Название: Industry 4.0: Paradoxes and Conflicts Автор: Jean-Claude Andre
Издательство: Wiley-ISTE
Год: 2019
Страниц: 354
Язык: английский
Формат: pdf (true)
Размер: 12.5 MB
Digital technology opens up extraordinary fields for applications that will deeply change the nature of jobs and trade, the very concept of work and the expectations of user–producers. The “masters of algorithms” have disrupted production and services, and this trend will continue for as long as electric energy and the elements of Industry 4.0 are in continued development. Beyond data control, a power struggle is working its way through the links in the value chain: intermediation, control of resources and command over human and physical networks, as well as partnerships, creativity and the political system.
Industry 4.0: Paradoxes and Conflicts examines the need for a serious and technological review, as well as for research and training regarding citizenship and politics. This is a new situation in terms of relationships of competence and authority, which must be the subject of scientific as well as political reflections for the whole social body, which needs to be educated about choices.
The concept of Industry 4.0 was quickly defined in the Preface to this reflection. Whether it is called “Industry 4.0”, as in Europe, the “Internet of Things” (IoT), as in the United States, or simply “Smart Manufacturing”, information and communication technologies (ICTs) are seriously reshaping modern manufacturing. Indeed, this digitization of manufacturing is likely to transform many of the industry’s production methods: the way in which products are sought to reach a market (design), and the way in which they are designed, manufactured and produced, distributed and consumed in relation to manufacturing supply/demand, possibly even individualized.
To put it simply, Artificial intelligence (AI), unlike conventional machines used in factories, is designed to exploit not only digital data, but also symbolic and non-numerical information (letters–words–signs–shapes–drawings–concepts–knowledge–reasoning). Under these conditions, as for humans, one cannot expect absolute perfection from AI. Mistakes can be made, even by the most intelligent of AI systems (and naturally also by humans, but with a lower frequency!).
Throughout the book, the author poses the following question: instead of submitting to choices, would it not be better to exercise foresight?
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