scholarly journals Evolution in Education: Chatbots

2020 ◽  
Vol 3 (1) ◽  
pp. 47
Author(s):  
George Dimitriadis
Keyword(s):  
Artificial Intelligence ◽  
Everyday Life ◽  
Adaptive Learning ◽  
Teaching Assistants ◽  
Global Market ◽  
Quality Education ◽  
Customer Engagement ◽  
Educational Settings ◽  
Advantages And Disadvantages ◽  
Repetitive Tasks

Artificial intelligence (AI) programs that simulate interactive human conversation, known as Chatbots, are one of the ongoing trends in the global market. Companies adopt Chatbots in order to offer better services to their customers. Businesses have realized that they are able to enhance the process of customer engagement and operational efficiency through Chatbot technology. Furthermore, most of us have experienced communication of this form in many aspects of our everyday life. This paper examines how Chatbots have evolved over the years, what the advantages and disadvantages of using them are and tries to explain the rise taking place nowadays. Subsequently, it explores the potential of applying this technology in educational settings. Personalized and adaptive learning seems to be imperative today and Chatbot technology can offer invaluable services towards that direction. Finally, it investigates the possibility of using them as virtual teaching assistants relieving teachers from the burden of repetitive tasks and helping them focus more on providing quality education to their students.

The Future of Human Workers

2018 ◽  
Author(s):  
Mahesh K. Joshi ◽  
J.R. Klein
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Mental Capacity ◽  
Machine Intelligence ◽  
The Internet ◽  
Traditional Model ◽  
Global Workforce ◽  
Repetitive Tasks ◽  
The Internet Of Things

New technologies like artificial intelligence, robotics, machine intelligence, and the Internet of Things are seeing repetitive tasks move away from humans to machines. Humans cannot become machines, but machines can become more human-like. The traditional model of educating workers for the workforce is fast becoming irrelevant. There is a massive need for the retooling of human workers. Humans need to be trained to remain focused in a society which is constantly getting bombarded with information. The two basic elements of physical and mental capacity are slowly being taken over by machines and artificial intelligence. This changes the fundamental role of the global workforce.

scholarly journals Aggregator of Demand Response for Renewable Integration and Customer Engagement: Strengths, Weaknesses, Opportunities, and Threats

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2391 ◽  
Author(s):  
Kody Ponds ◽  
Ali Arefi ◽  
Ali Sayigh ◽  
Gerard Ledwich
Keyword(s):  
Demand Response ◽  
Electricity Market ◽  
Swot Analysis ◽  
Traditional Approach ◽  
Customer Engagement ◽  
Energy Integration ◽  
New Approach ◽  
Advantages And Disadvantages ◽  
Knowledge Based ◽  
Political Economic

The world is progressing towards a more advanced society where end-consumers have access to local renewable-based generation and advanced forms of information and technology. Hence, it is in a current state of transition between the traditional approach to power generation and distribution, where end-consumers of electricity have typically been inactive in their involvement with energy markets and a new approach that integrates their active participation. This new approach includes the use of distributed energy resources (DER) such as renewable-based generation and demand response (DR), which are being rapidly adopted by end-consumers where incentives are strong. This paper presents the role of the DR aggregator to effectively integrate DER technology as a new source of energy capacity into electricity networks using information communication technology and industry knowledge., Based on DR aggregators, this framework will efficiently facilitate renewable energy integration and customer engagement into the electricity market. To this aim, advantages and disadvantages of DR aggregators are discussed in this paper from political, economic, social, and technological (PEST) points of view. Based on this analysis, a strengths, weaknesses, opportunities, and threats (SWOT) analysis for a typical DR aggregator is presented.

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.

scholarly journals Challenges of Aligning Artificial Intelligence with Human Values

2020 ◽  
Vol 8 (2) ◽  
pp. 54-72
Author(s):  
Margit Sutrop ◽  
Keyword(s):  
Artificial Intelligence ◽  
Everyday Life ◽  
Human Values ◽  
Moral Problem ◽  
Technical Challenge ◽  
Moral Principles ◽  
Normative Question ◽  
Alignment Problem ◽  
The Normative Question

As artificial intelligence (AI) systems are becoming increasingly autonomous and will soon be able to make decisions on their own about what to do, AI researchers have started to talk about the need to align AI with human values. The AI ‘value alignment problem’ faces two kinds of challenges—a technical and a normative one—which are interrelated. The technical challenge deals with the question of how to encode human values in artificial intelligence. The normative challenge is associated with two questions: “Which values or whose values should artificial intelligence align with?” My concern is that AI developers underestimate the difficulty of answering the normative question. They hope that we can easily identify the purposes we really desire and that they can focus on the design of those objectives. But how are we to decide which objectives or values to induce in AI, given that there is a plurality of values and moral principles and that our everyday life is full of moral disagreements? In my paper I will show that although it is not realistic to reach an agreement on what we, humans, really want as people value different things and seek different ends, it may be possible to agree on what we do not want to happen, considering the possibility that intelligence, equal to our own, or even exceeding it, can be created. I will argue for pluralism (and not for relativism!) which is compatible with objectivism. In spite of the fact that there is no uniquely best solution to every moral problem, it is still possible to identify which answers are wrong. And this is where we should begin the value alignment of AI.

The perspective of the use of artificial intelligence in the formation and control of modern and future urban areas

2021 ◽  
Vol 2 (80) ◽  
pp. 309-313
Author(s):  
D.N. Abilev ◽  
◽  
G.S. Dzhakipova ◽  
Keyword(s):  
Artificial Intelligence ◽  
Everyday Life ◽  
Urban Areas ◽  
Perfect Model ◽  
Routine Tasks ◽  
And Control

With the development of technologies and their introduction into everyday life, there is also the possibility of their professional use in various industries and structures. The AI system is a virtual assistant, whose development every year can create a perfect model of urban control and a virtual assistant in helping people with many routine tasks. This article describes the prospects for using AI and examples of its development.

REVISITING THE METHODOLOGICAL DEVELOPMENT IN SOIL EROSION RESEARCH

Ensemble ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 145-165
Author(s):  
Tanmoy Sarkar ◽  
◽  
Tapas Pal ◽  
Keyword(s):  
Artificial Intelligence ◽  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Geographic Information ◽  
Methodological Development ◽  
Advantages And Disadvantages ◽  
The Future ◽  
Soil Erosion By Water

Soil erosion (by water) is a major land degradation process that may threat the Sustainable Development Goals (SDG) by its negative impact on environment and human well-being. Soil erosion research demands scientific methods, tools and techniques to assess soil erosion with more accuracy and reliability. Soil erosion research has had experienced crude field-based techniques in early twentieth century to model-based approaches since the 1970s and very recent machine learning and artificial intelligence models to predict soil erosion susceptibility and risk. The paper aims to review the trend in methodological development in soil erosion by water through time. The brief background of different approaches, their relative advantages and disadvantages are reviewed. Depending on the time of establishment and wide application the approaches are classified and represented as erosion plot/runoff approach, erosion pin technique followed by environmental tracer method and model approach in combination with Remote Sensing (RS) and Geographic Information System (GIS). Recent advancement in artificial intelligence and application of statistical techniques have a great potential to contribute in soil erosion research by identifying various degrees of susceptibility in large scale and also to quantify the erosion rate with high accuracy. The Remote sensing (RS) and Geographic Information System (GIS) contribute to develop regional scale data base with exploration of real time data and spatial analysis. The combination of RS & GIS and process-based models must be more effective than the traditional soil erosion model in the context of prediction with greater reliability and validity. The future research on soil erosion is better to focus on the theoretical analysis and development of erosion prediction model with more quantitative refinement and to model the future.

The Changing Roles of Teachers With AI

2020 ◽  
pp. 1-25
Author(s):  
Libi Shen ◽  
Anchi Su
Keyword(s):  
Artificial Intelligence ◽  
Technology In Education ◽  
Human Beings ◽  
Educational Settings ◽  
Ethical Concerns ◽  
The Past ◽  
Changing Roles

Artificial intelligence (AI) is ubiquitous in our lives and is progressing at an accelerated rate in the past 60 years. AI application is diverse and AI technology continues to grow. It enables a machine to think like human beings and has opened a new horizon for industries, businesses, transportation, hospitals, and schools. How is AI applied to educational settings? How will the emergence of AI technology assist teachers' teaching and improve students' learning? Will the implementation of AI technology in education replace schoolteachers? What would be the ethical concerns of AI technology? What role do teachers play with AI in education? The purpose of this chapter is to explore the roles that teachers play in the innovation and evolution of AI and to seek approaches teachers should take in coping with AI technology. Issues and problems of teaching with AI will be discussed; solutions will be recommended.

The Impact of Personal Response Systems on Students' Learning Performance

2018 ◽  
pp. 234-250
Author(s):  
Simon C. H. Chan ◽  
Stephen Ko
Keyword(s):  
Theoretical Model ◽  
Contextual Factors ◽  
Learning Performance ◽  
Educational Settings ◽  
Personal Response Systems ◽  
Advantages And Disadvantages ◽  
Response Systems ◽  
The Impact

Personal response systems (PRSs) are prevalent across a range of educational settings, and this increasing importance has prompted many researchers to examine their various aspects. Their effects on students' learning performance have three main categories of antecedents: the learners' characteristics, the instructors' characteristics, and other contextual factors. A theoretical model is developed on the effects of PRSs on students' learning performance. This chapter describes the characteristics of PRSs, reviews their advantages and disadvantages, and proposes a theoretical model of their antecedents on students' learning performance. It concludes by exploring research implications and directions for future PRS research.

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