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AI, Robotics, and the Workplace of the Future

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... This tenet of TCUM suggests that employees facing DX should be able to forge more positive appraisals and greater self-efficacy if they can find some communicative partner to help them see the bright side of DX. In fact, digital technologies are alleged to free workers from tedious, repetitive jobs and open up the possibilities to create values in radically efficient, modernized ways (Ghosh et al., 2019;Kravchenko, 2019). Thus, it should be possible that employees find hope, or even excitement, in the prospect of their jobs being digitized/digitalized if their attention is navigated appropriately. ...
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Digital transformation provokes a great deal of uncertainty among employees. To gain insights into how employees manage the uncertainty driven by digital transformation and also how leaders can support them, this study has drawn on the theory of communication and uncertainty management (TCUM), which posits that the impact of uncertainty varies by how individuals appraise it and social support enhances positive appraisal. Based on those tenets, the current study advanced the following hypotheses: (a) uncertainty has direct and indirect negative effects on employees’ appraisal of digital transformation, self-efficacy, and job performance; (b) in contrast, direct supervisors’ transformational leadership has direct and indirect positive effects on appraisal, self-efficacy, and job performance; and also (c) transformational leadership moderates the impact of uncertainty. SEM with 4-wave time-separated data (N = 873 employee-supervisor dyads in Japan) found support for these hypotheses. The obtained findings are discussed with reference to TCUM, transformational leadership, and other relevant literature.
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Industry 4.0 is not a new idea and it has long been the focus of the academic community who approached it in many different ways but until now researchers did not agree on one definition. Furthermore, this concept is more and more accepted in the industrial society where companies intend to implement those new technologies to their business models to increase their competitiveness. Therefore it is crucial for companies to primarily understand the content of the Industry 4.0 to successfully transform to digital manufacturing. It is the role of the researchers to study the nine technologies of Industry 4.0 in order to facilitate the implementation of the later in the companies’ processes. To this matter, this paper intends to present a comprehensive literature review in order to establish a clear definition of Industry 4.0, studying independently each of the nine technologies to understand their respective functioning. It then permits us to identify the impacts of the Industry 4.0 nine technologies in manufacturing, logistics and stores. However, experts have agreed that most related theorems and definitions of Industry 4.0 are not mature enough to be implemented in real-life industrial scenarios. This is why in this paper we will also look at the practical implementations of those nine technologies in order to determine and correct the gap between the impacts identified by the academic community and reel-life practitioners. Lastly, many people regard new technologies as a threatening tool whose functioning goes beyond their scope of understanding; they fear that smart devices and systems will take over the control of their lives. This is why explaining the impacts that they will have on businesses and consumers, will increase awareness of Industry 4.0 and the adoption rate of its nine technologies and ultimately make the world a better place to live.
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Advances and Innovations in Systems, Computing Sciences and Software Engineering is a collection of world class paper articles addressing the following topics: Image and Pattern Recognition: Compression, Image processing, Signal Processing Architectures, Signal Processing for Communication, Signal Processing Implementation, Speech Compression, and Video Coding Architectures. Languages and Systems: Algorithms, Databases, Embedded Systems and Applications, File Systems and I/O, Geographical Information Systems, Kernel and OS Structures, Knowledge Based Systems, Modeling and Simulation, Object Based Software Engineering, Programming Languages, and Programming Models and tools. Parallel Processing: Distributed Scheduling, Multiprocessing, Real-time Systems, Simulation Modeling and Development, and Web Applications. New trends in computing: Computers for People of Special Needs, Fuzzy Inference, Human Computer Interaction, Incremental Learning, Internet-based Computing Models, Machine Intelligence, Natural Language Processing, Neural Networks, and Online Decision Support System
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Dr. Lester A. Gerhardt Professor and Chairman Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute Troy, New York 12180 This book is a collection of papers on the subject of Robotics and Artificial Intelligence. Most of the papers contained herein were presented as part of the program of the NATO Advanced Study Institute held in June 1983 at Castel vecchio Pascoli, Italy on the same subject. Attendance at this two week Institute was by invitation only, drawing people internationally representing industry, government and the academic community worldwide. Many of the people in attendance, as well as those presenting papers, are recognized leaders in the field. In addition to the formal paper presentations, there were several informal work­ shops. These included a workshop on sensing, a workshop on educational methodology in the subject area, as examples. This book is an outgrowth and direct result of that Institute and includes the papers presented as well as a few others which were stimulated by that meeting. A special note is the paper entitled "State-of-the-Art and Predictions for Artificial Intelligence and Robotics" by Dr. R. Nagel which appears in the Introduction and Overview chapter of this book. This paper was originally developed as part of a study for the United States Army performed by the National Research Council of the National Academy of Science and published as part of a report entitled "Applications of Robotics and Artificial Intelligence to Reduce Risk and Improve Effectiveness" by National Academy Press in 1983.
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The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across these categories, the robotics laws first proposed by Isaac Asimov in the twentieth century remain well-recognised and esteemed due to their specification of preventing human harm, stipulating obedience to humans and incorporating robotic self-protection. However the overwhelming predominance in the study of this field has focussed on human-robot interactions without fully considering the ethical inevitability of future artificial intelligences communicating together and has not addressed the moral nature of robot-robot interactions. A new robotic law is proposed and termed AIonAI or artificial intelligence-on-artificial intelligence. This law tackles the overlooked area where future artificial intelligences will likely interact amongst themselves, potentially leading to exploitation. As such, they would benefit from adopting a universal law of rights to recognise inherent dignity and the inalienable rights of artificial intelligences. Such a consideration can help prevent exploitation and abuse of rational and sentient beings, but would also importantly reflect on our moral code of ethics and the humanity of our civilisation.
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Robotics is that field concerned with the connection of perception to action. Artificial Intelligence must have a central role in Robotics if the connection is to be intelligent. Artificial Intelligence addresses the crucial questions of: what knowledge is required in any aspect of thinking; how that knowledge should be represented; and how that knowledge should be used Robotics challenges AI by forcing it to deal with real objects in the real world. Techniques and representations developed for purely cognitive problems, often in toy domains, do not necessarily extend to meet the challenge. Robots combine mechanical effectors, sensors, and computers. AI has made significant contributions to each component. We review AI contributions to perception and object oriented reasoning. Object-oriented reasoning includes reasoning about space, path-planning, uncertainty, fitting, and friction. We concluded with three examples that illustrate the kinds of reasoning or problem solving abilities we would like to endow robots with.
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There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting collective behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of collective robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations. 1 Preliminaries There has been much recent activity toward achieving systems of multiple mobile robots engaged in collective behavior. Such systems are of interest for several reasons: (1) tasks may be inherently too complex for a singl...
Stephen Hawking on the future of capitalism and inequality
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