keyword(s):  
Artificial Intelligence ◽  
Criminal Law ◽  
Human Intelligence ◽  
Creative Activity ◽  
Intellectual Activity ◽  
Distinctive Features ◽  
Pros And Cons ◽  
Human Thinking ◽  
The Given

The paper investigates the essence, concept and distinctive features of artificial intelligence. The author notes that currently there is no unified position not only in understanding the essence of this phenomenon, but also its capabilities. The analysis of the given definitions of the analyzed phenomenon allows to draw a number of conclusions. First, the artificial intelligence should not be confused with the so-called "natural intelligence" or human intelligence. Secondly, in understanding the essence of the artificial intelligence, various components of human thinking are included, some where it is creative activity, somewhere it is intellectual activity, etc. At the same time, this is important to understand the essence of the concept under consideration. Thirdly, it is necessary to identify types of the artificial intelligence. So, it is accepted to allocate strong and weak systems of artificial intelligence. So, it is accustomed to specify strong and week systems of the artificial intellect. The article substantiates that when the domestic legislator constructs norms on crimes related to the artificial intelligence, they should be based on a refutable presumption of its (artificial intelligence) public danger.

Smart Automotive Systems Supported by Configurable FPGA, IoT, and Artificial Intelligence Techniques

2020 ◽  
pp. 108-132
Author(s):  
S. Saravanan
Keyword(s):  
Artificial Intelligence ◽  
Network Information ◽  
Automotive Systems ◽  
Control Units ◽  
Field Programmable ◽  
Pros And Cons ◽  
Assistance Systems ◽  
Essential Knowledge ◽  
Intelligent Assistance ◽  
Dedicated Hardware

Modern vehicles are very complex by incorporating various computational signals and critical information transactions. Electronic control units (ECUs) are embedded with various software functions, network information, sensor/actuator communication, and dedicated hardware. Altogether, the special hardware needs to be adaptable to the current needs of next-generation vehicles. This chapter will give a broad idea about modern automotive systems by considering various factors. Finding the best reconfigurable field programmable gate array (FPGA)-based hardware, intelligent assistance systems for drivers and various communication protocols are elaborated in this chapter. Moreover, it also provides the essential knowledge of IoT-based smart automotive systems along with its pros and cons. This chapter also gives the awareness and comparative study of artificial intelligence (AI) systems in the present smart automotive systems. The overall observation of this chapter will satisfy the audience by knowing the reconfigurable FPGA, IoT, and artificial intelligence-based automotive systems.

scholarly journals Academic Policy Regarding Sustainability and Artificial Intelligence (AI)

2020 ◽  
Vol 12 (22) ◽  
pp. 9435
Author(s):  
Muhammad Tanveer ◽  
Shafiqul Hassan ◽  
Amiya Bhaumik
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
Educational Systems ◽  
Development Education ◽  
High Quality Education ◽  
Academic Policy ◽  
Pros And Cons ◽  
Using Data ◽  
Sustainability Policy ◽  
The Impact

Artificial intelligence (AI) has grown, and technologies have intensified across all fields of life, particularly in education. AI has been applied to resources to improve skills giving teachers the time and freedom to provide understanding and adaptability and drive performance. This paper, written for policymakers in the field of education, highlights the impact of AI and advancements in academic policy. These academic policymakers generate ideas and strategies for applying AI across various disciplines. There is also discussion around AI implementation in education throughout developing nations for moving towards and ensuring affordable, high-quality education for every individual. Education for sustainable development (ESD) aims to promote the development of knowledge, skills, understanding, values and actions necessary to build a sustainable world, to protect and preserve the environment, and promote social equity and economic sustainability. This paper analyses how AI can be used to update learning probabilities by providing examples of how it can be integrated with existing educational systems, using data to improve educational capital and quality in developing countries. It goes on to discuss whether policymakers and institutions can reinvent and rework educational programs to polish graduates’ skills for the growing presence of AI across all disciplines. There are four main parts to this work: (1) different dimensions regarding the complexities and potential implications, (2) the pros and cons of educational sustainability policy related to AI, (3) carving out AI and its outstanding execution, and finally (4) the linkage of AI with higher education within the context of educational expansions. In conclusion, the paper focuses on AI’s applications, benefits and sustainable development education challenges.

Digital Exam and Assessments

2019 ◽  
pp. 245-263 ◽  
Author(s):  
A. Mohammed Abubakar ◽  
Ibrahim Adeshola
Keyword(s):  
Artificial Intelligence ◽  
Faculty Development ◽  
Teaching And Learning ◽  
The Internet ◽  
Generational Cohorts ◽  
Generational Difference ◽  
Pros And Cons ◽  
Knowledge Emergence

Although it is widely recognized that exam and assessments are ways to explore and query knowledge, emergence of the internet, digitalization, and the deployment of artificial intelligence in teaching and learning extends the concept to digital exam and assessment. Some lines of research suggest that digital exam and assessments are costly and unfortunate, whereas others suggest that it is beneficial and adaptive. However, there are little theoretical underpinnings probing these arguments. To fill the void, this chapter probe existing teaching and learning literature, and concepts of digital exam and assessments relative to faculty development. To this end, this chapter theorize that these concepts are contingents on generational cohorts, arguments that advances and reorients research on digital exam and assessment, and generational difference are highlighted. The chapter concludes with pros and cons associated with digital assessments.

scholarly journals How Artificial Intelligence and New Technologies Can Help the Management of the COVID-19 Pandemic

2021 ◽  
Vol 18 (14) ◽  
pp. 7648
Author(s):  
Davide Barbieri ◽  
Enrico Giuliani ◽  
Anna Del Prete ◽  
Amanda Losi ◽  
Matteo Villani ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Hospital Environment ◽  
Private Companies ◽  
Healthcare Facilities ◽  
Material Resources ◽  
First Case ◽  
Pros And Cons ◽  
Environmental Measures ◽  
Development And Management

The COVID-19 pandemic has worked as a catalyst, pushing governments, private companies, and healthcare facilities to design, develop, and adopt innovative solutions to control it, as is often the case when people are driven by necessity. After 18 months since the first case, it is time to think about the pros and cons of such technologies, including artificial intelligence—which is probably the most complex and misunderstood by non-specialists—in order to get the most out of them, and to suggest future improvements and proper adoption. The aim of this narrative review was to select the relevant papers that directly address the adoption of artificial intelligence and new technologies in the management of pandemics and communicable diseases such as SARS-CoV-2: environmental measures; acquisition and sharing of knowledge in the general population and among clinicians; development and management of drugs and vaccines; remote psychological support of patients; remote monitoring, diagnosis, and follow-up; and maximization and rationalization of human and material resources in the hospital environment.

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